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Adjusting Featured Snippet Answers by Context

November 27, 2020 No Comments

How Are Featured Snippet Answers Decided Upon?

I recently wrote about Featured Snippet Answer Scores Ranking Signals. In that post, I described how Google was likely using query dependent and query independent ranking signals to create answer scores for queries that were looking like they wanted answers.

One of the inventors of that patent from that post was Steven Baker. I looked at other patents that he had written, and noticed that one of those was about context as part of query independent ranking signals for answers.

Remembering that patent about question-answering and context, I felt it was worth reviewing that patent and writing about it.

This patent is about processing question queries that want textual answers and how those answers may be decided upon.

it is a complicated patent, and at one point the description behind it seems to get a bit murky, but I wrote about when that happened in the patent, and I think the other details provide a lot of insight into how Google is scoring featured snippet answers. There is an additional related patent that I will be following up with after this post, and I will link to it from here as well.

This patent starts by telling us that a search system can identify resources in response to queries submitted by users and provide information about the resources in a manner that is useful to the users.

How Context Scoring Adjustments for Featured Snippet Answers Works

Users of search systems are often searching for an answer to a specific question, rather than a listing of resources, like in this drawing from the patent, showing featured snippet answers:

featured snippet answers

For example, users may want to know what the weather is in a particular location, a current quote for a stock, the capital of a state, etc.

When queries that are in the form of a question are received, some search engines may perform specialized search operations in response to the question format of the query.

For example, some search engines may provide information responsive to such queries in the form of an “answer,” such as information provided in the form of a “one box” to a question, which is often a featured snippet answer.

Some question queries are better served by explanatory answers, which are also referred to as “long answers” or “answer passages.”

For example, for the question query [why is the sky blue], an answer explaining light as waves is helpful.

featured snippet answers - why is the sky blue

Such answer passages can be selected from resources that include text, such as paragraphs, that are relevant to the question and the answer.

Sections of the text are scored, and the section with the best score is selected as an answer.

In general, the patent tells us about one aspect of what it covers in the following process:

  • Receiving a query that is a question query seeking an answer response
  • Receiving candidate answer passages, each passage made of text selected from a text section subordinate to a heading on a resource, with a corresponding answer score
  • Determining a hierarchy of headings on a page, with two or more heading levels hierarchically arranged in parent-child relationships, where each heading level has one or more headings, a subheading of a respective heading is a child heading in a parent-child relationship and the respective heading is a parent heading in that relationship, and the heading hierarchy includes a root level corresponding to a root heading (for each candidate answer passage)
  • Determining a heading vector describing a path in the hierarchy of headings from the root heading to the respective heading to which the candidate answer passage is subordinate, determining a context score based, at least in part, on the heading vector, adjusting the answer score of the candidate answer passage at least in part by the context score to form an adjusted answer score
  • Selecting an answer passage from the candidate answer passages based on the adjusted answer scores

Advantages of the process in the patent

  1. Long query answers can be selected, based partially on context signals indicating answers relevant to a question
  2. The context signals may be, in part, query-independent (i.e., scored independently of their relatedness to terms of the query
  3. This part of the scoring process considers the context of the document (“resource”) in which the answer text is located, accounting for relevancy signals that may not otherwise be accounted for during query-dependent scoring
  4. Following this approach, long answers that are more likely to satisfy a searcher’s informational need are more likely to appear as answers

This patent can be found at:

Context scoring adjustments for answer passages
Inventors: Nitin Gupta, Srinivasan Venkatachary , Lingkun Chu, and Steven D. Baker
US Patent: 9,959,315
Granted: May 1, 2018
Appl. No.: 14/169,960
Filed: January 31, 2014

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for context scoring adjustments for candidate answer passages.

In one aspect, a method includes scoring candidate answer passages. For each candidate answer passage, the system determines a heading vector that describes a path in the heading hierarchy from the root heading to the respective heading to which the candidate answer passage is subordinate; determines a context score based, at least in part, on the heading vector; and adjusts answer score of the candidate answer passage at least in part by the context score to form an adjusted answer score.

The system then selects an answer passage from the candidate answer passages based on the adjusted answer scores.

Using Context Scores to Adjust Answer Scores for Featured Snippets

A drawing from the patent shows different hierarchical headings that may be used to determine the context of answer passages that may be used to adjust answer scores for featured snippets:

Hierarchical headings for featured snippets

I discuss these headings and their hierarchy below. Note that the headings include the Page title as a heading (About the Moon), and the headings within heading elements on the page as well. And those headings give those answers context.

This context scoring process starts with receiving candidate answer passages and a score for each of the passages.

Those candidate answer passages and their respective scores are provided to a search engine that receives a query determined to be a question.

Each of those candidate answer passages is text selected from a text section under a particular heading from a specific resource (page) that has a certain answer score.

For each resource where a candidate answer passage has been selected, a context scoring process determines a heading hierarchy in the resource.

A heading is text or other data corresponding to a particular passage in the resource.

As an example, a heading can be text summarizing a section of text that immediately follows the heading (the heading describes what the text is about that follows it, or is contained within it.)

Headings may be indicated, for example, by specific formatting data, such as heading elements using HTML.

This next section from the patent reminded me of an observation that Cindy Krum of Mobile Moxie has about named anchors on a page, and how Google might index those to answer a question, to lead to an answer or a featured snippet. She wrote about those in What the Heck are Fraggles?

A heading could also be anchor text for an internal link (within the same page) that links to an anchor and corresponding text at some other position on the page.

A heading hierarchy could have two or more heading levels that are hierarchically arranged in parent-child relationships.

The first level, or the root heading, could be the title of the resource.

Each of the heading levels may have one or more headings, and a subheading of a respective heading is a child heading and the respective heading is a parent heading in the parent-child relationship.

For each candidate passage, a context scoring process may determine a context score based, at least in part, on the relationship between the root heading and the respective heading to which the candidate answer passage is subordinate.

The context scoring process could be used to determine the context score and determines a heading vector that describes a path in the heading hierarchy from the root heading to the respective heading.

The context score could be based, at least in part, on the heading vector.

The context scoring process can then adjust the answer score of the candidate answer passage at least in part by the context score to form an adjusted answer score.

The context scoring process can then select an answer passage from the candidate answer passages based on adjusted answer scores.

This flowchart from the patent shows the context scoring adjustment process:

context scoring adjustment flowchart

Identifying Question Queries And Answer Passages

I’ve written about understanding the context of answer passages. The patent tells us more about question queries and answer passages worth going over in more detail.

Some queries are in the form of a question or an implicit question.

For example, the query [distance of the earth from the moon] is in the form of an implicit question “What is the distance of the earth from the moon?”

An implicit question - the distance from the earth to the moon

Likewise, a question may be specific, as in the query [How far away is the moon].

The search engine includes a query question processor that uses processes that determine if a query is a query question (implicit or specific) and if it is, whether there are answers that are responsive to the question.

The query question processor can use several different algorithms to determine whether a query is a question and whether there are particular answers responsive to the question.

For example, it may use to determine question queries and answers:

  • Language models
  • Machine learned processes
  • Knowledge graphs
  • Grammars
  • Combinations of those

The query question processor may choose candidate answer passages in addition to or instead of answer facts. For example, for the query [how far away is the moon], an answer fact is 238,900 miles. And the search engine may just show that factual information since that is the average distance of the Earth from the moon.

But, the query question processor may choose to identify passages that are to be very relevant to the question query.

These passages are called candidate answer passages.

The answer passages are scored, and one passage is selected based on these scores and provided in response to the query.

An answer passage may be scored, and that score may be adjusted based on a context, which is the point behind this patent.

Often Google will identify several candidate answer passages that could be used as featured snippet answers.

Google may look at the information on the pages where those answers come from to better understand the context of the answers such as the title of the page, and the headings about the content that the answer was found within.

Contextual Scoring Adjustments for Featured Snippet Answers

The query question processor sends to a context scoring processor some candidate answer passages, information about the resources from which each answer passages was from, and a score for each of the featured snippet answers.

The scores of the candidate answer passages could be based on the following considerations:

  • Matching a query term to the text of the candidate answer passage
  • Matching answer terms to the text of the candidate answer passages
  • The quality of the underlying resource from which the candidate answer passage was selected

I recently wrote about featured snippet answer scores, and how a combination of query dependent and query independent scoring signals might be used to generate answer scores for answer passages.

The patent tells us that the query question processor may also take into account other factors when scoring candidate answer passages.

Candidate answer passages can be selected from the text of a particular section of the resource. And the query question processor could choose more than one candidate answer passage from a text section.

We are given the following examples of different answer passages from the same page

(These example answer passages are referred to in a few places in the remainder of the post.)

  • (1) It takes about 27 days (27 days, 7 hours, 43 minutes, and 11.6 seconds) for the Moon to orbit the Earth at its orbital distance
  • (2) Why is the distance changing? The moon’s distance from Earth varies because the moon travels in a slightly elliptical orbit. Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles
  • (3) The moon’s distance from Earth varies because the moon travels in a slightly elliptical orbit. Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles

Each of those answers could be good ones for Google to use. We are told that:

More than three candidate answers can be selected from the resource, and more than one resource can be processed for candidate answers.

How would Google choose between those three possible answers?

Google might decide based on the number of sentences and a selection of up to a maximum number of characters.

The patent tells us this about choosing between those answers:

Each candidate answer has a corresponding score. For this example, assume that candidate answer passage (2) has the highest score, followed by candidate answer passage (3), and then by candidate answer passage (1). Thus, without the context scoring processor, candidate answer passage (2) would have been provided in the answer box of FIG. 2. However, the context scoring processor takes into account the context of the answer passages and adjusts the scores provided by the query question processor.

So, we see that what might be chosen based on featured snippet answer scores could be adjusted based on the context of that answer from the page that it appears on.

Contextually Scoring Featured Snippet Answers

This process starts which begins with a query determined to be a question query seeking an answer response.

This process next receives candidate answer passages, each candidate answer passage chosen from the text of a resource.

Each of the candidate answer passages are text chosen from a text section that is subordinate to a respective heading (under a heading) in the resource and has a corresponding answer score.

For example, the query question processor provides the candidate answer passages, and their corresponding scores, to the context scoring processor.

A Heading Hierarchy to Determine Context

This process then determines a heading hierarchy from the resource.

The heading hierarchy would have two or more heading levels hierarchically arranged in parent-child relationships (Such as a page title, and an HTML heading element.)

Each heading level has one or more headings.

A subheading of a respective heading is a child heading (an (h2) heading might be a subheading of a (title)) in the parent-child relationship and the respective heading is a parent heading in the relationship.

The heading hierarchy includes a root level corresponding to a root heading.

The context scoring processor can process heading tags in a DOM tree to determine a heading hierarchy.

hierarchical headings for featured snippets

For example, concerning the drawing about the distance to the moon just above, the heading hierarchy for the resource may be:

The ROOT Heading (title) is: About The Moon (310)

The main heading (H1) on the page

H1: The Moon’s Orbit (330)

A secondary heading (h2) on the page:

H2: How long does it take for the Moon to orbit Earth? (334)

Another secondary heading (h2) on the page is:

H2: The distance from the Earth to the Moon (338)

Another Main heading (h1) on the page

H1: The Moon (360)

Another secondary Heading (h2) on the page:

H2: Age of the Moon (364)

Another secondary heading (h2) on the page:

H2: Life on the Moon (368)

Here is how the patent describes this heading hierarchy:

In this heading hierarchy, The title is the root heading at the root level; headings 330 and 360 are child headings of the heading, and are at a first level below the root level; headings 334 and 338 are child headings of the heading 330, and are at a second level that is one level below the first level, and two levels below the root level; and headings 364 and 368 are child headings of the heading 360 and are at a second level that is one level below the first level, and two levels below the root level.

The process from the patent determines a context score based, at least in part, on the relationship between the root heading and the respective heading to which the candidate answer passage is subordinate.

This score may be is based on a heading vector.

The patent says that the process, for each of the candidate answer passages, determines a heading vector that describes a path in the heading hierarchy from the root heading to the respective heading.

The heading vector would include the text of the headings for the candidate answer passage.

For the example candidate answer passages (1)-(3) above about how long it takes the moon to orbit the earch, the respectively corresponding heading vectors V1, V2 and V3 are:

  • V1=<[Root: About The Moon], [H1: The Moon's Orbit], [H2: How long does it take for the Moon to orbit the Earth?]>
  • V2=<[Root: About The Moon], [H1: The Moon's Orbit], [H2: The distance from the Earth to the Moon]>
  • V3=<[Root: About The Moon], [H1: The Moon's Orbit], [H2: The distance from the Earth to the Moon]>

We are also told that because candidate answer passages (2) and (3) are selected from the same text section 340, their respective heading vectors V2 and V3 are the same (they are both in the content under the same (H2) heading.)

The process of adjusting a score, for each answer passage, uses a context score based, at least in part, on the heading vector (410).

That context score can be a single score used to scale the candidate answer passage score or can be a series of discrete scores/boosts that can be used to adjust the score of the candidate answer passage.

Where things Get Murky in This Patent

There do seem to be several related patents involving featured snippet answers, and this one which targets learning more about answers from their context based on where they fit in a heading hierarchy makes sense.

But, I’m confused by how the patent tells us that one answer based on the context would be adjusted over another one.

The first issue I have is that the answers they are comparing in the same contextual area have some overlap. Here those two are:

  • (2) Why is the distance changing? The moon’s distance from Earth varies because the moon travels in a slightly elliptical orbit. Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles
  • (3) The moon’s distance from Earth varies because the moon travels in a slightly elliptical orbit. Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles

Note that the second answer and the third answer both include the same line: “Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles.” I find myself a little surprised that the second answer includes a couple of sentences that aren’t in the third answer, and skips a couple of lines from the third answer, and then includes the last sentence, which answers the question.

Since they both appear in the same heading and subheading section of the page they are from, it is difficult to imagine that there is a different adjustment based on context. But, the patent tells us differently:

The candidate answer score with the highest adjusted answer score (based on context from the headings) is selected, and the answer passage.

Recall that in the example above, the candidate answer passage (2) had the highest score, followed by candidate answer passage (3), and then by candidate answer passage (1).

However, after adjustments, candidate answer passage (3) has the highest score, followed by candidate answer passage (2), and then-candidate answer passage (1).

Accordingly, candidate answer passage (3) is selected and provided as the answer passage of FIG. 2.

Boosting Scores Based on Passage Coverage Ratio

A query question processor may limit the candidate answers to a maximum length.

The context scoring processor determines a coverage ratio which is a measure indicative of the coverage of the candidate answer passage from the text from which it was selected.

The patent describes alternative question answers:

Alternatively, the text block may include text sections subordinate to respective headings that include a first heading for which the text section from which the candidate answer passage was selected is subordinate, and sibling headings that have an immediate parent heading in common with the first heading. For example, for the candidate answer passage, the text block may include all the text in the portion 380 of the hierarchy; or may include only the text of the sections, of some other portion of text within the portion of the hierarchy. A similar block may be used for the portion of the hierarchy for candidate answer passages selected from that portion.

A small coverage ratio may indicate a candidate answer passage is incomplete. A high coverage ratio may indicate the candidate answer passage captures more of the content of the text passage from which it was selected. A candidate answer passage may receive a context adjustment, depending on this coverage ratio.

A passage coverage ratio is a ratio of the total number of characters in the candidate answer passage to the ratio of the total number of characters in the passage from which the candidate answer passage was selected.

The passage cover ratio could also be a ratio of the total number of sentences (or words) in the candidate answer passage to the ratio of the total number of sentences (or words) in the passage from which the candidate answer passage was selected.

We are told that other ratios can also be used.

From the three example candidate answer passages about the distance to the moon above (1)-(3) above, passage (1) has the highest ratio, passage (2) has the second-highest, and passage (3) has the lowest.

This process determines whether the coverage ratio is less than a threshold value. That threshold value can be, for example, 0.3, 0.35 or 0.4, or some other fraction. In our “distance to the moon” example, each coverage passage ratio meets or exceeds the threshold value.

If the coverage ratio is less than a threshold value, then the process would select a first answer boost factor. The first answer boost factor might be proportional to the coverage ratio according to a first relation, or maybe a fixed value, or maybe a non-boosting value (e.g., 1.0.)

But if the coverage ratio is not less than the threshold value, the process may select a second answer boost factor. The second answer boost factor may be proportional to the coverage ratio according to a second relation, or maybe fixed value, or maybe a value greater than the non-boosting value (e.g., 1.1.)

Scoring Based on Other Features

The context scoring process can also check for the presence of features in addition to those described above.

Three example features for contextually scoring an answer passage can be based on the additional features of the distinctive text, a preceding question, and a list format.

Distinctive text

Distinctive text is the text that may stand out because it is formatted differently than other text, like using bolding.

A Preceeding Question

A preceding question is a question in the text that precedes the candidate answer question.

The search engine may process various amounts of text to detect for the question.

Only the passage from which the candidate answer passage is extracted is detected.

A text window that can include header text and other text from other sections may be checked.

A boost score that is inversely proportional to the text distance from a question to the candidate answer passage is calculated, and the check is terminated at the occurrence of a first question.

That text distance may be measured in characters, words, or sentences, or by some other metric.

If the question is anchor text for a section of text and there is intervening text, such as in the case of a navigation list, then the question is determined to only precede the text passage to which it links, not precede intervening text.

In the drawing above about the moon, there are two questions in the resource: “How long does it take for the Moon to orbit Earth?” and “Why is the distance changing?”

The first question–“How long does it take for the Moon to orbit Earth?”– precedes the first candidate answer passage by a text distance of zero sentences, and it precedes the second candidate answer passage by a text distance of five sentences.

And the second question–“Why is the distance changing?”– precedes the third candidate answer by zero sentences.

If a preceding question is detected, then the process selects a question boost factor.

This boost factor may be proportional to the text distance, whether the text is in a text passage subordinate to a header or whether the question is a header, and, if the question is in a header, whether the candidate answer passage is subordinate to the header.

Considering these factors, the third candidate answer passage receives the highest boost factor, the first candidate answer receives the second-highest boost factor, and the second candidate answer receives the smallest boost factor.

Conversely, if the preceding text is not detected, or after the question boost factor is detected, then the process detects for the presence of a list.

The Presence of a List

A list is an indication of several steps usually instructive or informative. The detection of a list may be subject to the query question being a step modal query.

A step modal query is a query where a list-based answer is likely to a good answer. Examples of step model queries are queries like:

  • [How to . . . ]
  • [How do I . . . ]
  • [How to install a door knob]
  • [How do I change a tire]

The context scoring process may detect lists formed with:

  • HTML tags
  • Micro formats
  • Semantic meaning
  • Consecutive headings at the same level with the same or similar phrases (e.g., Step 1, Step 2; or First; Second; Third; etc.)

The context scoring process may also score a list for quality.

It would look at things such as:

  • A list in the center of a page, which does not include multiple links to other pages (indicative of reference lists)
  • HREF link text that does not occupy a large portion of the text of the list will be of higher quality than a list at the side of a page, and which does include multiple links to other pages (which are indicative of reference lists), and/are has HREF link text that does occupy a large portion of the text of the list

If a list is detected, then the process selects a list boost factor.

That list boost factor may be fixed or may be proportional to the quality score of the list.

If a list is not detected, or after the list boost factor is selected, the process ends.

In some implementations, the list boost factor may also be dependent on other feature scores.

If other features, such as coverage ratio, distinctive text, etc., have relatively high scores, then the list boot factor may be increased.

The patent tells us that this is because “the combination of these scores in the presence of a list is a strong signal of a high-quality answer passage.”

Adjustment of Featured Snippet Answers Scores

Answer scores for candidate answer passages are adjusted by scoring components based on heading vectors, passage coverage ratio, and other features described above.

The scoring process can select the largest boost value from those determined above or can select a combination of the boost values.

Once the answer scores are adjusted, the candidate answer passage with the highest adjusted answer score is selected as the featured snippet answer and is displayed to a searcher.

More to Come

I will be reviewing the first patent in this series of patents about candidate answer scores because it does have some additional elements to it that haven’t been covered in this post, and the post about query dependent/independent ranking signals for answer scores. If you have been paying attention to how Google has been answering queries that appear to be seeking answers, you have likely seen those improving in many cases. Some answers have been really bad though. It will be nice to have as complete an idea as we can of how Google decides what might be a good answer to a query, based on information available to them on the Web.

Added October 14, 2020 – I have written about another Google patent on Answer Scores, and it’s worth reading about all of the patents on this topic. The new post is at Weighted Answer Terms for Scoring Answer Passages, and is about the patent Weighted answer terms for scoring answer passages.

It is about identifying questions in resources, and answers for those questions, and describes using term weights as a way to score answer passages (along with the scoring approaches identified in the other related patents, including this one.)

Added October 15, 2020 – I have written a few other posts about answer passages that are worth reading if you are interested in how Google finds questions on pages and answers to those, and scores answer passages to determine which ones to show as featured snippets. I’ve linked to some of those in the body of this post, but here is another one of those posts:

Added October 22, 2020, I have written up a description of details from about how structured and unstructured data has been selected for answer passages based on specific criteria in the patent on Scoring Answer passages in the post Selecting Candidate Answer Passages.


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Pinterest tests online events with dedicated ‘class communities’

November 25, 2020 No Comments

Pinterest is getting into online events. The company has been spotted testing a new feature that allows users to sign up for Zoom classes through Pinterest, while creators use Pinterest’s class boards to organize class materials, notes and other resources, or even connect with attendees through a group chat option. The company confirmed the test of online classes is an experiment now in development, but wouldn’t offer further details about its plans.

The feature itself was discovered on Tuesday by reverse engineer Jane Manchun Wong, who found details about the online classes by looking into the app’s code.

Currently, you can visit some of these “demo” profiles directly — like “@pinsmeditation” or “@pinzoom123,” for example — and view their listed Class Communities. However, these communities are empty when you click through. That’s because the feature is still unreleased, Wong says.

When and if the feature is later launched to the public, the communities would include dedicated sections where creators will be able to organize their class materials — like lists of what to bring to class, notes, photos and more. They could also use these communities to offer a class overview and description, connect users to a related shop, group chat feature and more.

Creators are also able to use the communities — which are basically enhanced Pinterest boards — to respond to questions from attendees, share photos from the class and otherwise interact with the participants.

When a user wants to join a class, they can click a “book” button to sign up, and are then emailed a confirmation with the meeting details. Other buttons direct attendees to download Zoom or copy the link to join the class.

It’s not surprising that Pinterest would expand into the online events space, given its platform has become a popular tool for organizing remote learning resources during the coronavirus pandemic. Teachers have turned to Pinterest to keep track of lesson plans, get inspiration, share educational activities and more. In the early days of the pandemic, Pinterest reported record usage when the company saw more searches and saves globally in a single March weekend than ever before in its history, as a result of its usefulness as a online organizational tool.

This growth has continued throughout the year. In October, Pinterest’s stock jumped on strong earnings after the company beat on revenue and user growth metrics. The company brought in $ 443 million in revenue, versus $ 383.5 million expected, and grew its monthly active users to 442 million, versus the 436.4 million expected. Outside of the coronavirus impacts, much of this growth was due to strong international adoption, increased ad spend from advertisers boycotting Facebook and a surge of interest from users looking for iOS 14 home screen personalization ideas.

Given that the U.S. has failed to get the COVID-19 pandemic under control, many classes, events and other activities will remain virtual even as we head into 2021. The online events market may continue to grow in the years that follow, too, thanks to the kickstart the pandemic provided the industry as a whole.

“We are experimenting with ways to help creators interact more closely with their audience,” a Pinterest spokesperson said, when asked for more information.

Pinterest wouldn’t confirm additional details about its plans for online events, but did say the feature was in development and the test would help to inform the product’s direction.

Pinterest often tries out new features before launching them to a wider audience. Earlier this summer, TechCrunch reported on a Story Pins feature the company had in the works. Pinterest then launched the feature in September. If the same time frame holds up for online events, we could potentially see the feature become more widely available sometime early next year.


Social – TechCrunch


Join us for a live Q&A with Sapphire’s Jai Das on Tuesday at 2 pm ET/11 am PT

November 25, 2020 No Comments

Sure, we’re heading into a holiday weekend here in America, but that doesn’t mean that the good ship TechCrunch is going to slow down. We’re diving right back in next week with another installment in season two of Extra Crunch Live, our regular interview series with startup founders, venture capitalists, and other leaders from the technology community.

This series is for Extra Crunch members, so if you haven’t signed up you can hop on that train right here.

Next week I’m virtually sitting down with Jai Das, a well-known managing director at Sapphire Ventures.

Das as invested in companies like MuleSoft (sold for $ 6.5 billion), Alteryx (now public), Square (also public), Sumo Logic (yep, public) while at Sapphire, having previously worked corporate venture jobs at Intel Capital and Agilent Ventures. (Sapphire was itself originally SAP’s corporate venture capital arm, but it split off from its parent in 2011, rebranded, and kept on raising funds.)

Here are notes from the last episode of Extra Crunch Live with Bessemer’s Byron Deeter.

It’s going to be fun as there’s so much to talk about. I’m still bubbling up my question list, so to avoid giving the Sapphire PR team too much pre-discussion ammo let’s just say that corporate venture capital’s place in the 2020 boom is an interesting topic for both founders, and investors alike.

And I’ll want to press Das on the current market for software startups, where we are in the historical arc of SaaS multiples, the importance of API-led tech upstarts, where founders might look to build the next great enterprise startup, and if there are any new platforms bubbling up that could be a foundation for future founders to later leverage.

As this is an Extra Crunch Live, I’ll also work in a few questions from the audience (that means you, make sure you Extra Crunch subscription is live), to augment my own clipboard of notes.

This is going to be a good one. I’ll see you next Tuesday for the show.

Details

Below are links to add the event to your calendar and to save the Zoom link. We’ll share the YouTube link shortly before the discussion:


Startups – TechCrunch


10 Effective ways to boost click-through rate (CTR) using SERPs

November 25, 2020 No Comments

30-second summary:

  • Search engine ranking pages and algorithms are evolving quickly and you should keep pace with them to succeed.
  • Did you know, 51% of all searches end without a click?
  • Gone are the days when there are only organic text-based results on the page.
  • Today, there are paid listings, zero-click searches, images, videos, maps, featured snippets, people also asked for boxes, and even podcasts that result in dismal click-through rates (CTRs).
  • Branex’s digital marketing strategist, Irfan Ak has created a top 10 list that can boost your CTR in Google SERPs.

If you closely look at the first page of Google for any competitive keyword, you will find tons of elements on it. Gone are the days when there are only organic text-based results on the page. Today, there are images, videos, maps, featured snippets, people also asked for boxes, and even podcasts. Then there are paid listings which are visible on top of organic listings. SEO trends are changing quickly and it is impacting search engine results pages (SERPs). All this translates into declining organic reach, dismal click-through rate (CTR), and the rise of zero-click searches.

In fact, 51% of all searches end without a click. With search engines trying their best to fulfill user needs on search pages itself, fewer users will scroll down and click through your listing as they get the desired answer on the search page.

In this article, you will learn about ten effective ways to boost click-through rate (CTR) using SERPs.

How to increase click-through rate (CTR) - Stats

Source: SparkToro

1. Optimize for featured snippets

The coveted number one spot is no longer the target for digital marketers and digital marketing agencies. The focus has shifted to Position Zero. According to Ahrefs study, 12.3% of search queries have featured snippets. Search engines like Google pull data from the top 10 results to show as a featured snippet. If your blog or website is ranking on the first page of Google, you have an opportunity to grab the featured snippet and boost your visibility.

To do so, you need to understand the purpose of featured snippets. The main reason why search engines show featured snippets is that they want to provide a direct answer to a search query and if your listing does that, you have a bright chance of getting featured on a much sought-after position zero. 

Add featured snippets to increase click-through rate (CTR)

Source: Ahrefs

Secondly, featured snippets are displayed for long-tail keywords or questions-based queries. The focus is usually on offering short and precise answers to the user query and if your listing can do that while optimizing for long-tail keywords, it can rank on featured snippets. 

2. Improve your rankings

According to a study conducted by Backlnko which analyzed 5 million Google search results, moving one spot up can increase your click-through rate by almost 30.8%. Even though, this might vary depending on your current position and the position you have moved to. The same study also found that jumping from 10th position to 7th position did not have the same impact as moving from 6th position to 5th position or 2nd position to 1st position might have on your click-through rate. Instead of striving for ranking on the first page of Google, you should focus on ranking in the top three positions as 75.1% of all clicks go to the top three spots.

Click-through rate (CTR) organic - breakdown stats

Source: Backlinko

3. Write captivating headlines

David Ogilvy, the “Father of Advertising” and Founder of Ogilvy & Mather, once said,

“On the average, five times as many people read the headline as read the body copy. When you have written your headline, you have spent eighty cents out of your dollar.”

What is the first thing that users will read when they look at your listing? It is the headline. It can literally make it or break it for you. That is why it is important to write attention-grabbing headlines. Add an emotional element to your headline as research has shown that including positive or negative sentiments to your headlines can increase its click-through rate by 7%. Backlinko’s study I referenced above also found that titles that contain 15-40 characters have the highest organic click-through rate.

4. Meta description and URL

Have you ever seen a search result closely? What does it contain? A search engine listing usually comprises of three things

  • Title
  • URL
  • Meta Description

After optimizing your title, you should focus on optimizing your URL and meta description for click-through rate. Add your keyword in the URL as it will increase your clickthrough rate by 45% as compared to URLs that don’t contain the keyword.

Just like the title and URL, add your keyword in the meta description as well. Write a meta description in active voice and try to make it as actionable as possible. Don’t forget to add a call to action to persuade users to click on your listings. Make sure all the pages on your website have a meta description because pages that contain the meta description generate 5.8% more clicks than pages without meta description.

5. Add a schema markup

Search engines use a spider to crawl web pages and create an index of all those pages. The easier it is for search engines to crawl your website, the faster they will crawl your website and more likely your website to get indexed and ranked. By adding schema markup to your website, you can make it easy for search engines to understand what your website is all about and how different pages on your website covers.

There are different types of schema markups and implementing the right kind on your website can do wonders. For example, a review schema markup allows search engines to display ratings in your organic results. If your rating is good, it can increase your credibility, build trust, and help you attract new customers while increasing your click-through rate.

6. Optimize for Google My Business

Do you have a Google My Business page? If your answer is no, then you are missing out. Get your business featured on Google My Business and enter all the business details. Whether it is location-based searches, branded searches, or business-related or service-related searches, Google My Business results tend to show up.

Another advantage of using Google My Business is that it allows you to collect reviews and ratings from customers as well as allows your business to answer user questions. Both can help you build trust and win new customers. The more positive reviews your business has or the higher the rating, the better. It also offers some useful features to customers such as sharing business information with others or contacting the business directly.

7. Run well-targeted PPC ads

One of the best ways to overcome declining organic reach is to invest in PPC ads. Yes, they might be expensive in certain industries and might not work that well in other industries but if you are looking for quick results, PPC ads are your best bet, provided your PPC targeting strategy is on the money. Run PPC ads on branded keywords and prevent others from occupying your ad space. 

When you run PPC ads, it attracts targeted traffic that is more likely to convert into paying customers. This means that it not only increases your click-through rate but also increases your conversion rates too. The key to success with PPC ads is to choose the right ad type according to your industry.

8. Optimize images and videos for SEO

As mentioned before, SERPs are no longer limited to showing organic results anymore. They also show images, videos, and featured snippets to name just a few. What’s even more interesting is the fact that SERPs showing images and videos are slowly but surely increasing in number. This means that you can optimize your images and videos to increase your chances of ranking on these SERPs.

Here are some of the ways you can use to optimize images for SEO.

  • Use targeted keywords in image and video title, description, and alternate text
  • Place the image and video in a section of the page or in content where it best matches the keyword intent
  • Compress large size images and videos
  • Add a caption to images
  • Use common image sizes and optimal image formats

9. Give an irresistible limited time offer

Create a sense of urgency and use tactics such as countdown timer or mention the number of items remaining. When a user sees these things on your page, they are rushed into taking the desired action. Give a limited time offer that your target audience cannot resist, and you will see your clickthrough rate shoot through the roof. Don’t forget to add a call to action that tells users which action they should take next.

10. Optimize social media channel to show up in knowledge panels

Last but certainly not least is to optimize social media pages for knowledge panels. Search engines display these knowledge panels in order to present all your business information in a concise way. As a business, you can use this as an opportunity to connect your social media accounts and let users contact you directly from search engine results pages. For this process to work, all your social media accounts should pass the verification by Google. You can also use schema markup to highlight your social media accounts.

How do you boost your click-through rate using search engine result pages? Let us know in the comments section below.

Irfan Ak is an experienced digital marketing strategist, growth hacker, digital transformation expert at Branex. He can be found on Twitter @irrfanAK.

The post 10 Effective ways to boost click-through rate (CTR) using SERPs appeared first on Search Engine Watch.

Search Engine Watch


Proxyclick visitor management system adapts to COVID as employee check-in platform

November 24, 2020 No Comments

Proxyclick began life by providing an easy way to manage visitors in your building with an iPad-based check-in system. As the pandemic has taken hold, however, customer requirements have changed, and Proxyclick is changing with them. Today the company announced Proxyclick Flow, a new system designed to check in employees during the time of COVID.

“Basically when COVID hit our customers told us that actually our employees are the new visitors. So what you used to ask your visitors, you are now asking your employees — the usual probing question, but also when are you coming and so forth. So we evolved the offering into a wider platform,” Proxyclick co-founder and CEO Gregory Blondeau explained.

That means instead of managing a steady flow of visitors — although it can still do that — the company is focusing on the needs of customers who want to open their offices on a limited basis during the pandemic, based on local regulations. To help adapt the platform for this purpose, the company developed the Proovr smartphone app, which employees can use to check in prior to going to the office, complete a health checklist, see who else will be in the office and make sure the building isn’t over capacity.

When the employee arrives at the office, they get a temperature check, and then can use the QR code issued by the Proovr app to enter the building via Proxyclick’s check-in system or whatever system they have in place. Beyond the mobile app, the company has designed the system to work with a number of adjacent building management and security systems so that customers can use it in conjunction with existing tooling.

They also beefed up the workflow engine that companies can adapt based on their own unique entrance and exit requirements. The COVID workflow is simply one of those workflows, but Blondeau recognizes not everyone will want to use the exact one they have provided out of the box, so they designed a flexible system.

“So the challenge was technical on one side to integrate all the systems, and afterwards to group workflows on the employee’s smartphone, so that each organization can define its own workflow and present it on the smartphone,” Blondeau said.

Once in the building, the systems registers your presence and the information remains on the system for two weeks for contact tracing purposes should there be an exposure to COVID. You check out when you leave the building, but if you forget, it automatically checks you out at midnight.

The company was founded in 2010 and has raised $ 19.6 million. The most recent raise was a $ 18.5 million Series B in January.


Enterprise – TechCrunch


Harness the power of integrated CRO and social media

November 24, 2020 No Comments

30-second summary:

  • Promote brand awareness if you want customers to know you exist.
  • Collect social reviews and testimonials like you’re collecting candy.
  • User-generated content builds authenticity which means higher conversions.
  • Stay up to date on customer support so your leads are happy.
  • Use the FOMO (fear of missing out) concept to your advantage.

Do you have a new content marketing agency or ecommerce business? Or are you getting irrelevant traffic that doesn’t convert from your marketing campaigns? Is your business model just not resonating with your audience?

Perhaps, it is time to shift your focus on Conversion Rate Optimization (CRO) and social media marketing.

Social media is where your audience lives these days. According to Oberlo, about 45% of the world population is on social media. 

stat - CRO

Source: Oberlo

But note that getting traffic from social media is only winning half the battle of scaling your business. 

Regardless of whether you’ve got a SaaS startup, a cute pet toy company, or even if you’re just a drop shipper, you need to convert that traffic to drive sales.

And it will happen only when your audience takes the desired action like buying a product or signing up to your newsletter. 

Thus, your business should focus on increasing the number of visitors who complete a conversion. 

The process is known as Conversion Rate Optimization (CRO). 

Here’s what Skylar Reeves, founder of Ardent Growth, has to say about the benefits of CRO

“One of the biggest benefits of conversion rate optimization is the sheer ROI it can deliver without a linear increase in budget. There are often many small changes you can make to your marketing or advertising strategy that can increase your conversion rate dramatically – and that can make a huge difference to your annual revenue.”

By integrating CRO and social media, your business not only gets good traffic but increases sales as well. 

Let’s have a look at how you can leverage integrated CRO and social media for your business:

1. Create brand awareness

Online awareness about your brand will be created when people find you on search engines, via paid advertising, earned media, social media, link building, and more.

For instance, you can use social channels like Facebook to create brand awareness since it’s the most widely used social channel with 2.6 billion monthly active users.

Flipping the script, you can earn great brand mentions on popular blogs in your space, increasing brand awareness to relevant audiences

CRO - create brand awareness

Source: uSERP

If your company primarily caters B2B, an awesome tactic would be utilizing LinkedIn automation tools to generate leads from the popular social networking service. If you’re struggling to plan out your brand-building strategy, then try using product roadmap software.

Platonik’s Fraser McCulloch says,

“There are an estimated 7.5 billion searches a day on Google, the world’s biggest buyer research tool, figure out what problems prospects are searching for and give them solutions; that’s a better way to build a brand that people want.”

When you set up a social media account, you can optimize your account descriptions and keep it active and interactive with relevant content that converts. It will help you to get more traffic to your landing pages and, more than likely, conversions.

Mobile Marketer found out that 90% of people purchase from brands they follow on social media.

And of course, by connecting with your audience in real-time via social channels, you will be building a good relationship with them.

2. Get social reviews

CEO of Transcription Outsourcing LLC Ben Walker backs the importance of social reviews quite bluntly

“What I do — and what you should do — is use social proof to help convince new clients that your service is up to par.”

There is a good 72% percent of people who won’t take any action until they read reviews. The same poll suggests that 5% of users say they don’t trust businesses that don’t have reviews.

Search Pros founder Isaac Hammelburger has utilized customer reviews on his site and has been met with what seems to be an obvious success

“I’ve been able to increase lead gen calls by more than 20% after I started including reviews and testimonials on my site. Most companies can also boost their bottom line by leveraging this aspect of credibility.”

Clearly, social and client reviews can be a great tool to boost conversions. And it isn’t just for leads.  Reviews are especially important for online course creators as well to establish both trust and credibility of what they’re trying to sell to their audience.

take social reviews to improve CRO

Source: OneHourProfessor.com

However, there are different ways to collect social reviews. First and foremost, use Google Analytics to check and focus on getting reviews on the platforms that are getting the most traffic.

If you are using the Facebook channel, ensure to activate the Review Tab and make it visible. 

To do that, go to ‘Page Settings’ and scroll down to the ‘Templates and Tabs’ option. 

Find the Reviews tab and turn it on.

Source: Facebook

Once you do that, whenever your customers review your product or service, the ratings will appear on Google searches. 

Most importantly, make sure to respond to all the reviews for better customer experience and to receive even more reviews.  

Plus, don’t hesitate to ask for reviews one-on-one. 

Other tactics you can try are using an email marketing service to ask newsletter subscribers for feedback, offering incentives, placing CTAs on your site asking for reviews, and promoting the reviews you already have. 

Also, don’t delete the negative reviews. It shows that you are transparent. Instead, use negative reviews to your advantage by addressing the issues and apologizing for the poor user experience.

3. Create user-generated content

There’s no doubt that the content that comes directly from users in your niche market has immense ability to drive sales. In a Stackla study, 80% of people said that user-generated content has a huge impact on their purchasing decisions.

Plus, your consumers are 2.4 times more likely to see your content as authentic if it is user-generated as compared to content generated by your business.

user generated content (UGC) helps improve CRO

Source: Stackla

This means that user-generated content also succeeds in building customer trust and establishing your brand as a leader in the field. 

Running a hashtag contest on Instagram, asking intriguing questions by creating polls and quizzes are also great ways to create user-generated content.

For instance, an animal pet supplies retailer in the USA generated over 1,500 entries in 25 days by holding a hashtag contest.

Petco Instagram example

Source: Petco Instagram

It’s quite apparent that user-generated content is an excellent way of generating traction and boosting conversion rates. 

Also, share your user-generated content on Instagram stories since they are designed to drive purchases. The combo of the immediacy of Stories and the staying power of Highlights will let you create a permanent album. This way, potential buyers can keep viewing the user-generated posts until they make a decision to head to your website to make a purchase. 

You can also use Facebook to post engaging videos with the possibility of going viral.

4. Offer superior customer support

Companies are not only competing with prices and products but customer support and building relationships as well. 

You could use communication platforms like Ringblaze and other Vonage alternatives that can help with offering a competitive customer experience. 

But these days, customers are not only willing to do business with companies that offer great customer support but are also willing to pay more. 

In fact, 69% of American customers claim they would spend more money with companies that provide better customer service.

With the presence of social media, offering great customer support has never been easier. 

When you offer customer support on social channels, you can be present wherever your customers are. You just have to make it a point to answer all the queries that your customers post on social media as quickly as possible. 

And trust me, your customers do want a quick response. 

Look. 42% of consumers expect a reply from a brand on social media within 60 minutes, and well over half of consumers are less likely to buy from a brand that leaves questions on social media unanswered. 

You don’t want that to be the case with your brand!

Thus, whenever any issues crop up and users are dissatisfied with your service or product, they might leave negative feedback. Ensure to act on them and resolve the issue as fast as possible.

Moreover, you will have to know when to take an issue offline. There are instances when you might require personal data from the customer, or you will need to answer a series of questions. In such cases, it’s a better idea to move the conversation offline.

5. Optimize the landing page experience

It is known that mobile conversion rates are lower than desktop. You get more traffic from mobile, but it lags behind the desktop when it comes to conversions. 

There are different reasons for this. 

In addition to having more options to design a more attractive page layout on a desktop, it’s easier to navigate a site and view images on a bigger screen. Also, consumers are more likely to purchase on the desktop when the process is less complicated. 

In this case, you can use CRO to improve the landing page experience for the target audience coming from social media. 

A company found out that their lead rate started boosted by 19% after they designed a site explicitly for mobile visitors coming from a social media site.

So consider designing a landing page specifically for mobile visitors coming from social media sites. It will definitely help boost engagement. 

6. Create a FOMO

If statistics are anything to go by, over half of social media users suffer from FOMO (Fear of Missing Out).

create a FOMO to increase CRO

Source: Skyword

You can use this phenomenon to your advantage by deliberately creating FOMO and driving sales. 

For instance, you can add an element of social proof to your regular product image for a Facebook ad to drive common-phenomenon-versions. Even if your audiences don’t know you, seeing a celebrity endorsement or a review from real users will pique their curiosity which may generate shares and leads.

Another trick to make your content go viral is to create a sense of urgency by putting a time limit on the product or service you’re trying to sell. 

It will make people excited to buy your product, and they wouldn’t want to miss out on the opportunity. You can use terms like “Only 24 hours left!” or “Offer ends tonight!”

Here’s an example by an Amazon seller:

Amazon example

 

Source: Amazon

Ecommerce giant Amazon uses their Deal of the Day and countdown timer trick to influence customers to take action right away.

Wrapping up

In this digital age, where people mostly spend their time online on social networking sites, it will benefit your business immensely to leverage the power of integrated CRO and social media. 

As every marketing campaign starts by creating awareness, using social media channels to build brand awareness, and implementing social media strategies like getting social reviews, UGC, optimizing the landing page experience, improving customer support, and creating FOMO. 

If implemented correctly, CRO and social media integration will lead to better conversions and increased sales. 

The post Harness the power of integrated CRO and social media appeared first on Search Engine Watch.

Search Engine Watch


Thinking Simply About Ad Campaign Design

November 24, 2020 No Comments

One strategists looks to industrial designer Dieter Rams and his 10 principles of good design and applies 4 principles to PPC campaign builds.

Read more at PPCHero.com
PPC Hero


Five quick SEO wins to give your website a boost in search

November 24, 2020 No Comments

30-second summary:

  • There are SEO tactics you can apply even without significant expertise.
  • These tactics even the playing field a bit for those who can’t hire a huge team or outsource to an agency.
  • Paying attention to things like images and hosting can give your site a boost.
  • There are simple link building tools that are free and easy to use.
  • Applying these tactics will help you get in the SEO game and give your website a boost in search.

SEO is not easy. In fact, there are around 200 factors that go into determining where your website appears in search results. As such, optimizing your site for search can be a daunting task. Companies hire full teams of SEO experts or outsource the work to agencies to handle the huge workload that can come with executing an effective SEO strategy. Many companies, like yours perhaps, don’t have the resources to do this, however. Fortunately, there are a number of quick wins you can take advantage of to give your website a boost in search.

Try these five tactics to gain some quick SEO wins for your website.

1. Optimize images and visuals

The images and visual elements you place on your site, in articles, on pages, and all around, can be hugely valuable in giving an easy boost to your search rankings.

One example I like to point to is this image on the SE Healthcare website.

Give your website a boost in search - Optimize images and visuals

Image: SE Healthcare infographic ranking in image searches – Source

In working with SE Healthcare on the company’s SEO strategy for a new product launch, we were targeting keywords around the core of physician burnout. Over time, we noticed that this image actually started ranking. It started showing up for tons of searches for “physician burnout solutions” as a result. And those searches went straight to this image in an image search on Google.

Clicks on this result ended up with shares of our infographic appearing on social media as well as a serious lift in our search results for related searches. And we ultimately found that inquiries about related product lines began to rise as well.

So, make sure you’re doing the following to use images to give an easy boost to your search results.

Add visual elements throughout your site

First, adding images, infographics and other visual elements to your site just creates a better experience for users. Any time you can substitute a visual element to explain a concept rather than adding a thousand words of unnecessary text, it can go a long way in connecting with visitors.

Obviously, don’t eliminate text altogether or your SEO will suffer. But, be sure you add images in articles to enhance the articles. Add graphics to explain product features. Add high-quality images of your products. The list goes on, but you get the point. Images add tons of value to your site, and they can also help you rank in search. Google and other search engines love images.

Where to add images

To give you an idea of where you can place images to optimize your site, try the following:

Representative icons – Add representative icons above products and other elements to pull your visitors’ attention.

give your website a boost in search - Where to add images

Image: Icons to represent services – Source

Infographics – Drop infographics into articles and other pages to visually explain concepts and add more value to keep readers on the page and scrolling.

give your website a boost in search - Demo videos

Image: Example of an infographic to add value – Source

Demo Videos – These can really boost your ability to highlight your products by showing rather than telling.

give your website a boost in search with demo videos

Image: Demo video example – Source

Visual Coupon Codes – This is a great way to highlight discounts and entice shoppers on your site to make a purchase. Works great for ecommerce businesses.

Add coupons as a visual element

Image: Visual discount codes – Source

Thumbnail Images – Make sure to add thumbnail images for your posts. These will show up as shown below.

Use thumbnail images

Image: Example of using thumbnail images with posts – Source

Images in Blogs – Placing images through your blog is hugely important. You can use a header image as well as images throughout the post to illustrate important points.

Image: Example of adding a supporting image that expands on the info provided in the text within a blog post – Source

These are just a few ideas of how you can leverage visuals throughout your website to enhance the user experience and give your website a boost in search.

Incorporate videos

Embedding a YouTube video into your articles or your pages can really help boost stats like time on page and lower stats like bounce rate. When these stats head in a positive direction, Google will take notice.

Google loves sites that keep visitors’ attention and keep them on site. A video embedded in the middle of an article can add a minute or more to the time someone spends on your page. And the best part, you don’t even have to create the video.

For example, you could write an article about making Fall décor from egg cartons. Conduct a search on YouTube and find an example of someone doing this, and then embed it in the middle of the article. Not only will visitors read your copy, but they will likely also stop and watch the video, thus keeping them engaged longer.

Insert alt tags

Google is getting better at reading images and determining what they are showing, but the technology still has a way to go. To make sure Google understands the images on your website, you need to place alt tags in each one image upload describing the image. This helps Google determine what the image is showing and whether it relates to a specific search.

Images are super important for helping your site’s SEO performance, so be sure to follow the tips above to benefit.

2. Enhance website security

When you think of cyberattacks, what’s the first thing that comes to mind? Whatever answer popped into your head, I bet it didn’t have anything to do with SEO. Many site owners fail to realize the negative impact a cyberattack can have on your site’s search rankings.

Google, however, is paying attention to a variety of reasons. If your website is lacking in security, and Google takes notice, your site could be in serious trouble.

How Google treats cyber attacks

If Google crawls your website and finds it has been hacked, the search engine giant could actually blacklist your website. When this happens, site visitors will see a notice saying something like “This site may have been hacked.” It goes without saying that visitors seeing that notice will likely navigate away from your website and look for answers and solutions elsewhere.

People see this warning and instantly click away, which can seriously damage your site’s stats. Google will undoubtedly take notice, and your site could be demoted. You may not even notice anything until you see a huge drop in traffic or a major rise in your bounce rate and decide to investigate. By that point, the damage will be done, and you’ll be forced to spend tons of time making things right.

There are a number of types of attacks that can hurt your site. Let’s take a look at a couple types of cyberattacks that can have a seriously negative impact on your search rankings.

DDoS attack

DDoS stands for Distributed Denial of Service. This type of attack is becoming more and more prevalent. The cybercriminal will send massive amounts of bot-related traffic to your site, which can cause significant downtime.

This significant downtime can cause your search rankings to drop. Even 15-minutes of downtime can be a negative signal to Google, so just imagine what a whole week could do. For this reason, you need to take steps to avoid a DDoS attack in order to prevent a drop in search rankings.

Bad bots

This involves bad bots crawling your site and scraping content or stealing data. Obviously, you want to avoid an instance of data theft. Just think of all the major headlines that have been made in recent years from companies being hacked and customer data being stolen. A lesser-known bad bot is the content scraper. These bots essentially scrape your content and place it elsewhere. This compromises your site’s originality and uniqueness and can lead to your search rankings dropping.

These are just a couple of the types of hacks that can hurt your SEO. There are plenty more to be aware of, so you’ll want to do your homework and make sure your site is prepared.

How to protect your site

Fortunately, there are a number of proactive steps you can take to protect your site to avoid this negative impact on your SEO. Here are a few things you should be doing:

  • Make sure you have HTTPS setup
  • Install a strong firewall
  • Conduct regular testing to uncover potential vulnerabilities
  • Use multi-factor authentication for your website logins and even for email
  • Install a security plugin
  • Update your website regularly
  • Use secure logins and passwords for your team (and update them regularly)

Doing these things can position you to avoid the negative SEO impact of a cyberattack and help you maintain the search rankings you worked so hard to earn.

3. Speed up the hosting

Multiple studies confirm that faster site speed does indeed result in better search results. There are a ton of factors that go into optimizing the speed on your site, but one simple factor that’s super easy to control is your site’s hosting provider.

Many of the technical things you can do to speed up your site take time and often require an expert. Fast hosting, on the other hand, simply involves making the right choice and then working with the hosting providers to get your site up and optimized.

There are a ton of hosting providers that offer hosting for $ 2.99 a month (give or take), but often those are shared hosting, which can be significantly slower. To really get the most out of your hosting and truly experience an increase in site speed, I recommend looking at the following types of hosting providers.

Managed WordPress hosting

I start with this because 38% of websites are built using WordPress. It’s my preferred platform, and for WordPress users, managed WordPress hosting can really help optimize your site and give a boost to your site’s speed. I use a managed WordPress hosting provider for my own website.

Managed WordPress hosting often comes with a higher level of support, enhanced security, and obviously since I’m bringing it up here, faster page load speed.

The cost can range from $ 50 to upwards of $ 200 per month, which makes this an affordable option for small- to mid-sized businesses.

Dedicated hosting

The name speaks for itself. You won’t be sharing this hosting with anyone. It is 100% dedicated to your organization alone, which gives you a huge boost in speed. Unfortunately, this option also comes with a boost in cost.

That said, if you are seeing 100s of thousands of visitors to your site each month, this option is right for you. And if you’re seeing that level of traffic, and your site is optimized for conversions, you can likely afford it.

This option can cost a few thousand dollars, so if you aren’t quite there yet, it may be something to keep in mind for the future.

As you can see from the graphic below from Section.io, site speed can seriously impact the bounce rate of your website, which is why I stress the importance of the impact your hosting provider can have.

give your website a boost in search - Add infographics

Image: Source

If these options aren’t the right fit for you, there are tons of other options. With shared hosting, for example, you can pay a bit more to get faster speeds. And with Cloud hosting, you get the benefit of lower downtime.

Whatever option you choose, make sure you talk to the hosting provider and ask questions about site speed and how their platform will help you boost the performance in this area. A faster site is an easy way to give a boost to your SEO.

4. Simplified link building

Link building takes a lot of time and effort. You need to conduct research upfront, and then the execution part, including the outreach to website owners, can be quite time intensive.

There are, however, a few methods you can use to grab some easy links and start slowly building up your arsenal of links.

Let’s take a look at two specific ways you can do link building effectively while saving some time and effort.

HARO (Help A Reporter Out)

This is a great resource. Help A Reporter Out, known in the industry as HARO, allows you to connect with journalists who are seeking sources for the content they’re creating.

You sign up for an account, and when you receive emails with a list of inquires each day related to the subject matter you select. For example, if you run a marketing agency, you can sign up for the business and finance emails. If you run a healthcare organization, you can sign up for the healthcare list.

Once you’re signed up, you’ll receive emails each day that list out queries from journalists asking for expert sources like yourself to provide your opinion or advice on particular topics. Those emails will look something like this:

 

HARO exmaple

Image: HARO email example

As you can see in the email, you’ll see a one-liner highlighting the subject of the query. If you see something that stands out (a subject you feel you could answer expertly), you can just scroll down through the email and you’ll see the full query.

The full query will have more details about the publication and what, specifically, the writer is looking for. Only answer queries where you truly feel you are an expert.

Once you find something that’s a fit, submit an email to the writer via the email link in the email you were sent. I recommend formatting it something like this:

By using this format, you’ll have a better chance of getting accepted, and when you get accepted, the writer will typically add a link back to your site from your quote.

If you keep an eye on your HARO emails and try to respond to 1-2 queries each day, you will gradually start to get your answers accepted, thus gaining valuable backlinks, sometimes from super high domain authority sites. I’ve personally grabbed links from sites like Content Marketing Institute (80+ DA) and Forbes (80+ DA), among others.

Directory submissions

This is another easy link building win. All you need is the following information, and then you can start creating accounts for various directory sites.

  • Elevator pitch for your business (aka, brief description)
  • Your website’s URL
  • Physical address and contact information
  • Logo or image to accompany your listing

Some sites will allow you to enter more info, but you need to at least be armed with the basics above.

Start with the general sites like Yelp, Yellow Pages, and of course, Google My Business. Get those sites up, and then dig a bit deeper. Your industry will definitely have industry-specific directory sites, so don’t forget to fill out those as well.

By filling out directory sites, you are gaining links back to your website, but you are also setting up opportunities for your profile on those sites to appear in search when your site itself does not.

These are just a couple of easy ways to start building links. Begin with these tools, and as you start to get on a roll with HARO, and your directory sites are all set up, you can move onto more difficult efforts.

5. Check for broken links

One thing that can hurt your site is having broken links littering your pages. If you post a ton of content, it can be easy for broken links to slip past you.

For example, you link out to external posts to provide supporting information to your blog readers. Over time, the owners of the sites you link to may remove posts, or those pages themselves may become broken.

If you have a ton of broken links throughout your content, this can impact your SEO, and it can create a poor user experience.

Fortunately, there are lots of great tools you can use to check for broken links and then correct them. Here are a few options:

  • SEMRush – This is a paid platform with lots of bells and whistles. There are a ton of great tools included, so if you want to go all-in on SEO, start here.
  • Ahrefs – While Ahrefs has a great paid platform, they also offer a basic broken link checker for free. I highly recommend checking it out.
  • Dead Link Checker – This is another free tool. You just type in your URL and the checker will scan your site and point out any issues with broken links that it finds.

Whatever tool you choose, you’ll want to locate broken links and either update them with links to new, relevant content or unlink them. Doing this can help keep your site clean and give your website a boost in search.

Conclusion

Applying these tactics can help you get a head start on your SEO efforts. While many SEO tactics are very time-intensive and super challenging, these four tactics are a bit easier and can give you some quick wins.

And the best part is that you don’t need to be a seasoned SEO vet to execute these tactics. Anyone can set up a hosting provider, for example. And typically, the hosting provider will move your site over to the new hosting, so all you’ll have to do is provide some login info.

And looking at HARO, connecting with reporters for high-quality publications can be extremely challenging. HARO helps level the playing field and gives you access to reporters in a much easier way.

So, get your team together and figure out the best approach to start applying these tactics. If you stay consistent and focus on the end goal, these tactics can really give your website a boost in search.

Anthony is the Founder of AnthonyGaenzle.com a marketing and business blog. He also serves as the Head of Marketing and Business Development at Granite Creative Group, a full-service marketing firm. He is a storyteller, strategist, and eternal student of marketing and business strategy.

The post Five quick SEO wins to give your website a boost in search appeared first on Search Engine Watch.

Search Engine Watch


Daily Crunch: Snapchat adds Spotlight

November 24, 2020 No Comments

Snapchat introduces a TikTok-style feed, Amazon Echo Buds add fitness tracking and Vettery acquires Hired. This is your Daily Crunch for November 23, 2020.

The big story: Snapchat adds Spotlight

Snapchat has introduced a dedicated feed where users can watch short, entertaining videos — pretty similar to TikTok. This comes after the app also added TikTok-like music features last month.

Starting today, users will be able to send their Snaps to the new Spotlight feed. Viewers will be able to send direct messages to creators with public profiles (Spotlight will also include anonymous content from private accounts), but there will be no public commentary on these videos.

To encourage creators to post to Spotlight, Snapchat says it will be distributing more than $ 1 million every day who create the top videos on Spotlight.

The tech giants

Amazon’s Echo Buds get new fitness tracking features — Say “Alexa, start my workout” with the buds in, and they’ll begin logging steps, calories, distance, pace and duration of runs.

Uber refused permission to dismiss 11 staff at its EMEA HQ —The Dutch Employee Insurance Agency has refused to give Uber permission to dismiss 11 people at the company’s EMEA headquarters.

Facebook launches ‘Drives,’ a US-only feature for collecting food, clothing and other necessities for people in need — The feature is being made available through Facebook’s existing Community Help hub.

Startups, funding and venture capital

Relativity Space raises $ 500M as it sets sights on the industrialization of Mars — LA-based rocket startup Relativity had a big 2020, completing work on a new 120,000-square-foot manufacturing facility in Long Beach.

Resilience raises over $ 800M to transform pharmaceutical manufacturing in response to COVID-19 — The company will invest heavily in developing new manufacturing technologies across cell and gene therapies, viral vectors, vaccines and proteins.

Video mentoring platform Superpeer raises $ 8M and launches paid channels — The Superpeer platform allows experts to promote, schedule and charge for one-on-one video calls with anyone who might want to ask for their advice.

Advice and analysis from Extra Crunch

Seven things we just learned about Sequoia’s European expansion plans — Steve O’Hear interviews Luciana Lixandru and Matt Miller about the firm’s plans.

Founders seeking their first check need a fundraising sales funnel — Start digging the well before you’re thirsty.

Will Brazil’s Roaring 20s see the rise of early-stage startups? — In September, homegrown startups raised a record $ 843 million.

(Extra Crunch is our membership program, which aims to democratize information about startups. And until November 30, you can get 25% off an annual membership.)

Everything else

Vettery acquires Hired to create a ‘unified’ job search platform — Vettery CEO Josh Brenner said the two platforms are largely complementary.

Gift Guide: Which next-gen console is the one your kid wants? — This holiday season, the next generation of gamers will be hoping to receive the next generation of gaming consoles.

Original Content podcast: ‘The Crown’ introduces its Princess Diana — The new season focuses on Queen Elizabeth’s relationship with Prime Minister Margaret Thatcher, and on Prince Charles’ troubled marriage to Diana, Princess of Wales.

The Daily Crunch is TechCrunch’s roundup of our biggest and most important stories. If you’d like to get this delivered to your inbox every day at around 3pm Pacific, you can subscribe here.

Mobile – TechCrunch


Adjusting Featured Snippet Answers by Context

November 23, 2020 No Comments

How Are Featured Snippet Answers Decided Upon?

I recently wrote about Featured Snippet Answer Scores Ranking Signals. In that post, I described how Google was likely using query dependent and query independent ranking signals to create answer scores for queries that were looking like they wanted answers.

One of the inventors of that patent from that post was Steven Baker. I looked at other patents that he had written, and noticed that one of those was about context as part of query independent ranking signals for answers.

Remembering that patent about question-answering and context, I felt it was worth reviewing that patent and writing about it.

This patent is about processing question queries that want textual answers and how those answers may be decided upon.

it is a complicated patent, and at one point the description behind it seems to get a bit murky, but I wrote about when that happened in the patent, and I think the other details provide a lot of insight into how Google is scoring featured snippet answers. There is an additional related patent that I will be following up with after this post, and I will link to it from here as well.

This patent starts by telling us that a search system can identify resources in response to queries submitted by users and provide information about the resources in a manner that is useful to the users.

How Context Scoring Adjustments for Featured Snippet Answers Works

Users of search systems are often searching for an answer to a specific question, rather than a listing of resources, like in this drawing from the patent, showing featured snippet answers:

featured snippet answers

For example, users may want to know what the weather is in a particular location, a current quote for a stock, the capital of a state, etc.

When queries that are in the form of a question are received, some search engines may perform specialized search operations in response to the question format of the query.

For example, some search engines may provide information responsive to such queries in the form of an “answer,” such as information provided in the form of a “one box” to a question, which is often a featured snippet answer.

Some question queries are better served by explanatory answers, which are also referred to as “long answers” or “answer passages.”

For example, for the question query [why is the sky blue], an answer explaining light as waves is helpful.

featured snippet answers - why is the sky blue

Such answer passages can be selected from resources that include text, such as paragraphs, that are relevant to the question and the answer.

Sections of the text are scored, and the section with the best score is selected as an answer.

In general, the patent tells us about one aspect of what it covers in the following process:

  • Receiving a query that is a question query seeking an answer response
  • Receiving candidate answer passages, each passage made of text selected from a text section subordinate to a heading on a resource, with a corresponding answer score
  • Determining a hierarchy of headings on a page, with two or more heading levels hierarchically arranged in parent-child relationships, where each heading level has one or more headings, a subheading of a respective heading is a child heading in a parent-child relationship and the respective heading is a parent heading in that relationship, and the heading hierarchy includes a root level corresponding to a root heading (for each candidate answer passage)
  • Determining a heading vector describing a path in the hierarchy of headings from the root heading to the respective heading to which the candidate answer passage is subordinate, determining a context score based, at least in part, on the heading vector, adjusting the answer score of the candidate answer passage at least in part by the context score to form an adjusted answer score
  • Selecting an answer passage from the candidate answer passages based on the adjusted answer scores

Advantages of the process in the patent

  1. Long query answers can be selected, based partially on context signals indicating answers relevant to a question
  2. The context signals may be, in part, query-independent (i.e., scored independently of their relatedness to terms of the query
  3. This part of the scoring process considers the context of the document (“resource”) in which the answer text is located, accounting for relevancy signals that may not otherwise be accounted for during query-dependent scoring
  4. Following this approach, long answers that are more likely to satisfy a searcher’s informational need are more likely to appear as answers

This patent can be found at:

Context scoring adjustments for answer passages
Inventors: Nitin Gupta, Srinivasan Venkatachary , Lingkun Chu, and Steven D. Baker
US Patent: 9,959,315
Granted: May 1, 2018
Appl. No.: 14/169,960
Filed: January 31, 2014

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for context scoring adjustments for candidate answer passages.

In one aspect, a method includes scoring candidate answer passages. For each candidate answer passage, the system determines a heading vector that describes a path in the heading hierarchy from the root heading to the respective heading to which the candidate answer passage is subordinate; determines a context score based, at least in part, on the heading vector; and adjusts answer score of the candidate answer passage at least in part by the context score to form an adjusted answer score.

The system then selects an answer passage from the candidate answer passages based on the adjusted answer scores.

Using Context Scores to Adjust Answer Scores for Featured Snippets

A drawing from the patent shows different hierarchical headings that may be used to determine the context of answer passages that may be used to adjust answer scores for featured snippets:

Hierarchical headings for featured snippets

I discuss these headings and their hierarchy below. Note that the headings include the Page title as a heading (About the Moon), and the headings within heading elements on the page as well. And those headings give those answers context.

This context scoring process starts with receiving candidate answer passages and a score for each of the passages.

Those candidate answer passages and their respective scores are provided to a search engine that receives a query determined to be a question.

Each of those candidate answer passages is text selected from a text section under a particular heading from a specific resource (page) that has a certain answer score.

For each resource where a candidate answer passage has been selected, a context scoring process determines a heading hierarchy in the resource.

A heading is text or other data corresponding to a particular passage in the resource.

As an example, a heading can be text summarizing a section of text that immediately follows the heading (the heading describes what the text is about that follows it, or is contained within it.)

Headings may be indicated, for example, by specific formatting data, such as heading elements using HTML.

This next section from the patent reminded me of an observation that Cindy Krum of Mobile Moxie has about named anchors on a page, and how Google might index those to answer a question, to lead to an answer or a featured snippet. She wrote about those in What the Heck are Fraggles?

A heading could also be anchor text for an internal link (within the same page) that links to an anchor and corresponding text at some other position on the page.

A heading hierarchy could have two or more heading levels that are hierarchically arranged in parent-child relationships.

The first level, or the root heading, could be the title of the resource.

Each of the heading levels may have one or more headings, and a subheading of a respective heading is a child heading and the respective heading is a parent heading in the parent-child relationship.

For each candidate passage, a context scoring process may determine a context score based, at least in part, on the relationship between the root heading and the respective heading to which the candidate answer passage is subordinate.

The context scoring process could be used to determine the context score and determines a heading vector that describes a path in the heading hierarchy from the root heading to the respective heading.

The context score could be based, at least in part, on the heading vector.

The context scoring process can then adjust the answer score of the candidate answer passage at least in part by the context score to form an adjusted answer score.

The context scoring process can then select an answer passage from the candidate answer passages based on adjusted answer scores.

This flowchart from the patent shows the context scoring adjustment process:

context scoring adjustment flowchart

Identifying Question Queries And Answer Passages

I’ve written about understanding the context of answer passages. The patent tells us more about question queries and answer passages worth going over in more detail.

Some queries are in the form of a question or an implicit question.

For example, the query [distance of the earth from the moon] is in the form of an implicit question “What is the distance of the earth from the moon?”

An implicit question - the distance from the earth to the moon

Likewise, a question may be specific, as in the query [How far away is the moon].

The search engine includes a query question processor that uses processes that determine if a query is a query question (implicit or specific) and if it is, whether there are answers that are responsive to the question.

The query question processor can use several different algorithms to determine whether a query is a question and whether there are particular answers responsive to the question.

For example, it may use to determine question queries and answers:

  • Language models
  • Machine learned processes
  • Knowledge graphs
  • Grammars
  • Combinations of those

The query question processor may choose candidate answer passages in addition to or instead of answer facts. For example, for the query [how far away is the moon], an answer fact is 238,900 miles. And the search engine may just show that factual information since that is the average distance of the Earth from the moon.

But, the query question processor may choose to identify passages that are to be very relevant to the question query.

These passages are called candidate answer passages.

The answer passages are scored, and one passage is selected based on these scores and provided in response to the query.

An answer passage may be scored, and that score may be adjusted based on a context, which is the point behind this patent.

Often Google will identify several candidate answer passages that could be used as featured snippet answers.

Google may look at the information on the pages where those answers come from to better understand the context of the answers such as the title of the page, and the headings about the content that the answer was found within.

Contextual Scoring Adjustments for Featured Snippet Answers

The query question processor sends to a context scoring processor some candidate answer passages, information about the resources from which each answer passages was from, and a score for each of the featured snippet answers.

The scores of the candidate answer passages could be based on the following considerations:

  • Matching a query term to the text of the candidate answer passage
  • Matching answer terms to the text of the candidate answer passages
  • The quality of the underlying resource from which the candidate answer passage was selected

I recently wrote about featured snippet answer scores, and how a combination of query dependent and query independent scoring signals might be used to generate answer scores for answer passages.

The patent tells us that the query question processor may also take into account other factors when scoring candidate answer passages.

Candidate answer passages can be selected from the text of a particular section of the resource. And the query question processor could choose more than one candidate answer passage from a text section.

We are given the following examples of different answer passages from the same page

(These example answer passages are referred to in a few places in the remainder of the post.)

  • (1) It takes about 27 days (27 days, 7 hours, 43 minutes, and 11.6 seconds) for the Moon to orbit the Earth at its orbital distance
  • (2) Why is the distance changing? The moon’s distance from Earth varies because the moon travels in a slightly elliptical orbit. Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles
  • (3) The moon’s distance from Earth varies because the moon travels in a slightly elliptical orbit. Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles

Each of those answers could be good ones for Google to use. We are told that:

More than three candidate answers can be selected from the resource, and more than one resource can be processed for candidate answers.

How would Google choose between those three possible answers?

Google might decide based on the number of sentences and a selection of up to a maximum number of characters.

The patent tells us this about choosing between those answers:

Each candidate answer has a corresponding score. For this example, assume that candidate answer passage (2) has the highest score, followed by candidate answer passage (3), and then by candidate answer passage (1). Thus, without the context scoring processor, candidate answer passage (2) would have been provided in the answer box of FIG. 2. However, the context scoring processor takes into account the context of the answer passages and adjusts the scores provided by the query question processor.

So, we see that what might be chosen based on featured snippet answer scores could be adjusted based on the context of that answer from the page that it appears on.

Contextually Scoring Featured Snippet Answers

This process starts which begins with a query determined to be a question query seeking an answer response.

This process next receives candidate answer passages, each candidate answer passage chosen from the text of a resource.

Each of the candidate answer passages are text chosen from a text section that is subordinate to a respective heading (under a heading) in the resource and has a corresponding answer score.

For example, the query question processor provides the candidate answer passages, and their corresponding scores, to the context scoring processor.

A Heading Hierarchy to Determine Context

This process then determines a heading hierarchy from the resource.

The heading hierarchy would have two or more heading levels hierarchically arranged in parent-child relationships (Such as a page title, and an HTML heading element.)

Each heading level has one or more headings.

A subheading of a respective heading is a child heading (an (h2) heading might be a subheading of a (title)) in the parent-child relationship and the respective heading is a parent heading in the relationship.

The heading hierarchy includes a root level corresponding to a root heading.

The context scoring processor can process heading tags in a DOM tree to determine a heading hierarchy.

hierarchical headings for featured snippets

For example, concerning the drawing about the distance to the moon just above, the heading hierarchy for the resource may be:

The ROOT Heading (title) is: About The Moon (310)

The main heading (H1) on the page

H1: The Moon’s Orbit (330)

A secondary heading (h2) on the page:

H2: How long does it take for the Moon to orbit Earth? (334)

Another secondary heading (h2) on the page is:

H2: The distance from the Earth to the Moon (338)

Another Main heading (h1) on the page

H1: The Moon (360)

Another secondary Heading (h2) on the page:

H2: Age of the Moon (364)

Another secondary heading (h2) on the page:

H2: Life on the Moon (368)

Here is how the patent describes this heading hierarchy:

In this heading hierarchy, The title is the root heading at the root level; headings 330 and 360 are child headings of the heading, and are at a first level below the root level; headings 334 and 338 are child headings of the heading 330, and are at a second level that is one level below the first level, and two levels below the root level; and headings 364 and 368 are child headings of the heading 360 and are at a second level that is one level below the first level, and two levels below the root level.

The process from the patent determines a context score based, at least in part, on the relationship between the root heading and the respective heading to which the candidate answer passage is subordinate.

This score may be is based on a heading vector.

The patent says that the process, for each of the candidate answer passages, determines a heading vector that describes a path in the heading hierarchy from the root heading to the respective heading.

The heading vector would include the text of the headings for the candidate answer passage.

For the example candidate answer passages (1)-(3) above about how long it takes the moon to orbit the earch, the respectively corresponding heading vectors V1, V2 and V3 are:

  • V1=<[Root: About The Moon], [H1: The Moon's Orbit], [H2: How long does it take for the Moon to orbit the Earth?]>
  • V2=<[Root: About The Moon], [H1: The Moon's Orbit], [H2: The distance from the Earth to the Moon]>
  • V3=<[Root: About The Moon], [H1: The Moon's Orbit], [H2: The distance from the Earth to the Moon]>

We are also told that because candidate answer passages (2) and (3) are selected from the same text section 340, their respective heading vectors V2 and V3 are the same (they are both in the content under the same (H2) heading.)

The process of adjusting a score, for each answer passage, uses a context score based, at least in part, on the heading vector (410).

That context score can be a single score used to scale the candidate answer passage score or can be a series of discrete scores/boosts that can be used to adjust the score of the candidate answer passage.

Where things Get Murky in This Patent

There do seem to be several related patents involving featured snippet answers, and this one which targets learning more about answers from their context based on where they fit in a heading hierarchy makes sense.

But, I’m confused by how the patent tells us that one answer based on the context would be adjusted over another one.

The first issue I have is that the answers they are comparing in the same contextual area have some overlap. Here those two are:

  • (2) Why is the distance changing? The moon’s distance from Earth varies because the moon travels in a slightly elliptical orbit. Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles
  • (3) The moon’s distance from Earth varies because the moon travels in a slightly elliptical orbit. Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles

Note that the second answer and the third answer both include the same line: “Thus, the moon’s distance from the Earth varies from 225,700 miles to 252,000 miles.” I find myself a little surprised that the second answer includes a couple of sentences that aren’t in the third answer, and skips a couple of lines from the third answer, and then includes the last sentence, which answers the question.

Since they both appear in the same heading and subheading section of the page they are from, it is difficult to imagine that there is a different adjustment based on context. But, the patent tells us differently:

The candidate answer score with the highest adjusted answer score (based on context from the headings) is selected, and the answer passage.

Recall that in the example above, the candidate answer passage (2) had the highest score, followed by candidate answer passage (3), and then by candidate answer passage (1).

However, after adjustments, candidate answer passage (3) has the highest score, followed by candidate answer passage (2), and then-candidate answer passage (1).

Accordingly, candidate answer passage (3) is selected and provided as the answer passage of FIG. 2.

Boosting Scores Based on Passage Coverage Ratio

A query question processor may limit the candidate answers to a maximum length.

The context scoring processor determines a coverage ratio which is a measure indicative of the coverage of the candidate answer passage from the text from which it was selected.

The patent describes alternative question answers:

Alternatively, the text block may include text sections subordinate to respective headings that include a first heading for which the text section from which the candidate answer passage was selected is subordinate, and sibling headings that have an immediate parent heading in common with the first heading. For example, for the candidate answer passage, the text block may include all the text in the portion 380 of the hierarchy; or may include only the text of the sections, of some other portion of text within the portion of the hierarchy. A similar block may be used for the portion of the hierarchy for candidate answer passages selected from that portion.

A small coverage ratio may indicate a candidate answer passage is incomplete. A high coverage ratio may indicate the candidate answer passage captures more of the content of the text passage from which it was selected. A candidate answer passage may receive a context adjustment, depending on this coverage ratio.

A passage coverage ratio is a ratio of the total number of characters in the candidate answer passage to the ratio of the total number of characters in the passage from which the candidate answer passage was selected.

The passage cover ratio could also be a ratio of the total number of sentences (or words) in the candidate answer passage to the ratio of the total number of sentences (or words) in the passage from which the candidate answer passage was selected.

We are told that other ratios can also be used.

From the three example candidate answer passages about the distance to the moon above (1)-(3) above, passage (1) has the highest ratio, passage (2) has the second-highest, and passage (3) has the lowest.

This process determines whether the coverage ratio is less than a threshold value. That threshold value can be, for example, 0.3, 0.35 or 0.4, or some other fraction. In our “distance to the moon” example, each coverage passage ratio meets or exceeds the threshold value.

If the coverage ratio is less than a threshold value, then the process would select a first answer boost factor. The first answer boost factor might be proportional to the coverage ratio according to a first relation, or maybe a fixed value, or maybe a non-boosting value (e.g., 1.0.)

But if the coverage ratio is not less than the threshold value, the process may select a second answer boost factor. The second answer boost factor may be proportional to the coverage ratio according to a second relation, or maybe fixed value, or maybe a value greater than the non-boosting value (e.g., 1.1.)

Scoring Based on Other Features

The context scoring process can also check for the presence of features in addition to those described above.

Three example features for contextually scoring an answer passage can be based on the additional features of the distinctive text, a preceding question, and a list format.

Distinctive text

Distinctive text is the text that may stand out because it is formatted differently than other text, like using bolding.

A Preceeding Question

A preceding question is a question in the text that precedes the candidate answer question.

The search engine may process various amounts of text to detect for the question.

Only the passage from which the candidate answer passage is extracted is detected.

A text window that can include header text and other text from other sections may be checked.

A boost score that is inversely proportional to the text distance from a question to the candidate answer passage is calculated, and the check is terminated at the occurrence of a first question.

That text distance may be measured in characters, words, or sentences, or by some other metric.

If the question is anchor text for a section of text and there is intervening text, such as in the case of a navigation list, then the question is determined to only precede the text passage to which it links, not precede intervening text.

In the drawing above about the moon, there are two questions in the resource: “How long does it take for the Moon to orbit Earth?” and “Why is the distance changing?”

The first question–“How long does it take for the Moon to orbit Earth?”– precedes the first candidate answer passage by a text distance of zero sentences, and it precedes the second candidate answer passage by a text distance of five sentences.

And the second question–“Why is the distance changing?”– precedes the third candidate answer by zero sentences.

If a preceding question is detected, then the process selects a question boost factor.

This boost factor may be proportional to the text distance, whether the text is in a text passage subordinate to a header or whether the question is a header, and, if the question is in a header, whether the candidate answer passage is subordinate to the header.

Considering these factors, the third candidate answer passage receives the highest boost factor, the first candidate answer receives the second-highest boost factor, and the second candidate answer receives the smallest boost factor.

Conversely, if the preceding text is not detected, or after the question boost factor is detected, then the process detects for the presence of a list.

The Presence of a List

A list is an indication of several steps usually instructive or informative. The detection of a list may be subject to the query question being a step modal query.

A step modal query is a query where a list-based answer is likely to a good answer. Examples of step model queries are queries like:

  • [How to . . . ]
  • [How do I . . . ]
  • [How to install a door knob]
  • [How do I change a tire]

The context scoring process may detect lists formed with:

  • HTML tags
  • Micro formats
  • Semantic meaning
  • Consecutive headings at the same level with the same or similar phrases (e.g., Step 1, Step 2; or First; Second; Third; etc.)

The context scoring process may also score a list for quality.

It would look at things such as:

  • A list in the center of a page, which does not include multiple links to other pages (indicative of reference lists)
  • HREF link text that does not occupy a large portion of the text of the list will be of higher quality than a list at the side of a page, and which does include multiple links to other pages (which are indicative of reference lists), and/are has HREF link text that does occupy a large portion of the text of the list

If a list is detected, then the process selects a list boost factor.

That list boost factor may be fixed or may be proportional to the quality score of the list.

If a list is not detected, or after the list boost factor is selected, the process ends.

In some implementations, the list boost factor may also be dependent on other feature scores.

If other features, such as coverage ratio, distinctive text, etc., have relatively high scores, then the list boot factor may be increased.

The patent tells us that this is because “the combination of these scores in the presence of a list is a strong signal of a high-quality answer passage.”

Adjustment of Featured Snippet Answers Scores

Answer scores for candidate answer passages are adjusted by scoring components based on heading vectors, passage coverage ratio, and other features described above.

The scoring process can select the largest boost value from those determined above or can select a combination of the boost values.

Once the answer scores are adjusted, the candidate answer passage with the highest adjusted answer score is selected as the featured snippet answer and is displayed to a searcher.

More to Come

I will be reviewing the first patent in this series of patents about candidate answer scores because it does have some additional elements to it that haven’t been covered in this post, and the post about query dependent/independent ranking signals for answer scores. If you have been paying attention to how Google has been answering queries that appear to be seeking answers, you have likely seen those improving in many cases. Some answers have been really bad though. It will be nice to have as complete an idea as we can of how Google decides what might be a good answer to a query, based on information available to them on the Web.

Added October 14, 2020 – I have written about another Google patent on Answer Scores, and it’s worth reading about all of the patents on this topic. The new post is at Weighted Answer Terms for Scoring Answer Passages, and is about the patent Weighted answer terms for scoring answer passages.

It is about identifying questions in resources, and answers for those questions, and describes using term weights as a way to score answer passages (along with the scoring approaches identified in the other related patents, including this one.)

Added October 15, 2020 – I have written a few other posts about answer passages that are worth reading if you are interested in how Google finds questions on pages and answers to those, and scores answer passages to determine which ones to show as featured snippets. I’ve linked to some of those in the body of this post, but here is another one of those posts:

Added October 22, 2020, I have written up a description of details from about how structured and unstructured data has been selected for answer passages based on specific criteria in the patent on Scoring Answer passages in the post Selecting Candidate Answer Passages.


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