Monthly Archives: July 2020
For two months, the people of Hong Kong waited in suspense after China’s legislature approved a new national security law. The legislation’s details were finally made public yesterday and almost immediately went into effect. As many Hong Kong residents feared, the broadly written new law gives Beijing extensive authority over the Special Administrative Region and has the potential to sharply curtail civil liberties.
In response, the United States began the first measures to end the special status it gives to Hong Kong, with the Commerce and State Departments suspending export license exceptions for sensitive U.S. technology and blocking the export of defense equipment.
Much remains uncertain. Hong Kong had also previously enjoyed many freedoms that do not exist in mainland China, under the “one country, two systems” principle put into place after the United Kingdom returned control to China. After announcing the new policies, the U.S. government said further restrictions are being considered. Under special status, Hong Kong had privileges including lower trade tariffs and a separate customs and immigration designation from mainland China, but now the future of those is unclear.
Equally opaque is how the erosion of special status and the new national security law will impact Hong Kong’s startups in the future. In conversations with TechCrunch, investors and founders said they believe the region’s ecosystem is resilient, partly because many companies offer online services — especially financial services — and have already established operations in other markets. But they are also keeping an eye on further developments and preparing for the possibility that key talent will want to relocate to other countries.
- Regardless of your industry, the marketing strategy you are currently executing is completely different from the marketing strategy you had in place just six months ago.
- The situation that has unfolded over the last few months has thrown “business as usual” out of the window.
- Budgets are tight, events are canceled, and your buyers’ needs have dramatically changed in the last few months.
- Credly’s VP of Marketing, Adam Masur shares three of the most critical marketing metrics to measure in these unique circumstances.
When it comes to your marketing efforts, there are specific numbers you should be constantly tracking and working to improve. Yet, regardless of your industry, the marketing strategy you are currently executing is completely different from the marketing strategy you had in place just six months ago.
The situation that has unfolded over the last few months has left marketing teams in every industry at a loss for the best way to move forward. It is no longer “business as usual”. What works today may not work tomorrow, so marketers must be prepared to pivot quickly during this time of uncertainty. And we don’t expect that to change any time soon. Even when the pandemic is over and things start returning to “normal,” everyone is going to have to adapt to what the new “new world of work” looks like.
As you start to navigate a new way of marketing your product or services following the COVID-19 outbreak, you must reevaluate your strategies and develop a new plan of action. Budgets are tight, events are canceled and your buyers’ needs have dramatically changed in the last few months. Given the unique circumstances, here are three of the most critical metrics to measure right now.
Metric one: Cost per acquisition
Familiarizing an audience with your product or service and converting them to a paying customer comes at a price. Even in the best of times, I may argue that cost-per-acquisition (CPA), which measures the aggregate cost to acquire just one paying customer, is the most important metric. When it comes to how you’re spending your precious marketing dollars during this time, your CPA has to be top of mind.
These days, it’s possible that you’re encountering prospects with different risk tolerances, at different stages of product knowledge and purchase intent. It’s a great time to rethink ad copy and realign landing pages with more focused, more compelling, and more relevant content. It’s also a great time to look for the emergence of new keywords that have suddenly become more important in your customers’ minds. The best way to optimize your CPA is by addressing your audiences’ immediate concerns directly, and continuing the dialog until they’re ready to take the next step. Your quality scores will thank you for it.
Marketers have chased vanity marketing metrics like ad clicks from the beginning of time. But, most marketing teams can’t rely on metrics with empty promises. If you haven’t seen any of your numbers moving lately, maybe you aren’t looking hard enough. Maybe it’s bounce rates, session length, pages viewed, or the number or site visits before filling out a form–there’s something to be learned. Now is the time to test your hypotheses to figure out what’s changing in your customers’ worlds, and address these topics directly. You’ll get a better picture of the true health of your business rather than a false sense of success.
Metric two: Social media engagement
It’s always been hard for marketing teams to truly measure social media interactions, but social media is a critical avenue for establishing and developing organic relationships with your audience in today’s digital world. With billions of active users, social media provides modern marketers with more exposure, improved traffic, and increased brand loyalty.
Engagement on social media platforms can present itself in various ways: shares, likes, comments, and reposts are all the digital marketing metrics used to gauge your audience’s level of engagement. By tracking social media engagement, you have a better idea of your content’s reach and if it’s landing in front of the right people.
You can’t just rely on hard numbers. The sentiment, intent, objections, and accolades are all there for you to learn from, but you have to invest the time to dive in beyond a high-level engagement graph. Understanding how your audience is interacting with that content allows you to readjust your message as needed and create valuable interactions that continue to push your brand forward.
Focusing on your social media strategy right now helps your brand maximize limited resources. With tight budgets, authentically engaging in social media can help your team meet your audience where they are, provide valuable information, and generate meaningful relationships.
Metric three: Website traffic
Regardless of what the business landscape looks like, one goal every marketer has is to drive traffic back to their company’s website. While every marketing channel–inbound, outbound, events, social, content–brings in new leads and new prospects, it’s unlikely that anyone becomes a customer without visiting your website.
That’s why it’s not enough to drive traffic to your home page. You want to see that those people are visiting multiple pages, engaging with your content, and finding what they need to make the decision that’s right for them. Only then will they take the step to try, buy, or fill out the form that connects them with your sales team.
While marketers are working with limited resources and under unprecedented circumstances right now, we have to remember that so are our buyers. Marketers have to lean into actionable metrics from their website traffic, including bounce rate, average session duration, and pages per session. Are pages that used to get 100 visits a month, now getting 100 visits a day or vise versa? It could be a sign of your buyers’ shifting needs or priorities.
Spend the effort to get a clear understanding of your buyers’ current situation. Rely on data and analytics, and check your work by engaging and actively listening. Evaluating how these important marketing metrics are faring provides insight into how your overall strategy is doing and helps you allocate resources while still connecting with your audience in a meaningful way.
When it comes to marketing your product or service in the current climate, you have to be proactive. Marketers who are able to pivot, use data and analytics to guide their efforts, and tap into the new needs of their buyers will continue to be successful as we enter the new world of work.
Adam Masur, Vice President of Marketing at Credly, is driven by a passion for optimizing the way marketing teams and technology work together to grow businesses.
The post The three most critical marketing metrics to measure right now appeared first on Search Engine Watch.
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- Brand authority can make a huge difference in whether someone decides to buy from you or not.
- First you have to examine what your current brand recognition is like by seeing how you’re talked about online. This can help you identify opportunity areas.
- Then you can dive in deeper and start researching typical questions your target audience has. Why? So you can answer them.
- Finally, you’ll set out to answer the questions you collected in an authoritative way to start building trust.
Please forgive the fact that I’m tweaking a tired adage, but the message is true: Building your brand authority doesn’t happen overnight.
I was reminded of this fact very recently while scrolling through LinkedIn:
Ongoing marketing efforts are needed to tell an authoritative story and build trust in potential customers. It can always make a difference when someone is deciding between two companies, and it’s even more important with B2B, since those products/services tend to involve a higher cost.
Here’s how you can go about utilizing digital marketing to increase your brand authority.
Note: I’m going to focus on the content itself, but earning backlinks — which is significantly easier to do with high-quality content — is a primary way to indicate to Google that other sites trust you, which signals that you’re more authoritative. Prioritizing your backlink portfolio will dramatically help you in all other authority-building efforts.
Gauge your brand authority level
Don’t assume you already understand how you’re viewed by your audience. Instead, before launching into any marketing strategies, check the data to get a sense of how you’re being perceived.
- Have your branded searches increased or decreased? What search terms are people pairing with your brand?
- How are your customers or leads finding out about your brand? Was it from authoritative interviews or content you put out there or some other way?
- Are you ever mentioned in the media? If you haven’t already, set up Google Alerts for your brand name and any prominent, public-facing employees.
Another interesting consideration is: Who are the current authorities in your space? Are you aware of them all?
The first way to identify this is to type into Google the phrases you wish you ranked for and see who is ranking for those terms. Sometimes it’s the competitors you knew about, but sometimes other sites have climbed up the authority ladder.
Additionally, you can use tools like SparkToro to search your topic area and see where your audience is going for information.
If you search for your vertical, you can then see the most popular publications, podcasts, social channels, and more visited by the audience interested in your vertical.
Then the question becomes, are you on these lists? If not, who is and why? What are they doing well? You can aim to be featured on these different media outlets, as you know they appeal to your target audience.
Identify your audience’s questions
If you answer your audience’s questions, they’ll start to trust you and see you as an authority.
The concept sounds simple, and it is. But the execution is harder. First, how do you find out what their questions are?
Here are a few ways:
- Tools like Answer the Public and BuzzSumo’s Questions will show you what people are asking based on different keywords you enter.
Snapshot of BuzzSumo’s Questions tool
- Keyword research can reveal the types of challenges people are facing. Don’t just look at keyword volume — look at “People also ask”. Get lost for a little while, clicking on various questions and related keywords. (Keywords Everywhere is a cool tool for search volume/competition, as is Keyword Surfer).
- Talk to your sales team about what common questions are coming up. Have you answered these with content? Do they speak to the greater problems your audience faces?
- Brush up on your audience personas. Different segments of your audience may have different problems. See if you’ve been accidentally neglecting a segment.
Once you have a solid list of the questions your audience has, you can work on effectively answering those questions.
Answer the questions with authoritative content
Once you know what you want to write about, how do you make it authoritative?
First of all, your methodology matters. Do your own original research whenever possible. Content backed by data is inherently more trustworthy than content based on opinion. If you’re featuring opinion, make sure it’s someone who can prove their expertise through their past experience.
Secondly, the content has to be created in a way that conveys authority:
- It shouldn’t have any grammar or spelling errors
- If it’s time-sensitive in any way, it needs a date on the article so people know exactly when it was written and thus the content can be put in its proper context
- Sources should all be cited
- The design should be clean and easy to read
- The structure and navigation should be well-thought-out and provide insight into exactly what readers will learn
- All information should be backed up with explanations and facts
- If your piece was written by experts, provide their name and bio
Let’s take a look at some examples. I pulled the top organic text and video results for the query “how to choose a bike.” (I’m thinking about buying a bike, so I’m finding myself using a lot of bike-related examples as of late…)
REI’s article, “How to Choose a Bike,” ranks number one. I use REI examples a lot because I think they have a fantastic content strategy by using their expertise to answer all kinds of questions their customers could have.
But let’s focus specifically on what makes this article seem authoritative.
First, it’s well organized and clearly outlined, even including a table where you can get the top-level information very quickly. Having a well-thought-out structure and design is a visual indication of knowledge and understanding of a topic.
They also have a section at the bottom labeled “Contributing Experts” so you know exactly who put the guide together and what experience they have.
Finally, they responded to all of their comments, providing additional information to the people who had further questions.
Now let’s check out the top video result, which is from 2013, meaning people have found it useful for more than six years. What about it feels authoritative?
For one, look at how he outlines right at the beginning what the video will cover, setting proper expectations and indicating a solid knowledge of the subject.
Additionally, he doesn’t just list the features of the different types; he explains the usefulness of those features to help you make a more informed decision.
There are a few other techniques to display authority, as well. Andy Crestodina recommends including quotes and tips from other thought leaders in your piece. You can also get third-party validation for your content in the form of testimonials, reviews, or asking influencers to share what you created. The point here is to showcase that you associate with experts and that other people trust you.
It’ll take time and effort, but once you’re an authority, every other aspect of your marketing will gain more traction. Consider how to build authority into all of your digital marketing, and you’ll have the potential to amplify your results even further.
Amanda Milligan is the Marketing Director at Fractl, a prominent growth marketing agency that’s worked with Fortune 500 companies and boutique businesses.
The post How to build your brand authority through content marketing appeared first on Search Engine Watch.
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A Well-Formed Query Helps a Search Engine understand User Intent Behind the Query
To start this post, I wanted to include a couple of whitepapers that include authors from Google. The authors of the first paper are the inventors of a patent application that was just published on April 28, 2020, and it is very good seeing a white paper from the inventors of a recent patent published by Google. Both papers are worth reading to get a sense of how Google is trying to rewrite queries into “Well-Formed Natural Language Questions.
August 28, 2018 – Identifying Well-formed Natural Language Questions
The abstract for that paper:
Understanding search queries is a hard problem as it involves dealing with “word salad” text ubiquitously issued by users. However, if a query resembles a well-formed question, a natural language processing pipeline can perform more accurate interpretation, thus reducing downstream compounding errors.
Hence, identifying whether or not a query is well-formed can enhance query understanding. Here, we introduce a new task of identifying a well-formed natural language question. We construct and release a dataset of 25,100 publicly available questions classified into well-formed and non-wellformed categories and report an accuracy of 70.7% on the test set.
We also show that our classifier can be used to improve the performance of neural sequence-to-sequence models for generating questions for reading comprehension.
The paper provides examples of well-formed queries and ill-formed queries:
The abstract for that paper:
We present a large-scale dataset for the task of rewriting an ill-formed natural language question to a well-formed one. Our multi-domain question rewriting (MQR) dataset is constructed from human contributed Stack Exchange question edit histories.
The dataset contains 427,719 question pairs which come from 303 domains. We provide human annotations for a subset of the dataset as a quality estimate. When moving from ill-formed to well-formed questions, the question quality improves by an average of 45 points across three aspects.
We train sequence-to-sequence neural models on the constructed dataset and obtain an improvement of 13.2%in BLEU-4 over baseline methods built from other data resources. We release the MQR dataset to encourage research on the problem of question rewriting.
The patent application I am writing about was filed on January 18, 2019, which puts it around halfway between those two whitepapers, and both of them are recommended to get a good sense of the topic if you are interested in featured snippets, people also ask questions, and queries that Google tries to respond to. The Second Whitepaper refers to the first one, and tells us how it is trying to improve upon it:
Faruqui and Das (2018) introduced the task of identifying well-formed natural language questions. In this paper, we take a step further to investigate methods to rewrite ill-formed questions into well-formed ones without changing their semantics. We create a multi-domain question rewriting dataset (MQR) from human contributed StackExchange question edit histories.
Rewriting Ill-Formed Search Queries into Well-Formed Queries
Interestingly, the patent is also about rewriting search Queries.
It starts by telling us that “Rules-based rewrites of search queries have been utilized in query processing components of search systems.”
Sometimes this happens by removing certain stop-words from queries, such as “the”, “a”, etc.
After Rewriting a Query
Once a query is rewritten, it may be “submitted to the search system and search results returned that are responsive to the rewritten query.”
The patent also tells us about “people also search for X” queries (first patent I have seen them mentioned in.)
We are told that these similar queries are used to recommend additional queries that are related to a submitted query (e.g., “people also search for X”).
These “similar queries to a given query are often determined by navigational clustering.”
As an example, we are told that for the query “funny cat pictures”, a similar query of “funny cat pictures with captions” may be determined because that similar query is frequently submitted by searchers following submission of the query “funny cat pictures”.
Determining if a Query is a Well Formed Query
The patent tells us about a process that can be used to determine if a natural language search query is well-formed and if it is not, to use a trained canonicalization model to create a well-formed variant of that natural language search query.
First, we are given a definition of “Well-formedness” We are told that it is “an indication of how well a word, a phrase, and/or another additional linguistic element (s) conform to the grammar rules of a particular language.”
These are three steps to tell whether something is a well-formed query. It is:
- Grammatically correct
- Does not contain spelling errors
- Asks an explicit question
The first paper from the authors of this patent tells us the following about queries:
The lack of regularity in the structure of queries makes it difficult to train models that can optimally process the query to extract information that can help understand the user intent behind the query.
That translates to the most important takeaway for this post:
A Well-Formed Query is structured in a way that allows a search engine to understand the user intent behind the query
The patent gives us an example:
“What are directions to Hypothetical Café?” is an example of a well-formed version of the natural language query “Hypothetical Café directions”.
How the Classification Model Works
It also tells us that the purpose behind the process in the patent is to determine whether a query is well-formed using a trained classification model and/or a well-formed variant of a query and if that well-formed version can be generated using a trained canonicalization model.
It can create that model by using features of the search query as input to the classification model and deciding whether the search query is well-formed.
Those features of the search query can include, for example:
- Part(s) of speech
- Entities included in the search query
- And/or other linguistic representation(s) of the search query (such as word n-grams, character bag of words, etc.)
And the patent tells us more about the nature of the classification model:
The classification model is a machine learning model, such as a neural network model that contains one or more layers such as one or more feed-forward layers, softmax layer(s), and/or additional neural network layers. For example, the classification model can include several feed-forward layers utilized to generate feed-forward output. The resulting feed-forward output can be applied to softmax layer(s) to generate a measure (e.g., a probability) that indicates whether the search query is well-formed.
A Canonicalization Model May Be Used
If the Classification model determines that the search query is not well-formed, the query is turned over to a trained canonicalization model to generate a well-formed version of the search query.
The search query may have some of its features extracted from the search query, and/or additional input processed using the canonicalization model to generate a well-formed version that correlates with the search query.
The canonicalization model may be a neural network model. The patent provides more details on the nature of the neural network used.
The neural network can indicate a well-formed query version of the original query.
We are also told that in addition to identifying a well-formed query, it may also determine “one or more related queries for a given search query.”
A related query can be determined based on the related query being frequently submitted by users following the submission of the given search query.
The query canonicalization system can also determine if the related query is well-formed. If it isn’t, then it can determine a well-formed variant of the related query.
For example, in response to the submission of the given search query, a selectable version of the well-formed variant can be presented along with search results for the given query and, if selected, the well-formed variant (or the related query itself in some implementations) can be submitted as a search query and results for the well-formed variant (or the related query) then presented.
Again, the idea of “intent” surfaces in the patent regarding related queries (people also search for queries)
The value of showing a well-formed variant of a related query, instead of the related query itself, is to let a searcher more easily and/or more quickly understand the intent of the related query.
The patent tells us that this has a lot of value by stating:
Such efficient understanding enables the user to quickly submit the well-formed variant to quickly discover additional information (i.e., result(s) for the related query or well-formed variant) in performing a task and/or enables the user to only submit such query when the intent indicates likely relevant additional information in performing the task.
We are given an example of a related well-formed query in the patent:
As one example, the system can determine the phrase “hypothetical router configuration” is related to the query “reset hypothetical router” based on historical data indicating the two queries are submitted proximate (in time and/or order) to one another by a large number of users of a search system.
In some such implementations, the query canonicalization system can determine the related query “reset hypothetical router” is not a well-formed query, and can determine a well-formed variant of the related query, such as: “how to reset hypothetical router”.
The well-formed variant “how to reset hypothetical router” can then be associated, in a database, as a related query for “hypothetical router configuration”—and can optionally supplant any related query association between “reset hypothetical router” and “hypothetical router configuration”.
The patent tells us that sometimes a well-formed related query might be presented as a link to search results.
Again, one of the features of a well-formed query is that it is grammatical, is an explicit question, and contains no spelling errors.
The patent application can be found at:
Canonicalizing Search Queries to Natural language Questions
Inventors Manaal Faruqui and Dipanjan Das
Applicants Google LLC
Publication Number 20200167379
Filed: January 18, 2019
Publication Date May 28, 2020
Techniques are described herein for training and/or utilizing a query canonicalization system. In various implementations, a query canonicalization system can include a classification model and a canonicalization model. A classification model can be used to determine if a search query is well-formed. Additionally, a canonicalization model can be used to determine a well-formed variant of a search query in response to determining a search query is not well-formed. In various implementations, a canonicalization model portion of a query canonicalization system can be a sequence to sequence model.
Well-Formed Query Takeaways
I have summarized the summary of the patent, and if you want to learn more details, click through and read the detailed description. The two white papers I started the post off with describing databases of well-formed questions that people as Google (including the inventors of this patent) have built and show the effort that Google has put into the idea of rewriting queries so that they are well-formed queries, where the intent behind them can be better understood by the search engine.
As we have seen from this patent, the analysis that is undertaken to find canonical queries also is used to surface “people also search for” queries, which may also be canonicalized and displayed in search results.
A well-formed query is grammatically correct, contains no spelling mistakes, and asks an explicit question. It also makes it clear to the search engine what the intent behind the query may be.
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