Have you ever counted the number of premature obituaries you’ve read for email? The platform has taken some flak in recent years, but as a method for communicating with consumers it’s stronger and more effective than ever.
That view was reinforced earlier this month with Google’s announcement that it would bring the ‘Accelerated Mobile Pages’ open source project to the platform.
The move signaled the internet giant’s plan to redevelop its Gmail service and turn email into a ‘dynamic, up-to-date and actionable’ service, in line with its long-held desire to make the internet faster. In short, it wants to make it more interactive and more efficient.
Right now, most organizations consider an open rate of above 25% and a click-through rate (CTR) of more than 5% impressive, and Google wants to improve that by radically altering the make-up of each individual email.
The Silicon Valley giant has recognized the impressive longevity and adaptability of email. Despite the abundance of browsing data being collected online every day, it remains one of the most pervasive and effective forms of direct marketing; according to the Direct Marketing Association in the US, the median email marketing ROI (122%) is four times higher than any other channel.
So, Google has tasked its creative minds with revamping and progressing its email platform, with this the immediate result.
What will this mean in the short term?
Your favorite brands will now be able to integrate new interactive tools into email, such as the ability to browse websites, RSVP to events and complete forms without you leaving the platform.
Initially available as a ‘preview’ version to developers, the company plans to roll out support for the service to Gmail later in 2018. The service will continue to evolve, and in the future we’re likely to see entire transactions taking place within the body of an email.
Relatively mundane consumer tasks such as booking flights, writing reviews, ordering new clothes and browsing the wider web will all take place through one interface, removing the need for consumers to waste time navigating individual sites or search engines and creating a unified experience.
What’s driving this move?
There appear to be three main drivers on Google’s part: improved UX, more access to consumer data, and an increased scope to sell digital advertising. By providing a more streamlined service which facilitates commercial transactions online, Google will have greater scope to expand its offering to advertisers.
This will be based on the detailed insights gained from witnessing millions of consumer transactions within its Gmail platform, with this data used to build a more comprehensive digital persona for each individual user.
What are the benefits for consumers?
Google will undoubtedly be a beneficiary, but the company promises that consumers will benefit most from the change. Central to this is the promise of an improved experience of ecommerce when navigating the web. This will happen through a more direct relationship between consumers and their favorite brands, and fewer laborious administrative stages to complete a transaction or make an appointment.
By integrating live data into the platform, emails will be able to demonstrate a brand’s inventory in real time – so no more outdated discount offers, or appointments showing as available which have already been filled.
The move will also help refresh the occasionally cumbersome format of certain marketing communications. Email newsletters for example will be given a new dimension, giving consumers far more succinct and actionable content, while landing pages with extensive web capture forms will be phased out as brands collect further information on email and other sources.
How will Google’s position be strengthened?
As with any format change, it will take some time for AMP to be fully integrated into Gmail, so don’t expect any radical changes any time soon. Once integrated, it will also take time for brands to get on board and realize the ROI they will get from their spend. Moreover, as the change will be limited to Gmail only, we’re unlikely to see the entire format of email revolutionized overnight.
Nonetheless, it will be fascinating to see how Google’s competitors respond to the introduction of the AMP format. Many are keen to prevent the company’s hold over the web from growing, and will no doubt push forward with alternative propositions to AMP.
Facebook’s ‘Instant Articles’ service, for example, has long been viewed as an alternative platform for ‘snackable’ content, and was launched as long ago as the spring of 2015 – a year prior to the launch of the AMP.
Email’s enduring success has traditionally been ascribed to its simple format, so it’ll also be fascinating to see what kind of response there is from consumers.
Historically, they prefer communications which are less invasive and don’t interrupt their day to day activity, as can be the case with other direct marketing platforms. Many also prefer to retain their freedom of choice when it comes to purchasing, rather than follow a recommendation from a dispassionate algorithm. But the opportunity is there for marketers to rise to raise the bar when it comes to driving email engagement.
What does this mean for marketers?
From a practical perspective, AMP is likely to see a change in the performance metrics used by marketers when reviewing the success of any given campaign. CTRs in particular may be replaced by an alternative measure, given consumers will no longer need to exit an email to complete a transaction.
From a more long-term, strategic perspective, Google needs to put personalization at the heart of this change to make it successful. If the content offered in each email isn’t highly personalized to each individual user – based on the extensive raft of data Google already possesses – then consumers will turn away from the platform in favor of a more holistic marketing experience.
Artificial Intelligence (AI) will undertake a large part of this work. Indeed, AI marketing tools are already widely available and have been deployed by some of the world’s biggest brands to help deliver personalization in their email marketing campaigns.
To date, these technologies have largely been deployed to help with execution, but in future, expect to see AI take care of every aspect of an email, right down to the send time, design, subject line and body of text, including bespoke offers for each individual recipient.
It will be particularly crucial when it comes to creativity, which has been absent from email for many years due to the predominance of the ‘static’ HTML format. Marketers have struggled to create engaging content within the platform previously, as emails have had to rely on basic content – straightforward written copy and primitive designs/imagery – to ensure they reach target recipients.
With AMP, however, technology is finally catching up with the promise of marketing. Email marketers will need to get their creative juices flowing and use the change to embrace more engaging content strategies, as more simplistic email formats with limited scope for interaction will no longer entice customers.
The email platform continues to evolve, adapt and reinvent itself, despite premature predictions of its demise, and it looks set to form an integral part of direct marketing strategies for the foreseeable future.
Remember what I said about premature obituaries? Well, to reinvent the age-old proverb: email is dead. Long live email.
Higher experiment limit
Many of our users have given us the feedback that the current limit of 3 simultaneous running experiments is too low. This limit forces them to make difficult tradeoffs about which tests and customer segments should be prioritized. To help address this, we will soon be increasing this limit to 5 experiments. We believe this will give you more opportunity to use Optimize across your entire site.
New “Getting started with Google Optimize” video series
For many, running website tests may appear to be a daunting task. To make things easier, for anyone completely new to testing or recently started using Optimize, we’ve created a “Getting started with Google Optimize” video series. This will help you start testing in no time. Plus, you can watch the entire series in less than 15 minutes!
Optimize Overview: Quick primer on what Optimize is and how it can help you
Once you’re done watching the video series, be sure to create an Optimize account, if you don’t already have one.
We hope you like these changes. Stay tuned, because there are more improvements coming!
Posted by Rotimi Iziduh, Product Manager, Google Optimize
We’re excited to announce that you can now survey over 50 countries around the globe with Google Surveys.
When we first launched Google Surveys in 2012 (we called ourselves Google Consumer Surveys back then), our goal was to put quality market research in the hands of businesses of all sizes. Market research was costly and time-consuming in those days, and that made it hard for many companies to make decisions based on what their customers were actually thinking.
Google Surveys made it easy to keep your finger on the pulse of your customers with fast, reliable insights from real people. Since then, we’ve continued making improvements to the product. We also launched Surveys 360, our enterprise version, with advanced targeting, reporting and sharing features.
And now users of both versions can reach people in more than 50 countries. Wondering if your new product line should launch in Portugal? Stop guessing and find out. Lacking competitive intel in India? Not anymore. Trying to convince your boss that your idea is better? We can help with that.
“As a global company, we’re especially excited about the targeting expansion to over 50 new countries. We’ll be using Google Surveys to run consumer research and brand awareness studies in markets that have historically been difficult for researchers to access.” Frank Kelly, SVP Global Marketing & Strategy, Lightspeed GMI
These new targeting choices are available starting today. Hear more from our product team in this video:
To learn more about the new country options, see our help center article.
Posted by Michael Cumberbatch, Product Manager, Google Surveys team
We are only 2 weeks away from the PPC Hero Summit – a free online event offering top-notch PPC training and valuable discussions on trends and updates. Last week, we dove a little deeper into the first two sessions of the Summit. Today, we’ll talk about 2 more! Important 2018 Google AdWords Updates (12pm-12:20pm) In […]
Read more at PPCHero.com
Any stellar SEO strategy should be meticulously tracked and heavily data-driven.
Gut feel is great when deciding on which new pair of shoes to buy, but it’s not the best foundation to base your SEO work upon.
Google Analytics is a treasure trove of insightful data. And it’s free! However, with so much data available at our fingertips, it can be a bit of a minefield, and most people only scratch the surface.
Keyword rankings are great for stroking your ego and making your client smile and nod, but they don’t tap into the bigger picture.
In order to continually build on and improve your campaign, you need to pay close attention to the nitty-gritty of your data. There’s a lot to take into account, but in this post we’ll provide an overview of the key Google Analytics reports and views to bolster your SEO campaigns.
Many of these reports can be created as custom reports, which is handy for tailoring your reporting to specific business needs and sharing with clients.
Read on and we’ll help you to track and measure your SEO efforts like the analytical guru you are.
1. Organic search
Where to find it: ‘Acquisition’ > ‘Overview’ > Click through to ‘Organic Search’
It’s an obvious one but a good place to start. Head to the ‘Overview’ tab under ‘Acquisition’ for a base level indication of your website’s primary traffic channels. This provides an immediate summary of your top channels and how each is performing in terms of traffic volume, behavior and conversions.
As well as showing a general overview of organic traffic, you can also dig deeper into the data by clicking on ‘Organic Search’ in the table and playing around with the filters. Consider the most popular organic landing pages, an overview of keywords, search engines sending the most traffic, exit pages, bounce rates, and more.
On the topic of bounce rates, it’s a good idea to pay particular attention to this metric with regards to individual pages. Identify those pages with a bounce rate that is below the average for your site. Take some time to review these pages and work out why that might be, subsequently applying any UX/UI or targeting amendments.
This is all very well but wouldn’t it be handy if you could view only your organic traffic across the whole of your Google Analytics? It’s easier than you think. Simply click to ‘Add Segment’ and check the box for organic traffic.
Leave the ‘All Users’ segment for a handy comparison, or remove this segment for a view of only your organic traffic.
2. Landing page and page titles
Where to find it: ‘Behavior’ > ‘Site Content’ > ‘Landing Pages’ > Add secondary dimension ‘Page Titles’
One of the most frustrating aspects of Google Analytics organic reports is the dreaded ‘(not provided)’ result which features under ‘Keyword’.
This unfortunate occurrence is the result of searches which have been carried out securely. In other words, if the URL of the search engine features HTTPS or if they are logged into a Google account and therefore protected by data privacy policies. In these scenarios, the search term deployed by the user will not be provided.
But how wonderful would it be to see a list of all the search terms people used to find your site? Unfortunately I’m not a magician and I can’t abracadabra these search phrases from the Google abyss. But I can offer an alternative solution that will at least give you an overview.
View your organic traffic via landing page and page title, as this will show which pages are performing best in terms of organic search. By including the page title, you can then look at which keywords those pages are optimised for and get a pretty good idea of the search phrases users are deploying and those which are performing best in terms of traffic and bounce rate.
This can also help you identify the pages which are not performing well in terms of organic traffic. You can then review whether the keywords need refining, the onsite optimization needs an overhaul, or the content needs revamping.
3. Conversion goals
Where to find it: ‘Conversions’ > ‘Goals’ > ‘Overview’
It’s all very well having a high volume of organic traffic but if it isn’t converting then there’s really not much point. To test the quality of your organic traffic, you need to be tracking conversions. There are two levels to this.
The first is your conversion goals. You can filter these with regards to traffic and understand what percentage of a website’s conversions are resulting from organic traffic.
To further improve this data, add monetary value to your conversions to better demonstrate the value that your SEO efforts are bringing. Some clients care only about keyword rankings, some care only about the dollar signs. Either way, it’s worth spending some time with your client to work out how much each conversion is worth and the data that they are most interested in.
For example, let’s say you sell kitchens. If you know the average cost of a sale and the percentage of kitchen brochure downloads which convert to a sale, then you can work out an approximate value for each conversion.
4. Assisted conversions
Where to find it: ‘Conversions’ > ‘Multi-Channel Funnels’ > ‘Assisted Conversions’
Although useful, conversion goals only give a surface view of conversions. What if someone initially found your website via Google and didn’t convert, but then later returned to your website by typing in the URL direct and then converted?
It’s very common for users not to convert on their first visit to a website, especially if they are only in the awareness or consideration phase of the sales funnel. When returning the next time around to make a purchase, they are more likely to go direct, or perhaps they see a reminder via social media.
This is where assisted conversions can save the day. Find these by clicking on ‘Multi-Channel Funnels’ under ‘Conversions’, and then ‘Assisted Conversions’.
With this data, you can identify whether each channel featured on the conversion path of a user, therefore providing more accurate data in terms of the quality of your organic traffic.
Pay attention to any drops or surges in organic traffic in this section. If, for example, you have noticed a drop in organic assisted conversions yet your organic traffic has remained consistent, then it may indicate that the leads are no longer as qualified. This should prompt a review of your keyword and content strategy.
5. Site speed
Where to find it: ‘Behavior’ > ‘Site Speed’ > ‘Overview’
Site speed is important, we all know that. There are a number of tools we can use to find out the overall speed of a website: Google Page Insights, Pingdom, GTmetrix. However, these don’t tend to drill down into specific pages. The site speed report via Google Analytics can help you to identify any pages which are proving particularly slow.
You are likely to see a correlation between the time taken to load and the exit pages, you can also layer in bounce rate metrics.
Using this information regarding individual pages, you can then approach your development team with the cold hard evidence that they need to resolve that page speed issue.
6. Site search
Where to find it: ‘Behavior’ > ‘Site Search’ > ‘Search Terms’
If you have a site search function on your website then this report is super useful for a number of reasons. Firstly, it can indicate where the user experience may not be particularly strong on your website. If a page is proving difficult to find without having to search for it then it may hint at a wider site navigation issue.
In addition, it can also help identify any keywords or search terms which you may need to create a new page for if one does not already exist. The site search report is ideal for unearthing these gaps in your website’s offering.
Where to find it: ‘Audience’ > ‘Mobile’ > ‘Overview’
Comparing the traffic of mobile users to that of desktop and tablet is a handy way of identifying whether your site may have some mobile optimization issues. For example, if the bounce rate of mobile sessions is significantly higher than that of your desktop sessions, then you may need to carry out a mobile site audit.
It’s also worth considering the conversion rate of the different devices, as this can indicate which device traffic is the most valuable.
Given that over half of website traffic is now on mobile, you should see similar results reflected in your own analytics. Although it’s worth bearing in mind that some businesses are more likely to be more prevalent on mobile than others.
For example, a local business should feature in a lot of mobile searches, whereas a business to business service is more likely to be searched for on desktop by people sitting in an office.
8. Customize your dashboard
Where to find it: ‘Customization’ > ‘Dashboards’
Finally, for a quick overview of reporting, it pays to design a tailored dashboard for your client. We often find that clients don’t appreciate too much text or complex tables in reports, as they can be overwhelming at an initial glance.
Sure, you may be a Google Analytics whizz, but the chances are that your client isn’t. Therefore presenting the data in a way that is digestible and manageable is key to convincing them of your SEO prowess.
Create a dashboard that your client will understand. Use digestible charts, like bar graphs, pie charts and simplified tables. This will help the client visualize all of the data in one easy-to-view report. This can also be emailed to your client each week so they get regular updates.
Dashboards are created using customizable widgets. Begin by selecting the type of widget: this could be a simple metric, a timeline, a geomap, a table, or a pie or bar chart. With some widgets, you can also select whether to show a specified date range or whether to show data in real-time.
Once you have chosen your widget, you can configure the finer details, such as dimensions and other options depending on the type. Widgets can be edited, cloned or deleted, allowing flexibility in refining your dashboard as both you and your client see fit. For further information on creating a custom dashboard, have a read of Google’s handy guide.
There are a whole myriad of other reports and views available within Google Analytics; it takes time to become familiar with all the different types of data and formats. Hopefully this list has provided a solid starting point for genuinely valuable and insightful SEO reporting.
AdWords integration: Find the best landing page
Marketers spend a lot of time optimizing their Search Ads to find the right message that brings the most customers to their site. But that’s just half the equation: Sales also depend on what happens once people reach the site.
The Optimize and AdWords integration we announced in May gives marketers an easy way to change and test the landing pages related to their AdWords ads. This integration is now available in beta for anyone to try. If you’re already an Optimize user, just enable Google Optimize account linking in your AdWords account. (See the instructions in step 2 of our Help Center article.) Then you can create your first landing page test in minutes.
Suppose you want to improve your flower shop’s sales for the keyword “holiday bouquets.” You might use the Optimize visual editor to create two different options for the hero spot on your landing page: a photo of a holiday dinner table centerpiece versus a banner reading “Save 20% on holiday bouquets.” And then you can use Optimize to target your experiment to only show to users who visit your site after searching for “holiday bouquets.”
If the version with the photo performs better, you can test it with other AdWords keywords and campaigns, or try an alternate photo of guests arriving with a bouquet of flowers.
Objectives: More flexibility and control
Since we released Optimize and Optimize 360, users have been asking us for a way to set more Google Analytics metrics as experiment objectives. Previously,
Optimize users could only select the default experiment objectives built into Optimize (like page views, session duration, or bounces), or select a goal they had already created in Analytics.
With today’s launch, Optimize users no longer need to pre-create a goal in Analytics, they can create the experiment objective right in Optimize:
When users build their own objective directly in Optimize, we’ll automatically help them check to see if what they’ve set up is correct.
Plus, users can also set their Optimize experiment to track against things like Event Category or Page URL.
Learn more about Optimize experiment objectives here.
Why do these things matter?
It’s always good to put more options and control into the hands of our users. A recent study showed that marketing leaders – those who significantly exceeded their top business goal in 2016 – are 1.5X as likely to say that their organizations currently have a clear understanding of their customers’ journeys across channels and devices.1 Testing and experimenting is one way to better understand and improve customer journeys, and that’s what Optimize can help you do best.
1Econsultancy and Google, “The Customer Experience is Written in Data”, May 2017, U.S.
Posted by Rotimi Iziduh and Mary Pishny, Product Managers, Google Optimize
One of the inventors of the newly granted patent I am writing about was behind one of the most visited Google patents I’ve written about, from Ross Koningstein, which I posted about under the title, The Google Rank-Modifying Spammers Patent It described a social engineering approach to stop site owners from using spammy tactics to raise the ranking of pages.
This new patent is about targeted advertising at Google in paid search, which I haven’t written too much about here. I did write one post about paid search, which I called, Google’s Second Most Important Algorithm? Before Google’s Panda, there was Phil I started that post with a quote from Steven Levy, the author of the book In the Plex, which goes like this:
They named the project Phil because it sounded friendly. (For those who required an acronym, they had one handy: Probabilistic Hierarchical Inferential Learner.) That was bad news for a Google Engineer named Phil who kept getting emails about the system. He begged Harik to change the name, but Phil it was.
What this showed us was that Google did not use the AdSense algorithm from the company they acquired in 2003 named Applied Semantics to build paid search. But, it’s been interesting seeing Google achieve so much based on a business model that relies upon advertising because they seemed so dead set against advertising when then first started out the search engine. For instance, there is a passage in an early paper about the search engine they developed that has an appendix about advertising.
If you read through The Anatomy of a Large-Scale Hypertextual Web Search Engine, you learn a lot about how the search engine was intended to work. But the section about advertising is really interesting. There, they tell us:
Currently, the predominant business model for commercial search engines is advertising. The goals of the advertising business model do not always correspond to providing quality search to users. For example, in our prototype search engine, one of the top results for cellular phone is “The Effect of Cellular Phone Use Upon Driver Attention”, a study which explains in great detail the distractions and risk associated with conversing on a cell phone while driving. This search result came up first because of its high importance as judged by the PageRank algorithm, an approximation of citation importance on the web [Page, 98]. It is clear that a search engine which was taking money for showing cellular phone ads would have difficulty justifying the page that our system returned to its paying advertisers. For this type of reason and historical experience with other media [Bagdikian 83], we expect that advertising funded search engines will be inherently biased towards the advertisers and away from the needs of the consumers.
So, when Google was granted a patent on December 26, 2017, that provides more depth on how targeted advertising might work at Google, it made interesting reading. This is a continuation patent, which means the description ideally should be approximately the same as the original patent, but the claims should be updated to reflect how the search engine might be using the processes described in a newer manner. The older version of the patent was filed on December 30, 2004, but it wasn’t granted under the earlier claims. It may be possble to dig up those earlier claims, but it is interesting looking at the description that accompanies the newest version of the patent to get a sense of how it works. Here is a link to the newest version of the patent with claims that were updated in 2015:
Associating features with entities, such as categories of web page documents, and/or weighting such features
Inventors: Ross Koningstein, Stephen Lawrence, and Valentin Spitkovsky
Assignee: Google Inc.
US Patent: 9,852,225
Granted: December 26, 2017
Filed: April 23, 2015
Features that may be used to represent relevance information (e.g., properties, characteristics, etc.) of an entity, such as a document or concept for example, may be associated with the document by accepting an identifier that identifies a document; obtaining search query information (and/or other serving parameter information) related to the document using the document identifier, determining features using the obtained query information (and/or other serving parameter information), and associating the features determined with the document. Weights of such features may be similarly determined. The weights may be determined using scores. The scores may be a function of one or more of whether the document was selected, a user dwell time on a selected document, whether or not a conversion occurred with respect to the document, etc. The document may be a Web page. The features may be n-grams. The relevance information of the document may be used to target the serving of advertisements with the document.
I will continue with details about how this patent describes how they might target advertising at Google in a part 2 of this post.
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There was a park in the town in Virginia where I used to live that had been a railroad track that was turned into a walking path. At one place near that track was a historic turntable where cargo trains might be unloaded so that they could be added to later trains or trains headed in the opposite direction. This is a technology that is no longer used but it is an example of how technology changes and evolves over time.
There are people who write about SEO who have insisted that Google uses a technology called Latent Semantic Indexing to index content on the Web, but make those claims without any proof to back them up. I thought it might be helpful to explore that technology and its sources in more detail. It is a technology that was invented before the Web was around, to index the contents of document collections that don’t change much. LSI might be like the railroad turntables that used to be used on railroad lines.
There is also a website which offers “LSI keywords” to searchers but doesn’t provide any information about how they generate those keywords or use LSI technology to generate them, or provide any proof that they make a difference in how a search engine such as Google might index content that contains those keywords. How is using “LSI Keywords” different from keyword stuffing that Google tells us not to do. Google tells us that we should:
Focus on creating useful, information-rich content that uses keywords appropriately and in context.
Where does LSI come from
One of Microsoft’s researchers and search engineers, Susan Dumais was an inventor behind a technology referred to as Latent Semantic Indexing which she worked on developing at Bell Labs. There are links on her home page that provide access to many of the technologies that she worked upon while performing research at Microsoft which are very informative and provide many insights into how search engines perform different tasks. Spending time with them is highly recommended.
She performed earlier research before joining Microsoft at Bell Labs, including writing about Indexing by Latent Semantic Analysis. She was also granted a patent as a co-inventor on the process. Note that this patent was filed in April of 1989, and was published in August of 1992. The World Wide Web didn’t go live until August 1991. The LSI patent is:
Computer information retrieval using latent semantic structure
Inventors: Scott C. Deerwester, Susan T. Dumais, George W. Furnas, Richard A. Harshman, Thomas K. Landauer, Karen E. Lochbaum, and Lynn A. Streeter
Assigned to: Bell Communications Research, Inc.
US Patent: 4,839,853
Granted: June 13, 1989
Filed: September 15, 1988
A methodology for retrieving textual data objects is disclosed. The information is treated in the statistical domain by presuming that there is an underlying, latent semantic structure in the usage of words in the data objects. Estimates to this latent structure are utilized to represent and retrieve objects. A user query is recouched in the new statistical domain and then processed in the computer system to extract the underlying meaning to respond to the query.
The problem that LSI was intended to solve:
Because human word use is characterized by extensive synonymy and polysemy, straightforward term-matching schemes have serious shortcomings–relevant materials will be missed because different people describe the same topic using different words and, because the same word can have different meanings, irrelevant material will be retrieved. The basic problem may be simply summarized by stating that people want to access information based on meaning, but the words they select do not adequately express intended meaning. Previous attempts to improve standard word searching and overcome the diversity in human word usage have involved: restricting the allowable vocabulary and training intermediaries to generate indexing and search keys; hand-crafting thesauri to provide synonyms; or constructing explicit models of the relevant domain knowledge. Not only are these methods expert-labor intensive, but they are often not very successful.
The summary section of the patent tells us that there is a potential solution to this problem. Keep in mind that this was developed before the world wide web grew to become the very large source of information that it is, today:
These shortcomings, as well as other deficiencies and limitations of information retrieval, are obviated, in accordance with the present invention, by automatically constructing a semantic space for retrieval. This is effected by treating the unreliability of observed word-to-text object association data as a statistical problem. The basic postulate is that there is an underlying latent semantic structure in word usage data that is partially hidden or obscured by the variability of word choice. A statistical approach is utilized to estimate this latent structure and uncover the latent meaning. Words, the text objects and, later, user queries are processed to extract this underlying meaning and the new, latent semantic structure domain is then used to represent and retrieve information.
To illustrate how LSI works, the patent provides a simple example, using a set of 9 documents (much smaller than the web as it exists today). The example includes documents that are about human/computer interaction topics. It really doesn’t discuss how a process such as this could handle something the size of the Web because nothing that size had quite existed yet at that point in time. The Web contains a lot of information and goes through changes frequently, so an approach that was created to index a known document collection might not be ideal. The patent tells us that an analysis of terms needs to take place, “each time there is a significant update in the storage files.”
There has been a lot of research and a lot of development of technology that can be applied to a set of documents the size of the Web. We learned, from Google that they are using a Word Vector approach developed by the Google Brain team, which was described in a patent that was granted in 2017. I wrote about that patent and linked to resources that it used in the post: Citations behind the Google Brain Word Vector Approach. If you want to get a sense of the technologies that Google may be using to index content and understand words in that content, it has advanced a lot since the days just before the Web started. There are links to papers cited by the inventors of that patent within it. Some of those may be related in some ways to Latent Semantic Indexing since it could be called their ancestor. The LSI technology that was invented in 1988 contains some interesting approaches, and if you want to learn a lot more about it, this paper is really insightful: A Solution to Plato’s Problem: The Latent Semantic Analysis Theory of Acquisition, Induction and Representation of Knowledge. There are mentions of Latent Semantic Indexing in Patents from Google, where it is used as an example indexing method:
Text classification techniques can be used to classify text into one or more subject matter categories. Text classification/categorization is a research area in information science that is concerned with assigning text to one or more categories based on its contents. Typical text classification techniques are based on naive Bayes classifiers, tf-idf, latent semantic indexing, support vector machines and artificial neural networks, for example.
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Today at Dreamforce, Google and Salesforce are announcing a strategic partnership to deliver four new, turnkey integrations between Google Analytics 360, Salesforce Sales Cloud and Salesforce Marketing Cloud:
- Sales data from Sales Cloud will be available in Analytics 360 for use in attribution, bid optimization and audience creation
- Data from Analytics 360 will be visible in the Marketing Cloud reporting UI for a more complete understanding of campaign performance
- Audiences created in Analytics 360 will be available in Marketing Cloud for activation via direct marketing channels, including email and SMS
- Customer interactions from Marketing Cloud will be available in Analytics 360 for use in creating audience lists
These new connections between our market-leading digital analytics solution and Salesforce’s market-leading customer relationship management (CRM) platform will change the game for how our clients understand and reach their customers — and how they measure the impact of their marketing. These integrations are fully consistent with our privacy policies and have settings that offer privacy controls and choice on how data is used.
By integrating your customer data, you can see a customer’s path from awareness all the way through to conversion and retention. And with connections to Google’s ad platforms and Salesforce’s marketing platform, you can quickly take action, engaging them at the right moment. You’ll see these new integrations begin to arrive in the first half of 2018.
Until now, businesses have not been able to connect offline interactions, such as an estimate provided by a call center rep or an order closed by a field sales rep, with insights on how customers use digital channels. With the connection between Sales Cloud and Analytics 360, soon you’ll be able to include offline conversions in your attribution modeling when using Google Attribution 360, so you’ll have a more complete view of ROI for each of your marketing channels and even more reason to move away from a last-click attribution method. This integration will also let you see how your most valuable customers engage with your digital properties, answering some important questions like, what are they looking for and are they actually finding what they need?
With the integration allowing data from Analytics 360 to be visible in Marketing Cloud, you’ll gain a more complete understanding of how your marketing campaigns perform. For example, if you send an email campaign to frequent shoppers to promote your fall fashion line, you’ll be able to see right in Marketing Cloud information such as how many pages people visited when they came to your site, the number of times people clicked on product details to learn more, and how many people added items to their shopping cart and converted.
Easy to take action
Today, Google Analytics allows you to create audience lists and goals that you can easily send to AdWords and DoubleClick for digital remarketing and to optimize bids. With the new connection from Sales Cloud to Analytics 360, in addition to unlocking new insights and more data for attribution modeling, you’ll be able to combine Salesforce data (such as sales milestones or conversions) with behavioral data from your digital properties to create richer audiences and for smarter bidding.
For example, if you’re a residential solar panel company and want to find new customers, you can create an audience in Analytics 360 of qualified leads from Sales Cloud and use AdWords or DoubleClick Bid Manager to reach people with similar characteristics. Or, create a goal in Analytics 360 based on leads marked as closed in Sales Cloud, and automatically send that goal to AdWords or DoubleClick Search to optimize your bidding and drive more conversions.
With the Analytics 360 connection to Marketing Cloud, you’ll be able to use customer insights to take action in marketing channels beyond Google’s ad platforms, such as email, SMS or push notification. For example, you can create an audience in Analytics 360 of customers who bought a TV on your site and came back later to browse for home theater accessories, and use that list in Salesforce to promote new speakers with a timely and relevant email.
Every day, Google Analytics processes hundreds of billions of customer moments, Salesforce Marketing Cloud sends 1.4 billion emails, and there are over 5 million leads and opportunities created in Salesforce Sales Cloud. These new integrations represent a powerful combination, and we believe they will help marketers take a big step closer to the ultimate dream: providing every customer with a highly relevant experience at each step of their journey.
You’ll see these new joint capabilities become available beginning in 2018, and we’ll be sure to keep you updated along the way. Contact us here if you would like to learn more about Analytics 360. We hope you’re as excited as we are!
Posted by Babak Pahlavan, Senior Director of Product Management, Measurement & Analytics
The Google Analytics 360 + Salesforce integrations are just one part of a broader strategic alliance announced today between Google and Salesforce. Read about new integrations between G Suite and Salesforce and a new partnership between Google Cloud and Salesforce here.
Today we’re introducing the first of these integrations: sales pipeline data from Sales Cloud (e.g. leads, opportunities) can now be imported directly into Analytics 360, so any marketer in a business that manages leads can see a more complete view of the customer’s path to conversion and quickly take action to engage them at the right moment. Enterprises such as Rackspace and Carbonite are already benefiting from this integration, saving hours piecing together data and reaching new, more valuable audiences.
A complete view of the customer journey
We often hear from marketers how difficult it is to connect online and offline customer interactions in order to see a complete view of a customer’s journey — and they also tell us how helpful it would be if they could do it successfully. Good news: with the turnkey integration between Sales Cloud and Analytics 360, marketers can now easily combine offline sales data with their digital analytics data so they can see a complete view of the conversion funnel.
This opens up new ways to understand how customers engage with brands and how marketing programs perform. For example, marketers can explore the relationship between the traffic source for online leads (e.g. organic search vs. paid search vs. email) and the quality of those leads, as measured by how they progress through the sales pipeline.
Example of a report in Google Analytics 360 showing the relationship between the traffic source for online leads and the progression of those leads through the sales pipeline, as tracked in Salesforce
With the built-in connection between Analytics 360 and BigQuery, Google Cloud’s enterprise data warehouse, marketers can also easily move Sales Cloud data from Analytics 360 into Google Cloud to join it with other datasets and unlock BigQuery’s powerful set of tools for identifying insights.
Better marketing outcomes
More visibility into the customer journey is great — but the real value comes from being able to take action. For example, if one source of site traffic consistently delivers leads that are higher quality than another source, budget can be shifted to drive more of the better traffic.
The built-in connections between Analytics 360 and Google’s media buying platforms offer additional ways to find new customers and drive incremental revenue. Marketers can use the tools in AdWords and DoubleClick Search to optimize their bidding on search ads based on the goal of actual sales (offline conversions tracked in Salesforce) rather than just basic website leads. Or they can create an audience list in Analytics 360 of qualified leads from Sales Cloud and use AdWords or DoubleClick Bid Manager so their display ads reach people with similar characteristics.
“People are doing backflips over this”
Rackspace® is a provider of managed cloud services that relies heavily on digital marketing channels to capture interest from potential customers and drive new business. Rackspace has been beta testing the Sales Cloud to Analytics 360 integration and the team has already seen significant benefits from connecting their sales pipeline reporting to their digital marketing analytics.
“Being able to easily see our sales pipeline data in Google Analytics and get complete funnel reports with no manual work has been a game changer. We’re now able to quickly diagnose changes in lead volume and quality, and trace them back to our marketing investments in a way that was not possible before.
We’re getting better insights into our marketing performance and getting those insights much more quickly than when we were trying to stitch this together manually — saving 8-10 hours each week and reducing the lag from importing offline conversion data from 4-6 weeks to virtually real-time. People are doing backflips over this!” – Lara Indrikovs, Senior Manager, Digital Insights & Analytics
Carbonite offers cloud data back-up services that help protect personal and business data from data loss. Carbonite has also been beta testing the Sales Cloud integration and is gearing up to change their media activation strategy to take advantage of the new insights that are now available to them.
“We’re really excited about the opportunity to leverage Salesforce data in Google Analytics and our AdWords media campaigns. This will allow us to activate pipeline acceleration and lookalike prospecting campaigns based on the profiles of companies that achieved key milestones in our customer lifecycle after becoming a lead. We expect this new approach will improve our ROI by shifting our targeting capabilities towards more valuable leads and opportunities.” – Norman Guadagno, SVP of Marketing
Over the next few months we’ll be making additional Sales Cloud data available in Analytics 360, giving marketers even more intelligence. For example:
- Product-specific data will make it possible to run remarketing campaigns that present cross-sell or up-sell offers to customers based on products previously ordered
- Data predicting the likelihood of lead conversion will let marketers create audience lists of prospects who have a high likelihood of purchasing, which can be used for remarketing (to move people along the sales funnel) or prospecting
- Lifetime value data can be used as a diagnostic tool to provide insight into which marketing channel brings in the highest value customers
As 2018 moves on, we’ll continue to roll out more of the Salesforce-Analytics 360 integrations announced back in November. Soon marketers will be able to include conversion data from Sales Cloud in Google Attribution 360 for more accurate data-driven attribution modeling, surface data from Analytics 360 in Marketing Cloud for a more complete understanding of campaign performance, and make audiences created in Analytics 360 available in Marketing Cloud for activation via direct marketing channels like email.
Contact us here if you are not yet using Analytics 360 and would like to learn more. Current customers can talk to your account team or Certified Analytics Partner about developing a plan for implementing these integrations.
Stay tuned, it’s going to be a big year!
Kyle Harrison, Group Product Manager, Google Analytics