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Data Aggregators: Upsell Clients with Deeper Data Insights

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Firms that specialize in data and analytics are in big demand these days. Even large companies that used to be able to manage data in-house are beginning to outsource to experts at data firms. Businesses are looking for help with managing and processing data, but they’re also beginning to look for more than just the basics. It seems we’re hearing the term “Data as a Service” (DaaS) being coupled with newer terms like “Insights as a Service” (IaaS) as the technology speeds us forward.

A new report released by Forrester, Insights Services Disrupt The Data And Analytics Market, addresses this trend, detailing how changes in the marketplace are driving businesses to outsource their data needs to specialists such as data aggregators and other DaaS firms, and stressing the need for these data firms to adapt quickly to support this growing market.

One of the report’s authors, Jennifer Belissent, Ph.D., writes in a blog post, Introducing the New Insights Service Provider, “According to Forrester’s Q3 2015 Global State of Strategic Planning, Enterprise Architecture, and PMO Online Survey, 73 percent of companies understand the business value of data and aspire to be data-driven but just 29 percent confirm that they are actually turning data into action.”

The Forrester team recommends a new approach for data experts to consider.

A great time to be a data aggregator

Data aggregators and other data-crunching firms that are keeping up with the trends are in high demand. They’re also attracting some of the best talent in the data sciences, and if you’ve been looking to hire data experts, you know how competitive the market is these days.

Data firms understand what Belissent refers to as the “insights services cycle”. She argues that an increase in time to value can be achieved in four steps.

In the first step, a data firm helps its client define or refine the business problem, helping the client construct the right questions to ask in order to solve the problem. Once the right questions are in place, the data specialists are often really good at helping clients with step two, knowing where to find the right data in order to get the best answers. Belessent notes that aggregators often have an opportunity to get the right data at the right price for clients, as well.

Step three is the most important: applying advanced analytics capabilities and designing the right framework for performing those analytics.

This is where eContext is helpful. As a data expert, you have a question that needs an answer as quickly as possible, and you have a series of data sets that contain the right kind of information for analysis. What you don’t have is a month to wait for your data to be pulled from disparate sources and normalized for analysis — clients want answers and insights now.

eContext is a real-time classification engine that helps data aggregators pull text data from any source into a unified taxonomy structure for easy discovery, analysis, and strategic recommendations. eContext offers a deep classification structure — more than 500,000 total categories that reach down 21 tiers — to help you deliver greater relevance and deeper meaning on behalf of your clients.

We work with companies like DataSift that aggregate astronomic volumes of text data from a wide range of sources like social media networks, streams of editorial content, blogs, and forums, and other data sources they have access to. DataSift relies on eContext to quickly provide an infrastructure for all their data, so that they can unify, standardize, and structure their assets into a topic hierarchy framework to enhance overall efficiency of the insights supply chain.

Pulling it all together

eContext can be key in Belissent’s final quadrant of the insights services cycle — delivering better insights. She notes the growing number of firms that are differentiating their services by stressing excellent data capabilities backed up by keen insights.

Consider the competitors in your space who are delivering insights to clients based on the shallow industry-standard three-tiers-deep classification system. Leveraging eContext to classify your data gives you the infrastructure required to ,  help your key staff cull stronger and deeper insights, faster.   

It’s a great moment to be a data expert. Your services have never been more in demand, and there’s a wide and untapped market that’s just waking up to the fact that data will drive them forward. If you can add value by giving them answers along with insight faster than your competitor, you’re in a good position to lead the pack. Step out ahead of your competition with better, deeper, richer text classification capabilities from eContext.

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For the taxonomy editors at eContext, categorical organization is all we think about all day, every day. We look for new ways to approach taxonomy and we even find new ways to talk about it. In fact, during interviews, an employee used to pose an unusual question to job candidates: “How do you organize your spice rack?”

 

This simple question worked so well because it was completely unexpected and showed us how good the candidate could be at thinking fast on his or her feet. It’s also the kind of question that people answer honestly, and the answer would say a lot about how well the candidate might do at his or her job here at eContext where we’ve set out to organize, well, everything into a massive taxonomy of social and commercial topics.

 

We got a lot of great answers from candidates who proudly announced their strategy to keep the spice rack organized by size, type, use, and alphabetical order. It’s the kind of organization that’s automatically accessible and intuitive, no matter who’s cooking your kitchen (or shopping in your grocery store, come to think of it.)

 

But we also received well-argued responses that defied our expectations; one candidate grouped his spices according to their frequency-of-use in household favorite recipes. It’s a reminder of how niche-use schemes can have their own value, not to mention how important it is to be cognizant of all the different ways a concept can be classified. Regardless of the approach, a thorough and passionate answer would tell us, “this is a candidate for eContext.”

 

Taxonomy models

 

As we constantly tweak and iterate our taxonomy, we look to other models for inspiration. One taxonomy we love is the Luma Institute’s Taxonomy of Innovation. If you’ve ever wanted a roadmap for bringing an idea to life, all you’ll need to do is follow the steps mapped out in this wonderful interactive taxonomy. Guiding you through the three main stages of innovation —  looking, understanding, and making  —   Luma’s taxonomy helps you explore and understand each step of the process, drilling all the way down to giving you a format to follow for a brainstorming meeting and telling you how many seconds to allow meeting participants to come up with answers.

 

Luma’s taxonomy is a great way for us to help explain to those outside of our taxonomy-loving bubble what we do. It’s sometimes difficult for everyone to see how important it is to be able to organize data into a deep hierarchy on a web taxonomy, but we find almost everybody has had an idea at one point or another for a new product, and they can quickly relate to the Luma taxonomy, with its deep detail, and see the value it brings to a business process by providing a framework for helping ideas come to life.

 

Taxonomy and your business

 

If you have a business that relies on anything digital  —  a website, digital campaigns, or a social media presence, for example — then taxonomy can help you innovate. You can organize any kind of information about your business or your performance into a taxonomy so that you can see the progression of information and how it affects your business.

 

In our industry, the starting point is the basic taxonomy set by the Interactive Advertising Bureau (IAB). This basic taxonomy covers two tiers and most major commerce categories. However, two tiers is a shallow pool when you consider how much detail you need to get to know your customers better through the data you pull.

 

eContext is a deep taxonomy, providing a richer way to dive deep into your data by pulling it into a taxonomy with more than 450,000 nodes. With  up to 21 tiers of specificity by which you can understand your data, you can always zoom in or out to pull the insights you need at any given time. That flexibility will help you make better decisions about how to present information on your site or how to reach out to potential customers in your digital and social campaigns.

 

Weather you’re thinking about how to arrange your spice rack, launch the next great product innovation, or structure your web presence, taxonomy can help. And we’re here to help you build a better, deeper taxonomy.

 

Now, where did we put the cayenne?

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Recently, we talked a bit about the concept of topic intelligence: the ability to identify which specific subjects are mentioned within your text data. Aside from improved tagging and retrieval, topic intelligence can teach you about the behavior of consumers who interact with your content.

Usually in our examples, the user behaviors we discuss are positive ones: engagements, conversations, those actions that publishers and retailers seek to encourage. If you’re a purveyor of consumer content, keen awareness of that content’s many subject matters can help you figure out which topics resonate with your audience.

But what about those behaviors that organizations (and many users) find undesirable? Can you arm yourself against trolling, abuse — any of those actions which you may hope to discourage — by understanding, on a topic-by-topic basis, where those behaviors tend to occur?

This week, a handful of UK journalists grappled with just that question. Unusually for a news outlet of its kind, the Guardian turned the flashlight on itself — specifically, on the user comment threads that appear beneath most of its articles — as part of a series entitled “The Web We Want”. Comment sections in general are notorious for negative user interaction; the goal of the Guardian’s article was to spot significant trends that could identify when and where users might post abusive comments.

We decided to treat the 70m comments that have been left on the Guardian — and in particular the comments that have been blocked by our moderators — as a huge data set to explored rather than a problem to be brushed under the carpet.

The Research

The Guardian looked at comments that were labeled abusive and took note of the articles those comments appeared beneath. Researchers classified each article according to two different features:

  • The gender (and other demographic characteristics) of the article’s author
  • The article’s subject matter

The gender flag, it should be noted, was particularly striking. According to the investigation, “articles written by women got more blocked (ie abusive or disruptive) comments across almost all sections.” Unsurprisingly, articles written by straight, white males received the lowest percentage of blocked comments.

The examination of subject matter yielded significant results as well — and it is in this line of inquiry that we see the benefits of topic intelligence:

We also found that some subjects attracted more abusive or disruptive comments than others. Conversations about crosswords, cricket, horse racing and jazz were respectful; discussions about the Israel/Palestine conflict were not. Articles about feminism attracted very high levels of blocked comments. And so did rape.

The message is clear, if already intuitive: articles about divisive or turbulent subjects are more likely to draw abusive user comments.

It’s worth noting that the Guardian tags its articles with a fairly high degree of specificity — instead of simply relying on broad, traditional categories like sports and fashion (though those distinctions exist as well), the articles are tagged more granularly, with niche topics such as crosswords and horse racing. Even a sensitive subject like rape is tagged, because developing an awareness of subject matters means recognizing any topic, regardless of whether or not it’s pleasant to talk about. Because the Guardian organizes its content both comprehensively and with specificity, its researchers were able to develop a clearer understanding of the topics that are typically met with abusive comments.

The Response

So what do you do with this kind of intel? For one thing, publishers who can predict abuse on a topic-by-topic level are better equipped to moderate user behavior more efficiently, or even learn when to turn off commenting altogether:

The Guardian has already taken the decision to cut down the number of places where comments are open on stories relating to a few particularly contentious subjects, such as migration and race. This allows moderators to keep a closer watch on conversations that we know are more likely to attract abuse.

Beyond moderators, the Guardian’s journalists can also benefit from an awareness of troll-magnet topics. Style, tone, rhetoric — authors make innumerable decisions regarding how best to communicate with their audiences, and even if it doesn’t affect their overall approach to telling  a story, knowing which subjects tend to draw abusive comments can inform that decision making with an eye towards clear and uncompromised communication. Even marketing and PR teams, working to put this content in front of new readers, can be more effective at their jobs with these kind of findings. After all, the last thing you want is for potential users to associate your content that’s “crude, bigoted, or just vile.”

Going Deeper with Topic Intelligence

Crucially, the report included links to a sibling article that provided some details on the researchers’ methodology. The comment section of this article (fittingly) contained constructive advice from readers on how this research could be strengthened.

For what it’s worth, we at eContext have the strongly-held belief that increased granularity always leads to increased clarity. Perhaps in subsequent investigations, the Guardian can go a little deeper into their topics to try and uncover even more helpful correlations between subject matter and negative user interactions. In addition, organizing tags to a hierarchical structure could foster awareness at different tiers of specificity: Which topics within “Technology” are most likely to draw abusive comments? In articles dealing with the Israel/Palestine conflict, are there certain co-occurring subjects that reliably inhibit unwanted behaviors? These kinds of questions and others require an even more exhaustive tagging system, one in which specific tags are nested under broader categories for increased flexibility and coherence.

Finally, it would certainly be useful to classify the abusive interactions themselves. Which topics tend to appear in blocked or deleted comments? Do those topics align with the referring articles’ content or do they tend to differ substantially compared to the comments deemed appropriate? As long as you have the means to structure and learn from this kind of information, we firmly believe that the more behavioral data you can attain, the more equipped you’ll be to make constructive decisions.

On the whole, we found the Guardian’s efforts to be a terrific example of an organization using topic intelligence to foster a more positive experience for their audience. We hope other outlets will follow this example and classify their inventory to gain a more comprehensive understanding of content.  

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In a house with six kids, spring cleaning is a big deal. By the end of March, there can be dozens of pairs of shoes and boots clogging the mud room, not to mention a sea of ski parkas, winter coats, hats, scarves, and countless orphaned mittens and gloves. Each bedroom is equally littered with the spoils of winter, and everyone is eager for the “out with the old, in with the new” purge that spring cleaning promises.

One year, after a particularly harsh winter season, the powers that be in the household (the parents) went a bit nuts trying to clean it all and decided, instead, to organize a Great Purge. Everyone in the house was instructed to pull everything into a group of piles in their room: clothes that needed to go to storage, clothes they’d outgrown, clothes and boots for Goodwill, items that could be hand-me-downs, things that needed to be washed…

You get the picture. Once all the piles were arranged, boxes and laundry baskets were brought around to each room before anyone could forget which pile was which. Each kid placed their items into the correct box or laundry basket, and the boxes were carried off by the bigger kids.

As all the boxes were put neatly away in the basement, everyone was able to sweep away the winter dust and to make room for their spring wardrobe.

Using data tags to clean house

Does your data look like our house full of six messy kids? Admit it, you’ve got data strewn across every office silo, and a data mudroom so chock full of stray bits of text, you can no longer see the floor. It’s time to organize – with data tags.

Imagine being able to take all that stray data, throw it into a big pile, put it through a filter and have it come out on the other side, neatly arranged into compartments that make sense to you and to your business.

eContext is a text analytics solution that can take text data from any source — clickstream, social, customer profiles, you name it — and normalize it in real time into a topic hierarchy that you can use. Tag your data so that you can put it in the right bin to be analyzed, recycled, or thrown away, and suddenly you’ve got a very organized space to work with.

There’s another reason eContext is so good for your data purge. With some category structures, your data gets organized into very shallow categories, so you might wind up with the entire family’s boots in one box, and all the ski parkas in another. eContext extends to 21 tiers, so you can organize your data into very specific nodes. Instead of a box full of boots, you wind up with a series of specific boxes in your data basement, very neatly labeled, “boys ski boots”, “girls rain boots”, “riding boots”, “snow boots”, and “winter hiking boots”.

Ready for a new season?

It was always our parents’ dream that once the house was in order, we’d take the opportunity to “keep everything in its place from now on.” Of course, this never really happens when six kids are running around, but as a grown-up with tons of data charging through the door every day, you have the opportunity to keep your data in check constantly.

Because it can filter and tag your data in real time, you can use eContext continually to keep your data spring-cleaning-fresh. As much data as you have, from any source, in real time. Organized into 21 categories, and more than 450,000 nodes.

Now get out that broom. It’s time for a good data sweep.

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We continue to hear more about personalization for social media channels. This past week, the Instagram blog had a very simple announcement: “To improve your experience, your feed will soon be ordered to show the moments we believe you will care about the most.”

There’s a big promise in that simple announcement. Instagram is letting us know that it plans to invest more in getting to know what users like and dislike, and place a higher priority on understanding how to deliver a more relevant experience.

The Instagram blog also notes, “you may be surprised to learn that people miss on average 70 percent of their feeds.” Instagram knows that the social universe is getting ever more crowded, and they have to do a better job of grabbing and holding our attention. eConsultancy reports that Instagram users spend 21 minutes a day on the app. That’s a lot of time, but if we assume that a typical Instagrammer breaks up her 21 minutes into smaller intervals throughout the day, and that she spends those intervals paging quickly through her friends’ posts, checking her own for likes and comments, and taking in the occasional ad, it’s clear how crowded those 21 minutes really are. Bore her and she’ll just page through faster, missing even more of what she logged on to see.

 

Better social media personalization

 

To improve the experience, Instagram told users, they will now re-order Instagram feeds so users can “see the moments we believe you will care about the most.” We’ll infer that Instagram is also tweaking their feed to deliver the ads with which users are most likely to engage.

And that’s OK. Personalization for social media should be laser-focused on delivering to us what we want. If our social media channels know us so well that they can know who our favorite musician is and show us a video from that concert we wanted to see, as Instagram promises, that’s just as good as your best friend writing to tell you, “did you see this on YouTube last night?” And if Instagram can get just as good with delivering ads, it’s the same as your friend writing to tell you, “tickets go on sale tomorrow for the show, you in?”

 

Getting to that personal level

 

The trick is how to get there. After all, in real life and in social media, it takes a while to build a friendship, and there’s a lot of trust and sharing that has to go on. But it’s through that dual process of sharing and extrapolation that you can get to the heart of the relationship.

There are a lot of ways to parse data in order to get to know a user better. Smart players in social are using a wide variety of cues to make better decisions about what to serve up to users. From user profiles, listening tools, and basic clickstream data to more sophisticated approaches based on natural language processing and machine learning, social sites are able to draw a more accurate picture of who wants what.

eContext enhances that process in a few ways. First, we can help you pull all of your data into a single data set in real time. That way, you can see the big picture from all your data with very little effort on your part.  We also map all of that data to a deep taxonomy so that you can drill through tiers to get better insights on user interest and make smarter predictions about user intent. Our taxonomy has been created and curated by real people who understand the difference between a reference to jaguars at the zoo and Jaguars on the car lot. We deliver 21 tiers of categories, with 450,000 nodes to help you deliver the kind of personalization experience that keeps visitors engaged. Whether you’re a social site or a publisher looking to deliver better content and more relevant ads, or you’re researcher trying to deliver more relevance, we can help you pull and use data.

Why do we do it? We want our social feed to be more relevant, too.

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When you work on a product or service that’s primarily aimed at businesses, it’s easy to get accustomed to the well-traveled language of B2B.

eContext’s text classification, we’re used to saying, delivers insights. It empowers organizations to expedite their initiatives and adds value to big data by mapping assets to a hierarchical structure.

To be clear, all of these things are true. But a glut of buzzword-laden value statements–and let’s be honest, some have more meaning than others–can sometimes de-emphasize what makes an offering truly necessary or unique.

So this week, we decided to refresh our appreciation for eContext by looking at it from a different perspective. We asked a few staff members around the office: what if eContext were actually a consumer product? What if, instead of enriching data for large businesses, you were able to take advantage of topic classification in your day to day life?

The responses were great–a few people envisioned eContext as a kind of mobile app, while others wished for a browser extension or plugin to automatically classify content.

All-in-all, it was a fun exercise that reminded us how helpful it can be to have access to topic classification on a day to day basis.

Check out some of our favorite responses below.

 

Managing social media with better text classification

 

“I’m sick of apps, but what I’m even more sick of is social media.  I’ve deleted or abandoned most of my accounts, aside from Facebook, and that’s mostly to keep in touch with out-of-town friends and relatives, and to find out about local events.  I know there are ways to block a certain person’s content, but sometimes I don’t mind seeing cute pics of their new puppy, I just don’t wish to read their 82nd political post of the day.  Anecdotally, I’ve heard others complain that social media makes them “feel like crap” because it makes people’s lives look so much better than theirs.  For example, if someone just went through a break-up, they might not want to read about their college friend’s awesome spouse.  It would be useful to have an app that could filter out posts with certain keywords or topics, rather than filtering out people completely, and the app could include posts from various social networking sites, so there would be no need to log in to five of them.” — Allison, Taxonomist

 

Keeping recommendations in order

 

“I wish I had a better way to keep track of all the recommendations my friends and family pass along. TV shows, articles, book suggestions, that kind of thing. Usually, I try to make notes for myself on my phone or scrap paper, but it would be cool to have an app that could sort all that content by subject matter and keep it organized for when I have the time. Say I was between books and felt like reading a western, I could go into my app and see if my friends had given me any corresponding recommendations. Basically, I wish I had an eContext app to keep me more organized and account for my forgetfulness.” — Patrick, Administrative

 

Better networking  

 

“I’m always looking for ways to connect. I have a small business and I rely on networking for most of the work that I get. I’d love to be able to pull my Twitter feed and find out what people are saying about manufacturing or technology, two topics I work with frequently, so I could connect with them on a more effective level. Right now, it’s difficult to do this efficiently on Twitter, where you can’t get much deeper than a hashtag. I’d be interested to find ways to pull all of my friends who just happen to be interested in a topic like manufacturing and think of new ways to connect with them.

It’s also interesting to me to know the tangential things that people are interested in and finding unlikely associations. It’s simple enough to think of the obvious – a person who works at a manufacturing firm is also interested in manufacturing technology. I think it’s more fun to find unlikely associations, or things you wouldn’t necessarily think of, and eContext’s text classificaiton is a great way to visualize data and look for patterns that emerge. I would use this kind of information to find off-the-beaten path ways to reach out to potential new customers. If I can find marketing managers at manufacturing firms I suppose I could reach out to them with a message about marketing and manufacturing. But if I can find all the marketing managers at manufacturing firms who like the Cleveland Indians, I have a much better chance at getting their attention if I can wedge my Cleveland connection (and love of the underdog team) into my introduction. It’s very effective, but it takes time to do that kind of research. eContext could make it easier.

Go Tribe.” — Miriam, Marketing

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Millenials are showing greater interest in voting, and have a shot at changing the political landscape. Heightened interest means greater online traffic, and more opportunity for publishers to court and capture new readers and fans.
The Pew report shows, on the one hand, how much division there is in the types of sources that Americans turn to for news and information, but it also reveals how important social media, news websites, and apps are to the coveted younger audience. In the graph below, almost 50 percent of respondents aged 18 – 29 report that the most helpful news they get about the election comes from social media or news websites and apps.

PJ_2016.02.04_election-news_0-02

Capturing and keeping Millennials

Publishers are under a great deal of pressure to keep readers engaged and moving through their site, but often they’re using clunky, third-party tools or widgets to what a reader should read next, or worse, they’re asking blog contributors or lower-level data entry employees to manually select categories and keywords for this purpose.

You’ve got a very short time to entice a reader to stay on your site, and the key to keeping them there is delivering relevant content options. If a Millennial winds up on your site trying to find out more about Hillary Clinton’s economic platform, and the related links on your site have nothing at all to do with Hillary, or economic policy, or even politics, you’re not going to get her to stay.

Consider this set of recommendations from the bottom of a Forbes.com post titled Hillary Clinton Rolls out her Economic Platform which, as of February 16th, promoted three recommended articles on the Forbes site, one on Oracle’s cloud service, a photo essay of the richest person in each state, and another piece on how to exceed customer expectations. Nothing on economics or politics.

Forbes’ own content recommendations don’t quite strike the right note, either. The site’s “see also” list is as follows, with the most relevant topic at the bottom of a list of hit and miss matches:

    • Best Investment Plans
    • Economic Forecasts
    • Oil Gas INvestments
    • Most Profitable Business
    • Future Gold Price
    • Money Management Tips
    • Senator Hillary Clinton
  • Hillary Clinton Biography

At the bottom of the page is a series of brightly colored, but even less relevant ads delivered to the Millennial who searched for “Hillary Clinton’s Platform” – do you think any of these items are going to keep our politically-motivated visitor clicking?

    • Ever Googled yourself? Do a Deep Search instead
    • Anxiety? Hemp Extract, Now Legal in IL
    • Forget Pensions! 11 Rules for Getting Rich After 50
    • Skip the Mattress Store – 3 Ways You’re Getting Screwed Buying Retail
    • 2 Dudes on Shark Tank Reveal A Trillion Dollar Idea
    • 10 Online Dating Sites that Really Work
    • A Brilliant Way to Pay off Your Mortgage (It’s Genius!)
  • Men: 5 foods That Kill Testosterone and Cause Belly Fat

Seems like the word “economic” may have triggered a shallow response and delivered a series of ads that are way out of the scope of what the searcher was looking for.

Building relevance into your site

Forbes is missing opportunities for added page views. Even if we have no additional information, we know that our Millennial is hoping to learn about Hillary’s platform, and while there is plenty of information available on the Forbes site about the election and Clinton’s views, there’s very little for the visitor to discover from this page, and only one suggested topic and not a single ad has to do with the reader’s original query. Why should our impatient twenty-something dig through Forbes when she can just hit “back”, search Google or Bing, and get the info she’s looking for on someone else’s web property?

It’s another example where text classification can be a huge help. Using eContext, Forbes could classify both user searches as well as site content to a single hierarchy of topics — topics such as “Hillary Clinton”, “Public Policy”, or “Economic Sciences”. By connecting the topics a user is searching for with the content in its inventory, Forbes can deliver truly relevant articles and more intelligently place sponsored content. Each page the visitor reads that delivers more relevant content helps the reader build more confidence in Forbes as a destination, and makes her more likely to click on sponsored content and/or return to the Forbes site in the future.

eContext’s taxonomy facilitates interaction on your site by helping you deliver relevant topics. There are more than 450,000 categories, reaching down 21 tiers to help you pull out the topics that are most relevant to your search now.

A recent Time article published by Jared Kleinert and Stacey Ferreira, How 2016 Candidates Can Win Over Millennials, strongly encourages candidates to use ad targeting platforms that will appeal to Millennials. Publishers who can deliver relevance in content and ad delivery will please readers, but their sites will also be a more appealing place for campaign ad spend. This election season, digital ad spending will represent a 5,000 percent increase over the 2008 election and is estimated to reach $1 billion, according to Wired, so making efforts toward more relevant results has the potential to deliver big numbers, particularly if you cater to Millennials.

This election season promises to deliver a great deal of drama, debate, and interest — think of what you can gain by using eContext to help your site deliver better options to readers.

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Your customers are trying

As a retailer, it can be a struggle sometimes to bridge the gap between the items you sell and the customers who might buy them. So often you’re stuck in the middle with a product that a manufacturer has shipped to you along with the appropriate SKU and possibly a photo and a short description, and you have to figure out how to market that product so that your customers will find it on their first try when they get to your website.

One of the problems you have is that your customers aren’t looking up a formal SKU number — they’re going to your search box with the vocabulary they’re accustomed to using. If a customer arrives on your site and enters the keyword “strappy Choos”, will your search engine–trained to look for certain words from product descriptions–return any helpful results?. Sure, you sell plenty of strappy shoes, and you may even carry the Jimmy Choo brand she’s looking for,  but if your search results can’t make the connection, you’ve just given your customer a reason to leave your site.

 

Matching meaning instead of words

If your customer was visiting a retail location, a sales associate would take her right to the Jimmy Choo section, or show her a grouping of equally fun party shoes. But how can you recreate this experience online?

eContext has a solution that’s powered by human thinking. We can take your customer query and map it to our deep taxonomy to help you deliver better search results. We’ve had humans curating our taxonomy so that the terms are accurate and reflect real English language speech. Our classification goes up to 21 tiers deep and features 450,000 categories.  

When a shopper arrives at your site with a search term that’s puzzling to your search function, like “strappy choos”, pass that search term on to us. eContext looks at the search term in real time and returns category suggestions that your site logic can understand. Now you can deliver relevant options for your customer to consider, including “Jimmy Choo Footwear”,  “Heels”, and “Fashion Sandals”. With intelligent classification, what might have been a roadblock that sends your customer to competitor’s site is, instead, an intuitive shopping experience and a new opportunity for a sale.

In addition to real-time search, you can use eContext technology to classify product descriptions and consumer reviews. By applying the same topic classification to all of your interconnected product and consumer data, you’ll be well-equipped to match customer requests with relevant results.

With eContext, you increase your opportunities to sell to customers. How many times do you think you’ve lost a customer due to poor search? People will use search terms that make sense to them and it’s up to you to get to the heart of what they’re asking for and deliver.

 

Additional options with eContext

eContext helps you build more flexibility into your site by connecting you with a deep taxonomy that can roll up or roll down as you need it to. For example, maybe you carry a wide variety of Jimmy Choos, but want to promote the top-selling subcategory of “Jimmy Choo Ivette”. On the other hand, if you don’t carry the Jimmy Choo brand at all, you can move up a few categories and offer results for the more general topic of “Heels”.

eContext also returns scores, confidence measures for fit of a particular document to a category. These scores can be used for ranking. So, if the consumer is searching for something in the sandals category, and the retailer has many product descriptions related to that category, the scores can be used to select the most relevant product descriptions.

Data-savvy retailers can layer in other types of analytics as well, such as integrating relevance scores with click-through or conversion rates to identify the best choices for use in search results.

If you can build more relevance into your site, your end-user will stay longer, and you’ve got a much better chance to covert. If the shoe fits…

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A recent Forrester report notes that by 2019, online retail sales will grow to $480 billion. Already, retail depends on the online experience for almost every stage of the buyer’s journey, whether customers are researching for and purchasing products exclusively online, or using the web to make their in-store purchases. Better web classification for brands will be critical  as the market shifts under the pressures created by increased competition and demand.

Moving away from simplified product classification

Most of the taxonomy and retail classification products that currently serve the industry provide underwhelming results. A taxonomy strategy that’s shallow and manufacturer-focused makes perfect sense on the retailer’s back-end system, but it will likely deliver results that don’t make a lot of sense to shoppers.

To achieve better retail classification for brands and products, you need to be able to understand more about your customers. What typically gets them to your site in the first place? What kind of products are they looking for? What compels them to stay on your site to shop, and ultimately buy?

The good news is, you have the answers to these questions in your customer data. The bad news: Your data is a mash-up of customer profiles, tracked data, social intelligence, and some third-party information, too. eContext pulls all of that seemingly disparate data through its filter, tags it, and delivers a clean picture of your data, mapped to categories in 21 highly intricate tiers.

Because we’re experts at classifying data from so many different types of sources, we’ve become very good at identifying nuances in language. Over the past 13 years we’ve developed more than 55 million language elements that guide the intelligence behind our classification system. This enables us to exceed by 1000 times the number of tiers offered by the industry-standard IAB list.

A deep taxonomy for deeper engagement

By using the eContext framework, you can unify content on your site, and bring products together in ways that make sense for your customers. You’ll be able to deliver the results they want faster and with a more reliable level of accuracy, and you’ll be able to make better recommendations to them so that they’ll stay on your site to shop and make purchases.

As the market gets more crowded, and retailers of all shapes and sizes start finding ways to capture shoppers, you’ll need the best tools available to stay competitive. eContext is a key tool that will help you see the big picture while delivering the page-level results your customers are searching for.

Get a personalized demo or watch our video to learn more about how it works.

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If you sit on huge amounts of data and text, a text classification for publishers can provide new ways to make more accurate suggestions for readers and better pairings of content with promotions and ads. Text classification can also help publishers repurpose and repackage content so that they’re always getting as much as possible out of their most valuable asset.

Being able to better classify content may also be the key to winning the content game in the long term.  

A tight marketplace for publishers

The Pew Research Center’s State of the News Media 2015 report shows that only five companies generated 61 percent of total domestic digital ad revenue in 2014. Google, Facebook, Microsoft, Yahoo and AOL took the lion’s share of revenue. The report also showed that revenues and spending are up for publishers, and indicated that the market is getting more crowded and competitive each year.

Publishers who want a slice of the remaining pie need to be smart and aggressive. They must find ways to deliver quality content in ever more engaging ways while pairing content with the right kind of advertising for a better all-around experience.

Publishers have the text and data they need to analyze and optimize their efforts, but it can be a challenge to pull all that data together to make sense of it and really use it to its highest advantage.

A vertical classification system for publishers

There are a number of products and services available to publishers to help them organize their content or pull insights from their social channels. As good as these insights can be, the publisher is still left with the same problem: Data and text in a wide range of formats interspersed throughout editorial, marketing, and business systems with no way to connect them.

eContext makes the connection. We help publishers pull that data through a single filter, analyze the data, and categorize all of it under a unified classification system that goes 1000 times deeper than the industry-standard IAB system to 21 tiers, and in 25 top categories. This can be especially helpful to publishers who cover a wide range of topics across a number of verticals.

With a unified classification system, editors and digital marketers are all viewing the property through a single lens. Editors can make amazingly better on-page recommendations to keep readers on the site, and the digital team can benefit from deeper classification to increase engagement and clicks.

There will always be giants at the table taking big pieces of the pie for themselves, but they had better watch out — publishers with sharp elbows are bellying up to the table to take their fare share. Armed with smarter tools like eContext, they now have a good opportunity.

 

Watch a video to find out more or schedule a demo with us.

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