Mobile Shopping: Growing Fast, If Unevenly

exelate mobile shopping interests

Mobile shopping has continued to grow since the introduction of Smart Phones, and took a huge leap forward with the introduction of the tablet. In 2012, 11% of all online shopping was done on mobile devices. In 2013, this is expected to reach 15%. By 2016, 1 in 4 online sales will be completed on a mobile device. eMarketer reported just yesterday that US mobile payments are on track to top $1 billion in 2013.

We took a look at a range of shopping segments for June, in order to see how much interest was generated by users on mobile devices, vs. desktop computers. From shoes to food to fashion, mobile shopping continues to grow, but unevenly across segments.

Shoes were in the top plot, with 24% of shopping, including browsing and purchasing, coming from mobile users. This is followed closely by women’s fashion, comfortably beating men’s fashion in mobile browsing. This is despite the fact that men are more likely to shop using mobile devices overall.

PC video games came in at last place. With most video games immediately available for direct download, it makes sense we would see this. While you can watch a trailer or read the news about a game on your phone, you typically need to download it to a PC in order to play it.

In today’s digital world, it’s critical to focus on a mobile strategy, and to be aware of where your company fits within the larger retail ecosystem. Be prepared to harness the power of mobile!

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A Little Bit Country, a LOT Rock ‘n Roll: American Musical Interest

exelate data snax 7.5.13“R-O-C-K in the USA” seems to be alive and well! This week, our data team looked at different musical interests between males and females as well as across different age groups. Between country western, hip hop, jazz, and rock, rock took the cake as the most popular genre among all genders and ages. Some other insights:

  • Country western seems to be gaining popularity – more so for women than men, almost edging out rock as the top musical interest for women.
  • Hip hop and rap are most popular among the young, with a steady downward line in interest as age increases. However, it seems that some folks over 50 are still enjoying it!
  • Apparently, jazz is a genre for a select few – interest for both genders plummets and all age groups show a relatively equal amount of disinterest for it.

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Summer Escapes- Where Do People Take Vacations in the Summer?

eXelate- Summer 2013 Escapes

With summer here and the weather warm, people are planning summer vacations.

Topping off the most sought after location for May vacations was Florida. Whether it’s Disney World or Miami Beach, Americans from all over the country were interested in taking a trip to the Sunshine State. Number 2 proved that surf and sun were the operative vacation interests in America, with California coming in as the second most sought after state. Hawaii, in 5th, extended the palm tree vacations. New York and Texas, in 3rd and 4th respectively, were also important destinations for Americans.

We also took a look at the other side of the coin. Which states had people who were looking at travel the most? The results were interesting. Topping our list was Washington state. Perhaps people wanting to escape those May showers. Washington proved to be a bit anomalous though, as the next five states were all from the South. In the end, humidity might be the greatest vacation motivator of all!

  • People are always on the lookout for some fun in the sun, with 1st and 2nd place going to FL and CA, respectively.
  • Washington state displayed the most interest in travel, but the next 6 spots were all in the South.
  • The larger and more popular a state is, the more likely its residents will look to fly within it. In fact, the top 5 most popular travel destination states all look for travel plans within their own state, before looking outside of it!

Summer Interests: American Grillers


Happy First Day of Summer! To celebrate, we decided to take a look at one of our own favorite outdoor activities – the quintessential American BBQ.

Barbequing, or grilling, is a massively popular form of cooking in America. A full 75% of American households own a grill, and almost half of them grill year round.

We examined a full month’s worth of data in order to find out what BBQers are doing, and it turns out that May featured some intense interest in the Northeast. Not only does the Northeast have the most BBQers in the nation, but they were finally getting the weather to enjoy it. Connecticut, Maryland and Massachusetts led the pack, with the most per capita BBQ interest in the nation. But don’t worry, BBQing is popular nationwide.

It may surprise you that we look for BBQers at all. In fact, we found over 7 MILLION unique users looking for BBQ information or supplies in May alone. So what are you waiting for? Get the grill and beer out. It’s summer!

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U.S. Sports Abroad- European Interest in American Sports

American Sport in EuropeThis week we wanted to take a quick look at the popularity of the “Big 3” American sports in Europe. We examined browsing patterns for May, with an interest in which countries were most focused on news about which sport. We definitely found some interesting patterns.

This sort of snapshot is highly time-dependent. Interest in sports waxes and wanes as sports seasons come and go. These numbers were taken during the MLB and NBA regular seasons, but after the Superbowl, and these two ‘in season’ sports dominate the map.  Germany, which has the largest number of players in the Confederation of European Baseball, dominated baseball interest. This was shared with Spain, where baseball was introduced early by Latin American enthusiasts, and many Eastern European nations.

Basketball news was the winner in large parts of Europe. In fact, had it been included, college basketball was actually more popular than any of the three major sports for a few countries. Of course, we can’t discount Americans living and traveling abroad, trying to keep up with their home team swinging some results!

Surprisingly, despite being in the off-season, NFL news was still being actively read more than other sports in a few countries. We can only hope it shows real interest and not people confused by which “football” they were reading about!

Auto Insights: May’s Top 10 Segments

exelate auto buyers top 10

The Ford Mustang takes the race!

Here’s a snapshot of the top ten auto segments for May in a few of our most popular categories. Cleaning up is Ford, with the most popular segment in both our make and model categories, backed up by sports cars being our most popular body style! Perhaps some of our users are looking to spend some extra cash this summer?

These segments allow you to accurately find your audience across the web, targeting and retargeting users with precisely defined interests. Not only does eXelate maintain highly accurate Smart Data about body styles, makes and models, we create and maintain hundreds of additional segments for auto shopping with millions of unique users. Information about whether they prefer foreign or domestic, new or used, economy or luxury, and more. This is backed by a range of other auto related segments, including auto parts, tires, financing, lease and loan info, insurance seekers and demographics.

If you’re looking for auto shoppers, look to eXelate for the most accurate targeting on the market!

Notes from Brian Morrissey: Data and its Discontents

brian-morrisseyAt Digiday we have this thing we call Buzzword Bingo at events. The idea is that people get a prize by plotting out various buzzwords. I like to have a side bet nowadays of what will get checked off first: “native advertising” or “Big Data.” I don’t have the numbers totally crunched but I’m pretty sure Big Data is in the lead.

This is normal. Big changes – think the cloud – frequently become marketing terms that quickly lose all semblance of meaning. It’s easy to poke fun at them, or even dismiss their importance entirely. That would be a mistake with Big Data. It means something – but that something has been lost by all the marketing that’s overwhelmed it.

I say this because I feel that our ability to collect so much data, crunch it, etc. has sometimes caused us to lose sight of the ultimate goal. Take publishing. In my role as editor, data is incredibly important. I look at data from Google Analytics, Chartbeat and sharing services in order to determine answers to a few simple questions: 1) Is what we’re doing working? 2) What should we do? Now this data is an input. It’s just that. Our audience development manager, who is very young, mentioned to me that Upworthy uses about 200 versions of a headline to see which one will work. That’s OK to me, but it’s also a bit of a shortcut. In the end, I can’t make editorial decisions based purely on the numbers. All our stories would be Top 15 Worst Brand Screwups in Social Media. Our goals of building a strong brand and a loyal audience that respects us for honest coverage of important issues would be compromised. There’s not an algorithm for that. It’s a sensibility.

Data is an input that will help. When it comes to digital media, data is about two things from my point of view.

Data allows companies to better serve their customers. This isn’t new – companies have always relied on data. It’s just that now, there’s a lot more of it. The really interesting part about data is when companies improve their services for customers. This is the promise of Big Data to me. I go back to Amazon’s collaborative filtering technology. At the risk of sounding like the old guy my millennial colleagues like to paint me to be, this was a game changer. Suddenly I was able to find related products of interest to me. I knew full well Amazon was tracking my purchases and browsing to do this. And I loved it! Same with Netflix – I love it tracking me. I want it to track me. I need it to track me. I want it to figure out for me what to watch.

Data allows digital media to be more efficient and useful. In this world of data, we should see fewer, better ads. That’s the promise. We operate online leaving a digital bread crumb trail. Nothing is free in life. The implicit tradeoff is that we’ll allow publishers and advertisers to responsibly use this data in order to improve the ads we see to pay for the content and services we use. This is noble, and important – and I’m not saying that because eXelate bought me a lovely lunch. You can feel the “but” coming here, right?

The simple truth is the promise of Big Data in advertising is confusing. There’s an idea on the data side of this business that marketers must speak the language of technologists and not vice versa. We see this all the time in how the many technology companies try to explain what they do. Khurrum (Malik, CMO eXelate) and I were talking the other day, and he brought up the concept of the tyranny of knowledge. It fits perfectly for one of the biggest challenges of this industry: how to simply explain what it does. Too often there’s an assumption on the part of the data-crunching techies that everyone understands this – or should. It leads to people on the marketing side not asking simple questions for fear of looking foolish. But these are the questions that need to be asked: How does what you do help me serve my customers better? How can it help make advertising better and more efficient?

That brings me to where I see this idea of Big Data going. And it’s away. It’s like how social media is fading into the ether. “Social” is part of everything. I’d coopt something Charlene Li said years ago about social: It’s like air. So too is data. It’s everywhere. It’s not a feature, it’s the environment. Once we get over this idea that data is something new and exotic, to be mined maniacally, collected and protected zealously, we can get back to what I mentioned at the outset: How can we use these raw data inputs to help people? How can data be used to tell better stories? How can data improve services and even create entirely new ones?

To answer these questions, it is necessary to move a step further from Big Data – it’s time for quality over quantity.

Brian Morrissey is the Editor in Chief of Digiday. Follow him on Twitter @bmorrissey.

The Lyons Den: How Do You Measure Data Accuracy?

kevin lyonsThis week, eXelate unveiled the second white paper in our Smart Data series, accurate data is smart data. We believe that Big Data has yet to fulfill its promise of providing a clear and consistent business advantage. To address this, we argue that the industry needs to evolve from Big Data to Smart Data – data that drives business value because it is accurate, actionable, and agile. The accuracy white paper answers why accuracy is important, how to gauge it, and finally, what it takes to implement data accuracy.

exelate smart data

Which brings us to today’s topic, which builds on the white paper: How do you measure accuracy?

In measuring accuracy, it seems to me that many confuse accuracy and precision. Some, for example, might argue that a consensus approach which polls data providers is the best way to judge data accuracy. This approach essentially claims that attributes with the highest consensus across data providers is the most accurate. We categorically reject this simplistic view as it equates agreement – or precision – with accuracy. In fact, checking multiple data sources against one another may create a kind of confirmation bias (the tendency for people to believe data that supports what they already believe to be true).

This can happen when multiple vendors have the same technique to collect data. Take income data, for example. If several data vendors are supplying the mean income for a zip code to individual users, each will agree for a given household, but each will be wrong for most of the households. And, interestingly, if five data vendors applied the zip code mean to a specific user and one supplied the actual income to the same user, the actual income would be discounted as inaccurate. Serial correlation in data streams is often misinterpreted as accuracy. That is, everyone agreeing doesn’t necessarily make it right; it may just be that many data sources are wrong for the same reason – and that is why the consensus approach breaks down. Precision is not accuracy.

We therefore believe that online data must be validated with gold-standard, independent third party sources, and that these sources must contain registered (user-level) audience demography. Validating eXelate data against third party sources such as comScore and Nielsen allows us to verify that our data achieves the greatest possible balance of scale and accuracy, without degrading our data by including overly loose criteria.

There are a couple of very straightforward ways to validate the accuracy of data against a gold standard. For binary (either/or) outcomes, a confusion matrix is probably the most common approach. Let’s look at the simple case of gender. The below chart represents a simplified confusion matrix which allows us to judge the accuracy of our data:


The above chart reads as follows.  The rows represent what eXelate believes about a user. The columns are the “gold standard” against which we are being evaluated. So, from the perspective of correctly identifying males, there are four potential outcomes:

  • Accurate (male) – technically known as “true positive” – means that both eXelate and the “gold standard” knows the user to be male; or, we got it right.
  • Accurate (female) –  or “true negative” – means that both eXelate and the “gold standard” knows the user to be female,  so again we got it right (it’s a “true negative” because from the perspective of identifying males, we’re technically agreeing that this user is not male).
  • Inaccurate (actually male) – or “false negative” – means that eXelate believes the user to be female, but they are actually male; or, we identified this user incorrectly.
  • Inaccurate (actually female) – or “false positive” – means that eXelate believes the user to be male, but they are actually female; wrong again.

In the above, accuracy is defined as,


So, if you saw the following results:


your accuracy would be:


meaning that, overall, you were right 81% of the time.

To underscore the fact that precision is not equal to accuracy, even in technical terms, we can note that precision for males is defined as:


meaning that if you showed an ad to users that you thought were males, you would be on target  83% of the time.

These equations, as well as something called recall (of males, how many did we reach?), are KPIs eXelate employs to continuously evaluate and improve our data.

So, to summarize, accuracy matters!  Everyone in our business needs to understand what it is and what it is not. Accuracy needs to be calculated using accepted methods against gold standards. And those that fail to give it the attention it deserves do so at their own risk!

We’ll have much more to say on Smart Data and I encourage you to read our Smart Data series of white papers and continue to follow us @eXelate.

Mobile Browsing Interests of Men & Women

The future is mobile. Phones and tablets are becoming larger parts of our online activity. Our lives are filled with multiple browsing devices, from tablets and phones to traditional computers. Mobile devices reflect some of our most idle browsing, reflecting pleasure rather than work. We decided to compare mobile browsing across iOS and Android platforms for men and women.

exelate men women mobile browsing

Men and women have distinct browsing behavior, as you can from the segments they find themselves in. Some activities are common between men and women. Entertainment, technology, shopping and reading the news are all shared activities. On the other hand, there are some distinct differences. Websites relating to parenting, travel, health and food are all more common sites for women than men, while men show more interest in games, technology and finance.

Of course, just because we don’t see someone fitting the Finance or Food & Wine segments on a mobile device does not mean they aren’t interested! We are only capturing a part of that user’s browsing. That is why we are so excited about our new partnership with Drawbridge. Drawbridge increases our ability to connect our mobile and desktop users, expanding the range of platforms for a user we can collect data from, and subsequently allowing people to see relevant ads across multiple platforms. We may never see a user visit a parenting website on their desktop, but through cross-platform connections, we can make sure a user see ads to catch their interests across their digital space. This increases the accuracy, actionability and agility of our data; the core attributes of eXelate Smart Data.

The eXelate Team Helps Foster the Next Generation of Data Scientists

On Tuesday, the Data Science and Technical Operations groups at eXelate participated in our New York City community when members of the teams visited 6th grade math classes at MS 54 (Booker T Washington Middle School) to discuss how math is shaping our everyday world.

analytics team math school

eXelate’s Analytics Team (Sean Cook, Matthew Fornari, Tingting Lin, Kevin Lyons, and Patrick McCann)

The team started out by explaining what Data Scientists do at eXelate and how exciting their jobs are. Some case studies of the type of analyses the team conducts were presented, including a demonstration of how what consumers see on the internet (both the ads and content) is determined, in real-time, by advanced mathematical algorithms. The team even surveyed the kids ahead of time and built some statistical models that, in real time, successfully predicted (to the relief of the fingers-crossed analysts) the favorite movies of the students and the things they most like to do after school.

The presentation was concluded by noting that no matter what discouragement the students may endure, each of them can learn and apply math to their careers regardless of their background or appearance – one of eXelate’s core values. It was a great experience for the presenters and the students were very engaged, even dubbing the presentation as “cool” – a big win for us!

For what it’s worth, eXelate would like to make a call out to all Data Scientists out there: Get involved! Offer to help out at a school! Who knows, you might just help to change a kid’s life, all while having a lot of fun and fostering the next great generation of Data Scientists.