By Tobias Peggs
We’re delighted to announce that OneRiot has been acquired by Walmart.
The OneRiot team will now be joining @Walmartlabs - Walmart’s hub for the creation of new technologies and business models integrating social, mobile and retail for the next-generation of e-commerce. The official announcement is here:
by Tobias Peggs
At OneRiot, we’ve built a killer “Social Targeting Engine” that we use for mobile ad campaigns. You can watch a rough video demo here. And now, building on that foundation, we’ve launched a new “Social-Geo Census Database” to help deliver more mobile content to target audiences in specific geo-locations. You can watch a (pretty rough!) video demo here.
Mobile marketers have long used geo-targeting to reach users with improved performance over non-targeted campaigns. But OneRiot offers brand advertisers many additional levels of sophistication and performance – with the ability to target a mobile audience based on social interests and demographics within any geo-location.
For example, P.F. Chang’s is working with OneRiot to target young Business Professionals in Atlanta and Phoenix, socially interested in Dining and Entertainment. The campaign promotes P.F. Chang’s “Happy Hours” from 3PM–6PM every day, using rich media creative that features a scrolling image gallery of the food and drink available in the bistro. The ad unit, created in partnership with our friends at Celtra, also includes a store locator and three pre-populated Tweets that users can choose to share with their friends.
OneRiot’s social-geo targeting technology utilizes advanced machine learning and natural language processing techniques to determine mobile audience interests and demographics in particular geo-locations, based on publically-available social media activity data. An ideal target for the P.F. Chang’s campaign might include a specific geo-location in Atlanta where we see lots of mobile users posting business-related status updates, following celebrity chefs on Twitter, and see lots of Foursquare check-ins to local restaurants.
Mobile phones are inherently social devices, so it’s only logical that social-targeting is the best way for brand advertisers to reach the right audience on mobile – in any geo-location.
In an earlier test campaign for our Social-Geo Targeting product, concert promoter Live Nation worked with OneRiot to promote the upcoming Foo Fighters tour. The campaign was geo-targeted to specific cities where the rock band was due to play, and socially-targeted to users with an interest in rock music, music magazines, record labels and concerts. CTRs for the campaign were close to 2% - compared to mobile industry norms of around 0.3%.
by Tobias Peggs
At OneRiot, we’ve built a killer social targeting engine. Input a Twitter ID, and the output is two-fold:
1 – User interest map, based on standard IAB categories
2 – User demographics, including age, gender and ethnicity
You can see an example of this output in the screen shot below – this is from an internal tool that exposes our data set. The input was “@johnbattelle” – founder of Federated Media the Web2.0 conference amongst other things - and the output is… Well, you can see that we identify John as being a male, 45 yrs old, living in California, interested in advertising, technology and the fine life of food and drink. That much you would probably expect. But we also pick him out as being interested in photography. Is that right? I sent this screen shot to John check, “Photography is right,” he said. “I take a lot of photos. I am no pro, but I love my D90”. Bingo! (You can watch a rough video demo of the system at work here)
Based on publically available social data that we license via our friends at Gnip, we’ve generated user interest maps for just north of 75MM active Twitter users. This number gets bigger every day as we suck in more Tweets from the licensed hose. Meanwhile, our demographic coverage is 80% accurate for about 80% of the Twitter population. These stats improve with every new release (approx every 3 weeks).
How to do we determine this information? We start at two points. The first is to create language models that breakdown how users tweet. The second is to study follow-graphs that reveal who users are influenced by. By fusing these two approaches, we can find discriminating characteristics that identify a specific user as belonging to a certain demographic group or a certain interest-category group.
For example, it turns out that Hispanic 25yr old males tend to tweet “#LMAOOOO” (emphasizing the “O”) more predominantly than other groups. Meanwhile 40-something females tend to follow soppy singer @joshgroban at a statistically significant higher rate than males of any age. Niche influencers such as @CrankyOvary provide very strong signals for the interests and demographics of their followers. Meanwhile, broader-based influencers such as @barackobama offer few discriminatory clues about their followers – as many users in many demographic groups follow the US President, to the point where any signal is drowned out by noise. Our system spots literally tens of millions of similar subtle patterns. These patterns then “compete” inside an artificial intelligence system that results in an accurate rendering of “who you are” according to your Twitter activity. It’s good stuff – lots of large scale Machine Learning, Natural Language Processing, Statistical Analysis and Classification Techniques worthy of subsequent blog posts, all sat on top of a humming Hadoop cluster.
Of course, at OneRiot, we use this engine for social ad targeting. But we’ve started to sketch out several other new and interesting uses for this engine. If want to contribute an idea, let us know in the comments below.
Calling all big data geeks in the square state. The next Boulder/Denver BigData Meetup is at OneRiot HQ on August 17. This month features a talk by Ryan Tyer on Machine Learning at Scale. It also features beer and pizza, of course. Sign up on the meetup page.
by Bill Cullen
With OneRiot, media planners have multiple opportunities to deliver blowout mobile advertising campaigns targeted around events.
OneRiot’s publisher network includes all the leading 3rd party Twitter mobile apps. And mobile Twitter users get highly engaged around events – checking their apps in huge numbers to see what friends are saying and to get involved in the conversation. From an advertiser’s perspective, this means more targeted inventory becomes available across our network during these events.
For example, the Women’s World Cup Soccer Final scored a new Twitter record with 7,196 Tweets Per Second. Available ad inventory doubled during the game across our network. We see this pattern repeatedly – for Oprah’s Last Show, X-Games, Apple Key Notes, NCCAF Bowl Games, Valentine’s Day and many, many more. The pattern is predictable – and smart advertisers can work with OneRiot to take advantage.
This is the first of several posts focusing on events 3-6 months in advance to give media planners enough notice to leverage the tactics and scale they want with OneRiot event targeting.
Black Friday is 14 weeks away - enough time to for national brand to plan a highly effective campaign targeting spikes in twitter engagement around the biggest retail sales day of the year. How much ad inventory targeted at Black Friday shoppers will be available this year with OneRiot? Let’s look at the numbers:
2010 Twitter Impressions from #blackfriday conversations from 11/22-11/25, source: Tweetreach
By the time of Black Friday 2011, Twitter will have grown about 300% since the same time in 2010, so you can estimate about a 3x in Black Friday conversations, which means more than 2 Billion impressions across Twitter. OneRiot can address about 20% of all active Twitter users through our app network, so we’ll have about 400M impressions on the block for media planners to hyper target Black Friday shoppers with your brands’ message in the days leading up to the event: 11/21-11/24. That’s a potential blowout campaign for a strategic advertiser.
Not only can you target likely shoppers, but you can drill deeper with demo, geo, and niche interest targeting – like consumer electronics freaks or golf enthusiasts.
How can you take advantage of Black Friday? Contact OneRiot today to get moving on your campaign! theteam@oneriot.com
by Tobias Peggs
OneRiot is one year old today. More accurately, we’re one year old as a company that delivers socially-targeted advertising on mobile.
Twelve months ago, we had a consumer-facing “real time social search engine” – that was very cool but hard to monetize. Now we are a company that hits quarterly revenue targets by selling unique mobile advertising programs to the biggest agencies on Madison Avenue, while sending significant monthly checks to a network of application developers who show our ads to their users.
Although this has been a major pivot in product and business model, a lot of the underlying technology platform – and the stellar engineering team behind it – has remained intact. Undoubtedly, this made the initial business transition easier, and has subsequently helped us accelerate to a leading position in the market for targeted mobile advertising.
For those not familiar with it, our search engine found the content that was resonating with people on the social web. Now our advertising platform determines what that same audience is interested in, focuses on mobile, and targets relevant advertising messages that resonate accordingly.
To do this, we start by ingesting massive amounts of publicly available social data from Twitter, Foursquare and others. With advanced machine-learning techniques (in combination with a humming Hadoop cluster), we analyze friend connections, study the reach of influencers, and comb through the content in millions of Tweets and check-ins. From there, we determine demographic profiles and construct a “social interest-graph” which helps us properly target ads. And we do all this in “real time” to make sure that any advertising message we deliver resonates with users right now.
This means that sophisticated mobile marketers can work with OneRiot to execute advertising campaigns that utilize social-interest-based targeting techniques as well as demographic targeting. For example, Nike can work with OneRiot to target “people interested in soccer” who are “Hispanic”, “male”, and “aged 18-30”. Of course, geo-and OS-targeting come standard with mobile advertising, so Nike could further refine that campaign to reach Hispanic males, 18-30, interested in soccer, in California, using Android devices. Combined, this provides a granular level of audience targeting that we believe to be unmatched in mobile advertising today.
And now this clever capability is turning into a compelling business. Not only do we sell advertising campaigns directly, but we’ve also signed some significant reseller deals with bigger agencies who now view OneRiot as their mobile solution. We’ve successfully delivered multiple ad campaigns for the likes of Microsoft, The Gap, General Motors, AT&T, and even President Obama! Mobile is inherently social, and social targeting delivers fantastic results for these advertisers. Our social targeting data is also now available on a number of leading “real time bidding platforms” for use across multiple sources of mobile inventory. This gives us an additional, transactional revenue stream that is set to grow significantly as media buying on mobile migrates towards the automated approaches we’re witnessing today in the desktop display advertising ecosystem.
So what about the next 12 months? There’s no doubt that the market that we’re in – mobile advertising – is about to explode. By 2014, mobile internet usage will overtake desktop usage. And yet, last year, mobile advertising budgets totaled just 4% of internet spend. That’s out of whack, and will be fixed fast as advertisers follow the audience. And as the wider mobile advertising market grows, so does the opportunity in front of OneRiot. Our goal now is to capitalize on that – by scaling, innovating and executing.
We will scale. We will monetize as many mobile ad impressions as we can. Our recent moves into RTB gives us enormous reach, where we can now supply valuable targeting intelligence across billions of ad impressions each month. In the meantime, we continue to drive our direct and reseller business impressively, commanding ever higher CPMs in line with the performance of our targeted ad campaigns.
We will innovate. We will find new ways to improve the accuracy, coverage and performance of our targeting technology. Fundamentally, we believe that “social” and “mobile” are tightly coupled – and social targeting on mobile delivers the best results. But both social and mobile are in their infancy. Who knows what both will look like in five years? (Remember: there was no iPhone five years ago and the world’s most popular Android was C-3PO). It’s our job to stay ahead of both fields – and to bring new signals into the mix. For example, geo-location is an obvious area to explore with mobile advertising. Our recent announcement of a new social-geo targeting data product – enabling advertisers to target the right users, in the right location, with the right offer, at the right time – is just the start.
We will execute. The turn-around we’ve delivered in the last 12 months shows that OneRiot is a company with execution in its DNA. But we all know that the faintest whiff of complacency could kill us stone dead. We’ve done well this year, but this is just the beginning. We need to work harder, faster and smarter than we ever have before if we want to stay ahead.
We’ll be making plenty of announcements on this blog in the coming weeks and months on scale and innovation. (You can assume we’re executing like crazy in the background). Some will raise eyebrows, and will open up new opportunities that we tackle with relish. That’s exactly why we work for a company like OneRiot. The next twelve months? Bring it on.
by Tobias Peggs
The Women’s World Cup Soccer Final scored a new Twitter record with 7,196 Tweets Per Second. When any big event like this is on TV, capturing the attention of the nation, social media engagement goes through the roof. By analyzing activity on Twitter in realtime, OneRiot sees this pattern like clockwork throughout the year – it occurs with sporting events to cultural moments to celebrity awards and more.
And when TV-related social media activity spikes, we also see that this spike is driven by a massive amount of people watching the TV and checking their social mobile apps at that time. In other words, the same audience is following the event on two screens. TV is the first screen, and the phone is the second screen. In fact, 71% of smart phone owners watch events live on TV at the same time as checking social updates on their phone.
Big media companies like Disney/ESPN are beginning to understand this, and broadcast on both mediums simultaneously to capture audience attention on both screens. But from an advertiser’s perspective – which is how we look at it – this means more available ad impressions to the same target audience.
For example, here’s a chart that shows Tweets Per Second during this year’s Super Bowl, overlaid with available impressions on the OneRiot social-mobile ad network.
Our available ad impressions doubled during the Super Bowl. In other words, our apps saw twice as much activity as usual while the game was being broadcast live on TV.
This phenomena offers the potential to deliver blow-out advertising campaigns, targeting the same audience demographic on TV as the phone – and targeting a big number of them as available ad impressions double.
We executed a campaign like this for Chevy during the Super Bowl. Chevy ran TV ads during the half time show, targeting an audience which was predominately males, 18-50, interested in sports, with a strong affinity for cars. However, Chevy were also wise the fact that large numbers of this audience would be following along on the second screen. So they worked with OneRiot to target the same creative at the same audience at the same time, on the phone (in the form a click-to-play mobile video ad).
If the target user watched Chevy’s ad on the TV, and then picked up their phone, Chevy double-dipped. But if that user missed the TV ad because they were on their phone, then Chevy got a second bite of the cherry. Thanks to second screen tactics like this, enabling Chevy to reach their target audience wherever and however they were engaging with the big game, Chevy became the 4th most talked about brand on Super Bowl day – a huge achievement given the number of brands shouting for attention on that day.
If you want to engage with an audience on the second screen around a big event such as the Soccer World Cup or the Super Bowl, talk to theteam@oneriot.com
by Tobias Peggs
Mark Suster has a great post outlining several reasons why he’s doubling down on Twitter. One such reason is the power of implicit data that exists within the Twitter ecosystem.
Targeting ads to “Sports Guys” using implicit Twitter data.
As Mark writes: “Do you follow Fox News, Rush Limbaugh, Sean Hannity and Glenn Beck? Well if you also follow Keith Olberman and Rachel Maddow then I can interpret something about you. If you follow the former and not the latter I can interpret something else. Companies [can] run correlation analyses to determine probabilities that you are a, b or c. Even if they’re not using this to target you with information sent via Twitter, they might use it in aggregate to determine things like the likely electoral votes in a region that will swing for a candidate. Or the probability of Southern Democrats to buy cable versus satellite or an Android versus an iPhone.”
At OneRiot, we use similar analysis to determine what users are interested in right now, and then target ads using that data.
You can “see” how it works using this tool. Simply type in a Twitter ID and, based on implicit data, you can “see” what that person is interested in right now. This is broken out by IAB interest categories (e.g. “Sports” is a Tier 1 interest, with “Sports->Cycling” being Tier 2). The tool also shows a sample advertisement that OneRiot might display to that user.
Sonos ad targeted to a male user with interests in Music and Technology
This simple tool sits on top of some pretty sophisticated Big Data Analysis, Machine Learning and Natural Language Processing. We’ll cover the technical detail in a later post, but some important considerations include:
1 – Who a user follows. As Mark points out, who you follow can be used to help interpret what you are interested in. To use a simple example: I might never tweet… but if I follow a number of influential tech bloggers, I’m clearly using Twitter to consume tech content, and I’m interested in “Technology”. To get a more accurate read of interests, it’s also important to understand how influential those tech bloggers are in certain content categories. To enable this, we’ve developed a granular Klout-like score for category influence. For example, @parislemon might be a tech influencer who OneRiot scores highly on content related to “Apple” but low on “Microsoft”. If I chose to follow him over another tech influencer with the opposite scores, it might indicate that I’m more interested in products coming from Cupertino than Redmond (which in turn influences what ads OneRiot will display for me).
2 - Content in Tweets tweeted. This seems like the most obvious signal, but we use it in a non-obvious way. If a user tweets “Watching the movie Horrible Bosses #LMAOOO”, you could imply that the user likes comedy movies. However, more interesting to us is the word-level unigram, “#LMAOOO”. By studying n-grams in hundreds of millions of tweets, from millions of users, we’ve built a statistical language model that can determine user attributes such as age, gender, ethnicity and even income level. As an illustrative example, it maybe that 18-24 year old Hispanic females are more likely to emphasize the “O” in “#LMAOOO” than other age groups or other ethnicities. Hundreds of thousands of similar indicators compete inside our language model. The end result is that it’s possible to target ads to specific demographic groups with incredible accuracy.
3 - Content in Tweets consumed in the stream. Twitter is a global conversation, and the realtime firehose of Tweets reflects the changing interest of its users. Accordingly, OneRiot processes the content in that firehose to identify temporal interests that a user might have right now. To illustrate, let’s assume that “User A” is not typically a movie fan, and follows no defined “movie influencers”. We would not normally target that user with a movie advertisement. Meanwhile, elsewhere in the Twitterverse, a cluster of known movie influencers suddenly start Tweeting a lot about “Super 8”. Our system will automatically connect the dots and understand that “Super 8” is hot in the movie category. To continue with the illustration, let’s now assume that because “Super 8” is hot, a lot of people that “User A” does follow also start Tweeting about it, and “User A” consumes those tweets. OneRiot would now automatically categorize “User A” as being temporarily interested in that movie. There’s a window of opportunity to effectively target “User A” with an appropriate movie ad. When we use targeting techniques like these, the performance is through-the-roof fantastic. (Our theory is: from User A’s perspective, the ad content is out of their norm, so it stands out. But it’s also “socially relevant right now”, which is intriguing. The one-two combination results in a killer click-through rate).
Now, we combine all this magic (and more) for targeting ads specifically on mobile. Why? Well, targeting for mobile ads is hard. Generally speaking, cookie-based technologies which work well on the web for audience targeting do not work on mobile. So in the “cookie-less world” of mobile, media buyers need other signals to identify a target audience. OneRiot’s primary targeting signal is “social”, including a heavy dose of Twitter. Using techniques like those covered above, OneRiot analyzes social media activity published and consumed by mobile users to implicitly determine audience characteristics – and we target ads based on that data. This approach capitalizes on the fact that mobile is inherently social, meaning social signals are by far the strongest way to determine what content the mobile audience will engage with at any point in time.
I hope this provides some insight into the “how” of OneRiot’s socially targeted mobile ads, and how we use implicit data in the Twitter ecosystem to help. For the “why”, read here, here and here.
by Tobias Peggs
Three numbers are jumping out at us this morning – showing that socially-targeted, in-app advertising, really works.
The first comes from our friends at Compete.com. Their new study reports that 52 percent of all smartphone owners recall ads they encounter in mobile apps. That number drops to 40 percent when asked about ads encountered while surfing the mobile web.
The second comes via TechCrunch from the team at Flurry. Their new study shows that the average user now spends 9% more time using mobile apps than the Internet. In June users spent an average of 81 minutes daily on mobile apps, compared to 74 minutes on the web. A year ago, the average user spent just under 43 minutes a day using mobile applications.
Flurry says that this staggering growth in mobile app usage is a result of more sessions during the day per user, as opposed to an increase in session length. As we’ve already blogged, social apps are the primary driver behind mobile growth. Flurry’s data indicates that users are checking their Twitter apps and others more often as opposed to spending more time in any one app in any given session. From an advertiser’s perspective, this offers many more opportunities to engage the user in relevant ways.
The third number comes from our own internal reports tracking mobile ad campaigns we ran over the weekend. One in particular – for the Foo Fighters forthcoming tour – is especially worth highlighting. We’re geo-targeting that campaign to cities where the rock band are going to play, and socially-targeting within those geo-locations to users with a social interest in rock music. The CTRs are hovering around 2% - which is about 10x industry average for mobile ads.
De La Soul might claim that “Three” is the magic number. But “Ten” is even more impressive…
by Bill Cullen
OneRiot is now able to pair its socially targeted mobile ad inventory with engaging rich media creative. This is the grand slam that mobile advertisers have been asking for – and we are pumped to now offer it! That is, the ability to address a highly targeted audience on mobile coupled with compelling rich creative that outperforms standard banners. You can see some beautiful demo rich media ads live on OneRiot mobile inventory by heading to http://bit.ly/RichRiot on your iPhone or Android.
Working with top mobile rich media providers like Celtra, we can now bring features like video, social sharing and image galleries to mobile ads like this:
Celtra has a blazing fast web based “Ad Creator” tool, a great demo platform, insightful analytics and wonderful people. In the coming weeks we’ll be announcing a wider mobile creative alliance with several top vendors who have all been certified by OneRiot. They make the creative production process ridiculously smooth. You can generally build an ad far faster with a Celtra-like tool verses a comparatively lengthy and expensive process for desktop rich media with Adobe flash. Here’s a glimpse at Celtra’s interface with drag-and-drop components, and even a live chat bot if you need instant help:
So what does all this mean for advertisers? It’s time to start loading the bases for the grand slam! Activate your brand teams and educate your clients that there are no longer barriers to reaching a targeted audience on mobile with outperforming rich media ads.
As of last week, with Apple’s Twitter Single-Sign-On integration, there is even more to get excited about. Users on iOS5 authenticated at the OS level will be able to click on a Twitter share button in an advertisement, and instantly be able to share a branded Tweet to their followers. This subtle change makes it far easier to share branded content and we are poised to see advertisers take full advantage of it to enhance an “earned media” strategy.
If your brand is taking a backseat mobile advertising it might be time to hop in the front and give OneRiot a call to see what’s driving innovation in targeting and creative for top brand advertisers. Follow Bill on Twitter or email bcullen@oneriot.com to find out how to work with OneRiot.
