The Gamification of Data
I attended the Insight Innovation Conference this week – a conference where marketing research professionals gather to think about the future of their industry. A number of the sessions dealt with the topic of gamification. Marketing research is really all about gathering data, and a lot of that data is gathered via surveys. And, not surprisingly, market researchers are finding it harder than ever to get people to participate in their surveys, finish the surveys even when they do participate, and supply trustworthy, high quality answers all the way through. It’s a vexing problem, and it is one that is central to the future of this industry.
That’s where gamification comes in. Some of the smartest minds in the research business think that by making surveys more fun and more engaging, they can not only improve response rates, but actually gather better quality data. And this has implications for all of us.
One particularly interesting presentation provided some fascinating “before and after” examples of boring “traditional” survey questions, and the same question after it had been “gamified.” As significantly, he showed encouraging evidence that gamified surveys do in fact deliver more and better data.
And while it’s relatively easy to see how a survey, once made more fun and engaging, would lead people to answer more questions, it’s less obvious how gamification leads to better data.
In one example, the survey panel was asked to list the names of toothpaste brands. In a standard survey, survey respondents would often get lazy, mentioning the top three brands and moving to the next question. This didn’t provide researchers with the in-depth data they were seeking. When the question was designed to offer points for supplying more than three answers and bonus points for identifying a brand that wasn’t in the top five, survey participants thought harder, and supplied more complete and useful data.
In another example, survey participants were given $20 at the start of the survey, and could earn more or lose money based on how their responses compared to the aggregate response. Participation was extremely high and data quality was top-notch.
Still other surveys provided feedback along the way, generally letting the survey participants know how their answers compared to the group.
Most intriguing to me is that gamification allowed for tremendous subtlety in questions. In a game format, it’s very easy to ask both “what do you think” and “what do you think others think,” but these are devilishly hard insights to get it in traditional survey format.
Gamification already intersects with crowdsourcing and user generated content quite successfully. Foursquare is just one well-known example. But when the marketing research industry begins to embrace gamification in a big way, it’s a signal that this is a ready-for-prime-time technique that can be applied to almost any data gathering application. Maybe it’s time to think about adding some fun and games!
People Power
There was news this week about the formation of Bloomberg Beta, a new venture capital fund sponsored by data company Bloomberg LP. One of Bloomberg Beta’s early investments is a company called Newsle, that will alert you whenever someone you specify – a friend or colleague – is in the news. This is a tough nut to crack. Searching thousands of news sources and trying to determine if the John Smith mentioned in an article is the same John Smith of interest to you is a complex undertaking. But what really intrigued me is that those who have written about Newsle see another major problem that the company faces: lack of activity. Think about it. If you import your list of Facebook friends (something Newsle encourages you to do), the chances of any of them appearing in news stories is pretty low. That means most people will sign up for Newsle and nothing will happen, not because Newsle isn’t working, but because there is no news to report. It’s hard to establish the value of your service if you’re not delivering at least a little something every now and then.
That’s why in addition to your Facebook friends, Newsle also encourages you to import your LinkedIn contacts, and while you are at it, your address book as well. Somewhat incongruously, Newsle also encourages you to follow politicians and celebrities. The hope is the more people you track, the more likely you’ll get hits.
But what if Newsle flipped its model? Instead of serving individuals who for the most part have small lists of mostly boring contacts, why not hook up with commercial data publishers, many of whom have tens and even hundreds of thousands of contacts in their databases? Publishers could then send real-time alerts out to their subscribers who are interested in specific people or any activity relating to executives at a given company. In addition to sales intelligence, these news alerts could also provide a basis for making contact with a prospect. Plus, publishers could database these news events to build deep profiles on company executives that would have evergreen value.
This could be a great opportunity for Newsle to crack its volume problem, and for data publishers to add in high-value alerting services and historical data all in one fell swoop.
That’s powerful, people!
Is Data the Salvation of News?
Doubtless by now you’ve heard the buzz around the travel news start-up called Skift. Skift is the brainchild of Rafat Ali, the founder of PaidContent. Skift appears to be a disruptive entry into the B2B travel information market, and seeks to distinguish itself through a fresh style of reportage and eclectic editorial coverage (news of innovative airport design merits the same level of coverage as news about major airlines). Given Rafat’s track record and the fondness these days for all things disruptive, Skift has recently attracted an additional $1 million from investors. Where this gets really interesting is that Skift wants to broadly cover the incredibly huge global travel industry with only a handful of reporters. That means Skift will deliver a mix of original reporting along with licensed and curated content. So where’s the innovation and disruption? The answer, in a word, is data.
Skift’s plan is to deliver most of its news free on an advertising-supported model, but to also offer paid subscriptions (reportedly to range from $500 to $1,000) to give subscribers access to travel data. It’s no surprise then, that Skift is positioning itself as a “competitive intelligence engine.”
Skift may be on to something. I first got interested in the intersection of news and data back in 2007, when I read some fascinating articles written by Mike Orren, the founder of an online newspaper called The Pegasus News. Orren had discovered that despite his focus on hyper-local news, the editorial content that consumers are ostensibly hungering for, fully 75% of those who came to his site were there for some sort of data content. Others in the newspaper industry have also reported similar findings.
In this context Skift seems to have a firm grasp of the new dynamics of the information marketplace: while there is an important role for news, it’s increasingly hard to monetize. That’s why news married to data is a much smarter business model. News provides context and helps with SEO. It can be monetized to some extent through advertising. Data offers premium value that is easily monetized with a subscription model, and the two types of content, intelligently combined, offer a compelling, one-stop proposition to those who need to know what’s going on in a specific market.
This is, of course, a conceptually simple model that not too many legacy news publishers have been able to execute on. That’s because the two types of content are inherently distinctive, from how they are created to how they are sold. Perhaps a disruptive market entrant like Skift will be able to crack the code and produce both types of content successfully itself. Personally, I think the fastest and surest path to success is to build strong partnerships with data publishers.
Drawing the Line: Customers as a Data Source
Today’s New York Post reports that Bloomberg was confronted by Goldman Sachs for allegedly allowing its journalists to tap into subscriber usage data.
It is early into this event, and still unclear what the ultimate impact on Bloomberg might be, but regardless of outcome, this remains an area of acute importance to all data publishers. That’s because data publishers often have access to potentially confidential and valuable information, and the slightest misstep could put your whole business at risk by destroying customer trust.
The Bloomberg case was actually pretty tame in many respects: a Bloomberg reporter called Goldman Sachs to inquire if a partner was still working there because he hadn’t logged into his Bloomberg terminal for a long period of time.
Login data provides one level of insight into the activity (or non-activity) of your subscribers, but that’s just the tip of the iceberg. If you know what job function a particular subscriber performs, and also what that subscriber is searching on, you could potentially get insights into new product development activity, sales strategy or even potential acquisition targets. You see where I am going, and hopefully you also see why you should never go there. Your subscribers, often unknowingly, are trusting you with a lot of potentially sensitive and valuable information. It’s your duty to guard it carefully.
I’m not suggesting that there is any issue with aggregate analysis of activity against your database to better understand what your subscriber base as a whole is interested in so that you might improve your product. But whenever you start associating specific search and view activity with specific subscribers, you need to be very careful.
Depending on the markets and the job functions you serve, you may even want to re-think if, say, your customer service people should be able to view a specific subscriber’s saved searches. And even something as innocuous as putting up a list of “most viewed companies this week” could inadvertently reveal too much if you operate in a tight vertical.
Too often these days, I am seeing people do things because they can, not because they should. Technology is often addictive in this way. But I urge you to look before you leap. Trust is easy to lose, hard to regain and essential to your success.
Enigma: Disrupting Public Data
Can you actually disrupt public data, which by definition is public, and by extension is typically free or close to free? Well, in a way, you can.
A new start-up called Enigma, which can be thought of as “the Google of public data,” has assembled over 100,000 public data sources – some of them not even fully or easily accessible online. Think all kinds of public records from land ownership, public company data, customs filings, private plan registrations, all sorts of data, and all in one place.
But there’s more. Enigma doesn’t just aggregate, it integrates. That means it has expended tremendous effort to both normalize and link these disparate datasets, making information easier to find, and data easier to analyze.
The potentially disruptive aspect to a database that contains so much public data is that there are quite a few data publishers with very successful businesses built in whole or in part on public datasets.
But beyond the potential for disruption, there’s some other big potential for this (I’ve requested a trial, so at this point I am working with limited information). First, Enigma isn’t (at least for now) trying to create a specific product, e.g. a company profile database. Rather, it’s providing raw data. That will make it less interesting to many buyers of existing data products who want a fast answer with minimum effort. But it also means that Enigma could be a leveraged way for many data publishers to access public data to integrate into their own products, especially since Enigma touts a powerful API.
The other consideration with a product like this is that even with 100,000 datasets, it is inherently broad-based and scatter-shot in its coverage. That makes it far less threatening to vertical market data publishers.
Finally, Enigma has adopted a paid subscription model, so it’s not going to accelerate the commoditization of data by offering itself free to everyone and adopting an ad-supported model.
So from a number of angles, this is a company to watch. I’m eagerly waiting for my trial subscription; I urge you to dig in deep on Enigma as well.