The Outlook on LinkedIn

LinkedIn is one of the most important data products ever created, and the recent Fortune interview with LinkedIn CEO Jeff Weiner is chock-full of insights and fresh thinking. I can't do justice to the full interview in one post, but here are a few points to whet your appetite:

1. Data Beget Data: As Weiner puts it, "One of the most exciting parts of the LinkedIn platform and the LinkedIn ecosystem is that the more members we attract, the more deeply they become engaged, the more data is being generated. And that data can be leveraged to create more relevant experiences for our members and better return on investment for our customers. Data really powers everything that we do. So, it powers algorithms that will suggest people you may know, so you can build out your network. It can suggest groups you may like that you can join and share information and knowledge."

The notion that participatory, open databases can achieve a network effect, where every new participant makes participation in the databases more compelling to others, is hardly new. But LinkedIn takes this to another level, using the data it collects to fuel more engagement and more participation. This is the unique capability of structured content - it is more susceptible to algorithmic alchemy.

2. A Global Labor Marketplace: LinkedIn believes that if it can collect enough information about people and companies (and it already has over 2 million company profiles), it can create a global labor marketplace that efficiently moves the right person to the right job, something that could fuel tremendous new levels of productivity and economic growth. How often do you get to wrap a big business vision with a clear social good? As importantly, this thinking supports my belief that many data products can pivot from information repositories to true industry marketplaces. 

3.  Core Competencies: LinkedIn has clearly set its sights on becoming a provider of internal corporate directories, something big companies need, but rarely execute well. And what a beautiful idea: companies get better and more powerful internal directories while LinkedIn reaps huge new numbers of public profiles. And might I add that this is a wonderful example of Perkins' Law: "No organization outside the data business will voluntarily maintain a database if there is a viable alternative to doing so."

4. LinkedIn and Outlook: In an attempt to stir the pot, Fortune suggests to Weiner that Microsoft should buy LinkedIn and integrate it into Outlook. Weiner demurs in response, but this raises what I think is an hugely under-appreciated possibility for LinkedIn: to become the world's best spam filter. LinkedIn is uniquely able to assess the legitimacy of someone sending you email, as well as your interest in receiving it. The notion of building an identity layer into LinkedIn, and a lot of other vertical market databases, remains an area of huge opportunity.

My happy conclusion is: a lot of these opportunities are not unique to LinkedIn. There are lots of exciting opportunities for smaller, vertical market data products as well. Read the full article and put on your thinking caps!

Google: Free Here; Paid There

Google may be a lot of things, but it's certainly not boring. Just this week in fact, it did several interesting revenue model back-flips, changing one product to free and making another one paid.

Let's start with Zagat. Zagat sells its content, in print and online. Not a revenue model Google knows anything about, but that didn't stop Google from snatching up Zagat for around $150 million in 2011. I predicted at the time that Google would make Zagat content free and dump in into Google Places (home of its user-generated business reviews). What happened? Google announced this week that it will make Zagat content free and dump it into Google Places. Google Places, in turn, will be dumped into Google Plus, as part of an initiative to shore up Google's faltering response to Facebook.

Google hasn't thrown away all of Zagat's revenue, at least not yet. You'll still be able to buy the print Zagat guides. Google will still charge for the Zagat iPad app. And my suspicion is that Zagat's real source of profit, gift copies of the guides imprinted with corporate logos, will continue. Make sense? If so, click here.

The biggest question for me is what happens when you mix Zagat's edited, witty, curated reviews with a much larger grab-bag of user generated reviews? Will Zagat reviews shine, or get lost in the sauce? Will people continue to submit reviews to Zagat when they can get immediate gratification (and reach the same audience) with a user-generated review? Sure, the Zagat brand is strong, but Google is sailing into uncharted waters, and I am not sensing a strong hand on the tiller.

This very same week, Google decided to rebrand its Google Product Search service as Google Shopping. And with the new name, Google decided a revenue model might be cool too. So the new Google Shopping service will be paid inclusion. Yes, Google Shopping is now a buying guide.

Charging for inclusion in the product directory (Google daintily calls this "a commercial relationship with merchants") is apparently the first time a Google-created service has gone from free to paid. Also, as you read Google's rationale for this shift, you realize that it has spent a lot of time and money to learn some basic truths about data publishing, for example:

• Even companies that do make the effort to submit product information in structured format are lousy about keeping their information current
• A smaller database of highly accurate data is more attractive to most users than a larger database of moderately accurate data
• Structured data permits far more powerful and precise searching of product information

So while I have historically been at a loss to figure out what Google is doing, it's getting easier these days as Google moves ever-closer to doing everything, all at once. Just don't try this strategy at home!

Search Engines: From Indexers to Distributors?

A New York Times article this week, entitled "From Search, to Fetch," describes moves by both Google and Bing to get you to an answer faster. Called the "Knowledge Graph" by Google and "Snapshot" by Bing, you'll find that searches for certain types of information will now bring you a highly summarized presentation of key facts without needing to click on any of the links shown in the search results.

As the article concludes:

Both Microsoft and Google stress that these developments are but the first timid steps into a beautiful future - a future where search pages know what you mean, display exactly the information you want with one click, and even perform tasks for you. These companies are no longer happy serving only as the card catalog for the Web; now they even want to bring you the book.

More interesting to me, however, is that only in a small percentage of cases will Google (courtesy of Google Books) truly bring you the book. In the majority of cases, what Google will bring you is data. And where do these data come from? Third-party databases.

This is just one more example of search engines tacitly acknowledging the value of structured and semi-structured content. As importantly, Google is also acknowledging that some content sources are more dependable and trustworthy than others. Yes, Google is now featuring content that hasn't been selected by algorithms, but rather by humans basing their decisions in large part on the brand reputation of the content provider. Bing is presumably operating the same way.

Google so far is limiting itself to free third-party data sources such as Freebase, the CIA World Factbook and Wikipedia, among others. The data sources used by Bing aren't disclosed, but Snapshot reportedly is a bit more commercially oriented, providing summarized data on hotels, restaurants, bands, events, etc. I think it is quite likely Bing is already licensing some of this content from third parties.

The potentially great outcome is that with the arms race mentality of Bing and Google, one or both may start licensing more content in an attempt to offer the most compelling search experience. That's good for those publishers willing to be paid a large fee to make some or all of their content broadly available for free (and what a great ride that was for many publishers during the dot com boom). The losers in this scenario are those data products with commoditized content. For those publishers with expensive, specialized and proprietary content, it's a mixed scenario. Some may experience neither benefit nor harm. Others may find that exposing a taste of their data for free can yield tremendous levels of exposure that can drive new sales.

The way I see it, the search engines continue to evolve from information indexers to information distributors. And this could be a very fine evolution indeed.

Big Data: A Long Way from Plug-and-Play

One of the key markets for all the new big data analytics providers is marketers themselves, a group that should be a natural for turning deep customer insight into increased revenue. But are they ready? Well, according to a study by Columbia Business School and the New York American Marketing Association, although nearly all (91 percent) of marketers value and want to make data driven decisions, 29 percent report that their marketing departments have "too little or no customer/consumer data." Thirty nine percent of the marketers surveyed said their data is collected too infrequently and "not real-time enough." Two in five marketers admit that they cannot turn their data into actionable insight and about an equal number (36%) report that they have "lots of customer data," but "don't know what to do with it."

Researchers found that despite widespread adoption of digital marketing tools like mobile ads and social media, they are less likely to be measured for ROI. Eighty five percent of marketers are using brand accounts across Facebook, Twitter, Google+, and Foursquare but 14 percent of the social networking users are tying them to financial metrics. Fifty-one percent of marketers said they use mobile ads (in-app, or SMS) but only 17 percent of those using mobile ads are tying them to financial metrics. Forty one percent of email marketers measure their results with financial metrics. Overall, 60 percent of companies report that comparing the effectiveness of marketing across their different digital media is "a major challenge."

Forty two percent of marketers report that they are not able to link data at the level of an individual customer and 45 percent are not using data to personalize their marketing communications. Twenty-eight percent said they do not know which high-value customers to focus their marketing on.

Marketing success in the advent of Big Data means mapping marketing metrics to objectives aligned with corporate strategy, collecting and sharing data at the individual customer level throughout the organization, targeting and personalizing marketing efforts and measuring ROI across touch points. But marketing success in Big Data also depends on having the data in the first place. We're not all there yet, which is why the excitement around Big Data needs to be grounded in the mundane reality of where most marketers are today.

-- Nancy Ciliberti

Got Klout?

Imagine a business based on a mash-up of social media, analytics and ratings. And that's exactly where a company called Klout plays.

Klout exists to assess your social media importance. Using advanced algorithms, it looks at how active you are in social media, how big your audience is, how influential are the people in your audience, and the impact of your social media activity. All this gets rolled up in a Klout score - a number from 1 to 100.

If this sounds like nothing more than an interesting academic research exercise, you might be surprised. Klout reportedly has over 5,000 large companies tapping into its database to determine who really matters online. Uses are varied and fascinating. PR companies use Klout to assess whether or not to personally engage with someone who has made a negative online comment about a client. Marketers are creating customized pitches to those with the highest Klout scores in the hopes of engaging with them and getting them to talk to their audiences about their products. And this is just the tip of the iceberg in terms of potential applications. Consider, for example, that Klout has already built a connector to Salesforce.com.

In terms of potential applications, some are cutting edge, but not all are necessarily positive. There are numerous reports floating around of people applying for jobs and being rejected due to low Klout scores. Some hotels reportedly will look up your Klout score at check-in, and provide free upgrades to those with high scores, presumably in the hopes of favorable online mentions. Similarly, Cathay Pacific airlines will make its San Francisco frequent flier lounge available to anyone with a high Klout score - regardless of what airline they are flying. The objective again is favorable mentions.

Implications? What we may be seeing is a devolution in advertising where marketers move to a bottoms-up approach to distributing their messages, with the hope that they can achieve powerful and cost-effective reach by having a small group of individuals amplify their brands and their messages for them. This could have serious impact on those that make money today by aggregating fixed audiences.

Of course, as the rewards for having social influence grow, so too will the number of people gaming the system to improve their scores to reap all these upgrades, free samples and attention. As these activities accelerate, social media measurement could end up getting so polluted and undependable that it becomes too difficult to isolate true influencers, likely a fatal blow to this innovative new marketing approach. Alternatively, Klout, like Google, could try to keep the game going by regularly tweaking its algorithms to maintain its value. But as we add the wisdom of algorithms to the wisdom of crowds, are we really getting any smarter?