Twitter and LinkedIn Battle for Eyeballs and Loyalty

On June 29, Twitter and LinkedIn decided to end a partnership that began in 2009. Before the 29th, tweets had the ability to flow seamlessly from Twitter to LinkedIn. That's no longer possible. Twitter has restricted its API to prevent tweets from posting to LinkedIn user profiles. LinkedIn users can still create updates to publish to Twitter - it is a matter of clicking a button and it happens.

More significantly, the separation is a story which illustrates the difference between how collaboration looks on paper and how it plays out in practical terms when collaborating companies mature and change and business models uncomfortably bump up against one another.

If you are a regular reader, you are likely an information provider. As an industry, publishers are familiar with business model conflict and the Twitter and LinkedIn the split is not surprising.

The pairing made sense for convenience reasons: compose once and publish twice. A seamless flow of tweets from Twitter to LinkedIn added aspects of community that LinkedIn, with its origins as a structured database, had lacked from its inception.

As a website for professional networking, LinkedIn succeeds in its ability to connect people. Once connections between people on LinkedIn are made, the ability to share information is limited. LinkedIn Groups have found wildly varying degrees of success. (InfoCommerce LinkedIn Group members: please check out my colleague Megan's question posted earlier this week regarding how helpful you find LinkedIn Groups and weigh in).

But is this loss of seamless "tweet flow" truly a big loss for LinkedIn? Arguably not.

Although the collaboration enabled sharing of information between LinkedIn connections, the pairing was not without its problems. Pacing and content between the sites were a less than ideal match. Overall, LinkedIn is much slower paced than Twitter. The Twitter partnership produced significant amounts of content for LinkedIn. Yet Twitter users who tweet often (say 15 or more times a day) tend to stand out and can crowd or eclipse LinkedIn generated updates displaying on the site. Perhaps this is the reason why hiding tweets on LinkedIn was an option.

Further, tweets aren't entirely consistent with that which should be shared on a professional networking site. Twitter content that doesn't play well to an audience of business connections could carry more significant consequences than just personal embarrassment. And even anodyne tweets, because of their economy of space, still offer ample room for miscommunication.

LinkedIn and similar sites using Twitter's API have created a range of value-added products from Twitter clients to analysis tools. These products have improved Twitter's value and reach. Even though LinkedIn was never really a destination to go to read tweets, LinkedIn and others using Twitter's API may have funneled some traffic away from Twitter which presents a challenge when money is in the mix. Twitter's revenue model relies on ad money (promoted tweets).  

As International Business Times' Valli Meenakshi Ramanathan notes: "Though the end of the partnership was nothing new in the social network landscape as search giant Google moved away from the microblogging sweetheart recently, leaving Twitter to spruce up its search function to stay on track, the changes did call for LinkedIn having to redefine its strategy and operations."

Bottom line, this is a battle of eyeballs, user loyalty and control of content. And while LinkedIn might look like the loser, it probably is time for LinkedIn to put more effort into enhancing its value proposition, rather than papering over the issue with a tidal wave of tweets.

-- Nancy Ciliberti

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!

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.

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?