Feb. 16 2011 - 12:07 am Posted by Bruno Aziza
Image via CrunchBase
Investors started the year excited, then disappointed, about the potential of a Facebook IPO and a $50B valuation. But fortunately, the upcoming LinkedIn IPO and its $2B valuation gives them an opportunity to get in the game and cash in on the much talked-about “social network” trend.
The LinkedIn IPO is indeed exciting, but if you are an executive, you should spend more than just your money on LinkedIn – you should spend time understanding how the social network works, and how its model can help you build better applications for your organization.
LinkedIn offers many practices that organizations should follow when building internal applications. In this post, I’ll focus on two: how LinkedIn thinks about productivity, and its approach to data.
“Time In App”
Most productivity applications measure success by the number of hours its users spend in it. For example, we know that Facebook represents about 12% of your internet time. According to Nielsen Research, internet users spend close to 5X more time on Facebook than YouTube. So Facebook wins, right? Wrong! While “time in app” might appear to be a great gauge for stickiness, LinkedIn’s CEO argues that it might not be the right measurement (see Jeff Wiener’s explanation at the O’Reilly Web 2.0 conference here).
While Facebook’s drive towards advertising dollars might justify the importance of the ‘time in app’ metric (you might have noticed Facebook’s recent advertising addition to your photos?) – LinkedIn focuses on productivity for its members (LinkedIn makes money via ads, but member services and enterprise hiring services are also part of its business model).
What does this mean to you: Your company’s application model is more similar to LinkedIn than to Facebook. Don’t be drawn to the overly satisfying measurement of “time in app” unless your business model is driven by ads; your company gets more value by optimizing your employees’ time.
If you are looking for inspiration on how to change the culture of measurement inside your organization, I highly recommend looking up Zappos’ CEO Tony Hsieh’s work in call centers. In this video, Tony explains how a longer resolution time is better than a shorter one (his book, “Delivering Happiness” tops the customer service and management charts on Amazon).
“Mi Data es Su Data”
Facebook is not particularly regarded for its ability to give its members value back on their own data. While it’s very easy to get data into Facebook, it’s very difficult to get data out and in a meaningful way. Simply charting your friends’ geographical spread is difficult (join the Facebook Data Team page to stay appraised of the latest). Beyond suggesting new friends, Facebook does little to share back with the community the incredible insights it gathers about its users.
LinkedIn’s approach to data is quite different. The LinkedIn Analytics team has been hard at work understanding your data trail, and they are not shy to share these analytics with you. My favorites include LinkedIn’s “Signal,” “Career Explorer,” “InMaps” or “Skills” which launched most recently.
Each application exemplifies LinkedIn’s drive to fulfill its vision – better connecting business people, through analytics. The above applications showcase that, by using clever algorithms, members can be presented with insights that anticipate their questions and connect with others more efficiently.
What does this mean to you: Your organization is sitting on latent data that, if used, can return incredible value to your employees and bottom line. Think through the data your applications hold and the tasks that could be automated or suggested. Take a look at LinkedIn’s Career Explorer. You can use it to explore the future of your career based on the paths of others. Along the way, Career Explorer suggests relevant information to make your exploration more useful. Imagine if you could build something similar inside your organization. Say your employee wants to launch a new product and your application suggests what the path to launch will look like; who’s encountered similar issues or the knowledge base articles they should read? Wouldn’t that be useful? Career Explorer exhibits the characteristic of the best analytical applications. They don’t just provide insights, they allow you to visualize a possible future and prompt you to act on it.
As I argued in my recent keynote at Predictive Analytics World, our world is becoming more analytical. And in this regard, LinkedIn is light years ahead of Facebook.
Where does your organization stand?
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