NEW YORK – Long ago, I used to run a conference called PC Forum. People would say to me, “If only I could sit next to Bill Gates....” Just last week, a friend pulled me aside at a conference to ask for advice. “What’s the best way to make conferences more efficient for meeting people?” he asked. “Just like marketing, it seems it’s only about 50% effective.”
He was asking the wrong question. The interaction has to be two-way: Do other people really want to meet him?
A conference optimized to help my friend would fail, because the people everyone wants to meet are unlikely to show up. Indeed, does my friend have a right to their time? He told me that he had actually sat in a breakout group with 20 people, each of whom he wanted to meet, but he managed to talk to only two of them. I was a bit concerned. Was this guy I was trying to help actually a stalker?
What he wanted was a tool that would allow him to make contact with each person on the list of people he had picked out. This is probably a legitimate goal – he sells decent products – but the reality of the world is that relationships, even around so-called shared interests, are not necessarily symmetrical.
More people want to meet Bill Gates or Marissa Mayer than vice versa. If we were to create a real market, it would become unpleasantly commercial – a bit like those charity auctions where celebrities or tycoons donate the pleasure of their company for lunch with the highest bidder, except that the VIP pockets the money.
At yet another conference, I was musing about how to make introductions efficient but not transactional when I was introduced to Lisa Anderson of Werqit by Megan Smith of Google. That was a useful signal. Anderson did not just approach me on her own; she was introduced.
It turns out that Anderson is working on the answer to precisely this problem of asymmetry in introductions. The trick is not just to find the right target (that is, a person), as social networks such as LinkedIn and search tools can do, but to enlist allies and manage a campaign to achieve a specific goal with the ultimate help of, yes, the target. Werqit’s workflow solution does a good job of discovering, through social activity, who is likely to help you – and, just as important, who will probably brush you off.
In other words, the behavior her startup looks for is not purchasing behavior (like so many “social” tools), but actual social behavior. Werqit plans to build a “collaboration graph” by looking not only at ability to help or collaborate, but also at indicators of willingness.
Willingness reflects a complex mix of incentives influencing when, whom, and how to help – and also reflects how busy a potential ally or target is. (As in any market, you need to consider not just your targets, but also who is competing with you for their attention.) The indicators of willingness might include the frequency with which someone engages with a particular person; how often people are asked (or overloaded with requests) for help; the types of requests they accept; which topics they engage with, and with whom; and what kind of help they give.
Werqit uses these indicators to suggest who in your network is likely to be most helpful in the context of a particular mission or goal, enabling you to enlist them as allies. Then it helps to figure out whom to target to achieve that goal – whether it’s funding for a startup, a job for yourself, a sale for your product, a publisher for your book, or any other mission you can define (and add to a crowd-sourced collection).
The service, currently in beta, is not an app; it is a full-featured workflow tool that will use machine learning over time. The premise is that willingness to help is influenced not just by connections, but also by the kind of connections and by the requester’s ability to formulate a clear and specific request. Clearly, Werqit is both a flattering compliment (and complement!) to LinkedIn and a competitor for what LinkedIn does only in part. LinkedIn provides “introduction” workflow, but Werqit includes mission-specific templates and a curated collaboration graph for finding allies.
Currently, Werqit relies on what it can glean from public data and the user’s own Facebook, Twitter, and LinkedIn interactions. Over time, it will develop its own database of users.
This is the first new tool that I have come across whose creators seem to understand that the problem is not simply to find the right people; it is to run the right process to succeed at a specific task with the help of those people.
Consider my own interaction with Anderson. I frequently advise people who approach me without an introduction that they should start with someone who knows them, not with a stranger they would like to know.
Even at a conference, that is good advice. Maybe my friend was lucky to speak with only two of the 20 people in his breakout group. As Werqit’s Anderson knows, the most effective introductions are those made by others.