Planning in High Heels

Posts Tagged ‘data

Why it’s time to stop thinking about the consumer and start thinking about the network.

Two things happened this week that made me realise just how redundant it is today to think about a single, individual consumer.

First, I had a briefing on a new project. Some lovely (and smart) people had done some thinking on the consumer-the classic pen portrait. They’d thought hard about it and they’d done their research but I found myself thinking that it didn’t tell me what I really wanted to know. While they were telling me about the individuals, I was thinking about the network. Asking myself:

  • What content are these people sharing?
  • Why do they share it?
  • How do they share it-active endorsement versus more passive sharing (ie via social plug-ins)?
  • Where do they share it?

The brilliant Griffin Farley has already touched on some of these questions in his excellent thinking on propagation planning. As he so pithily puts it, “plan(ning) not for the people you reach, but for the people that they reach”. If you haven’t checked out his excellent presentation, I strongly urge you to do so. It’s one of the most useful pieces of thinking I’ve come across on influence and social spread.

So what do I have to bring to the propagation party? Well, while influencers are undoubtedly important, I think peer to peer networks may be even more so. Or perhaps the point is that everyone is an influencer today-albeit to varying degrees. There is no-one we talk to today (hermits and Trappist monks excepted) who doesn’t exist within a network-and the shape, structure and dynamic of that network may just be the most important thing for marketers to know about them. More important, perhaps, than demographics, attitudes or psychographics. As Mike Arauz puts it, in another wonderful presentation, “The effectiveness of our work is dependent on our ability to engage and empower networks of people connected by shared interests”.

To take this a step further then, perhaps we should stop producing pen portraits of individuals and start providing a portrait of a network:

  • How big is the network?
  • How loose (or tight) are the connections?
  • Are those connections symmetric or asymmetric?
  • What fuels those connections-friendship, a shared cause, shared interests, altruism, personal gain?

From consumer insights to network insights

The second thing that happened is that, having developed a campaign recently around the principles of social spread, a client, not unreasonably, asked how we could be confident that it would scale.

We had a high degree of confidence, no question. We were targeting a highly creative, motivated community-and each member of that community had his or her own fanbase. The core community-and their fanbases-would be actively incentivized to spread the word as far as possible within their personal networks. With luck, it’ll be awesome….

Yet, perhaps inevitably, it’s hard to predict exactly how the campaign will spread. Of course there are some norms we can apply around the number of connections in the average social network and around users’ propensity to interact with content shared by friends or by brands in social channels.  We can use the most robust and predictive data we have. However, we still lack quantitative planning tools that truly reflect the networked consumer. We have vast quantities of data that will tell us what the average 18-20 year old guy is watching or reading but not nearly as much data on what they’re sharing, spreading, using or participating with. We have isolated incidences, greatest hits and occasional case studies of course.

We have very limited data on how sharing varies across different kinds of networks-asymmetric vs symmetric, loose ties versus strong ties- although what we have is fascinating-this presentation from Luke Wroblewski is a must-read for my money. Interesting data is also emerging on why users share content and how this varies across the globe.

However, we still lack a consistent, robust and continuous data stream we can use for forward planning. So perhaps the next generation of planning tools-tools for both account and media planners (if that distinction remains in 5 years time) need to reflect the next generation of planning-planning for the networked consumer. Whoever captures, owns, understands and uses that data will have an extraordinarily powerful tool at their disposal.


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