Illustrating the WOM ripple
By Molly FlattA WOM ripple can be defined as the spread and exposure of a piece of conversation or content across online and offline scapes, as it is relayed, repurposed and used to inspire further conversations. There’s lots of commentary devoted to identifying effective ripple triggers, such as the whitepaper on Spreadable Media I mentioned yesterday; key qualities include the relevance, creativity, adaptability, originality, informative value and emotional engagement of the trigger, as well as who is distributing it, where, and why.
However, it can be notoriously difficult to help clients envisage exactly how that conversational trigger then ignites in the space, accelerating through search; social networks, communities and interconnections; and aggregation, distribution and bookmarking tools. With the right software and research layer, it’s possible to measure the numbers, but it’s still tricky to illustrate the extraordinary, unexpected and synaptic spread of ideas and images across a host of different communities and scapes.
For example, brands rarely take into account offline visual cues. Mike R relates the story of his new jet-powered car cleaner, which quickly appeared on several driveways on his street without him uttering a word of recommendation to anyone. We’ve all had similar experiences; I’ve been looking for months for a pair of boots I saw on a girl walking down High Holborn. Any truly pervasive word of mouth project should be finding ways to tap into these incredibly powerful offline triggers and platforms for the WOM ripple, even if they’re a little less definable to a CEO.
The concept of the Social Graph has historically been used to examine personal interconnections online, and Beth Kanter’s new post The Conversation Graph: The Social Life of A Blog Post attempts an update by examining various tools that track the journey of a piece of content. But there’s still no clear illustration of how a trigger spreads both on and offline, with all the corresponding complexities and unexpected factors that invariably pop up when you’re dealing with human behaviour - not least the fact that content spreads between people who aren’t visibly connected.
To accompany the quantifiable figures, there’s a real need for some in-depth case studies, taking individual examples of a product, service or brand experience and tracking in minute detail how it spreads. This should use social media measurement tools but also interview and examination of the family, community, social context and behaviour of the person involved - as well as where, how and if it translates into a sale. Watch this space.
