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We all know that stories animate human behavior, including B2B buyer and user behavior. And yet the overwhelming wealth of quantitative data available from cloud and SaaS applications and platforms has pushed product people out of their story element and into the realm of data. While this isn't bad in itself, all this data offers an incomplete and inaccurate picture for competitive marketing, competitive intelligence, product marketing, and customer success teams.
I've been working in the world of stories, specifically buyer and user stories, by profiling B2B wins, losses, churn, retention, up-sell, cross sell, and downgraded behavior, for just over 10 years. I firmly believe in the importance of buyer stories in order to understand markets, but stories do have a problem: They are hard to compare, slice, dice, and develop a coherent picture. In a world where data is so readily obtainable, stories become dismissed by way of anecdotes, and written off as opinion.
But we need stories. If you have spent even a day with data scientists analyzing user behavior, you will know that they test hypotheses through iteration and experimentation, which amount to stories. And they often hit limits of what the data explains. There is more to user and buyer behavior than what the data provides. We need to understand the "Why people change?" motivations, not just the changes that they make. We need to understand perceptions, and not just the actions that result. It's only through stories that can provide the answers to these questions.
My view is that story and data need to be in continual dialog. Your data will help me ask better questions; my stories will help you conduct better experiments. Yet we come back to the challenge of stories: They live in a "flatland" of transcripts and excerpts. How can we analyze and compare stories to look for broader narratives that will help us segment markets and understand segmentation behavior?
We at Eigenworks have cracked the code on this, and we want to share our ideas with you. After 10 years of analyzing buyer stories (via win/loss analysis, churn analysis, and other in-depth interviews / analysis in B2B), we have developed a model for buyer decisions that you can use. That's right! You don't have to hire us to use our model. We are publishing our model with an easy-to-use UI that allows you to start codifying stories in your market.
Here are a few highlights of the story workflow:
Focus on decisions by interviewing buyers using a structured yet not scripted dialog.
Extract "nuggets" of insight from the dialog. These nuggets become the unit of analysis on the decision. Many of the nuggets exert a "force" on the decision, which could push a buyer or user in different directions. Some forces will compel a purchase, while others could deter it.
Divide the field of play into both experiences and outcomes. There is a buyer and customer experience. There is also an envisioned outcome ("vision for change") and customer outcome.
Develop a set of themes around why people buy (or stay with their status quo). This answers "Why change?" and "Why you?" when a customer chooses your product over a competitor's product.
With enough stories parsed in this fashion, a highly structured data set emerges. I'm hitting the road over the next few months to share this idea with product teams across North America. The first big reveal of the idea will be at the Competitive Marketing Summit webinar coming up next week. I hope you'll join us, and help us give stories a seat at the table with big data.
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Here are your first steps:
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