Originally Published in Retail Customer Experience
Written by Mark Smith
Companies today are swimming in customer data — data on their preferences, online behavior, buying patterns, and much more. While sourcing all relevant data into one place can present brands with real challenges, in principle, every company has enough data at their disposal to create fairly detailed customer profiles. What’s more, with the right analytics tools, you can even extrapolate from this data to generate maps of buyer journeys and ideal customer profiles for more effective targeting.
However, as valuable as this historical data can be, the most important customer action isn’t something they did in the past. It’s what they are going to do next. Companies strive to predict these next steps based on behaviors that resemble models of customer behaviors (customers who did x and y often do z) or by trying to infer intent from specific behaviors (customers who visit product review websites may intend to make a purchase in the near future). But how effective are these models at predicting what next steps a customer might take?
Some claim it can be very effective. And a raft of vendors have sprung up offering, at least in their view, actionable insight into your customers’ next moves. When you take a closer look, of course, what these vendors offer is little more than inferential clues regarding where a customer might be in their journey. We see this particularly in the B2B world where review sites and sites specializing in content syndication essentially sell visitor and download data as signals of intent.
To be fair, this may be adequate in a B2B scenario. Buying cycles in B2B are more drawn out and research is a critical part of the buying process. If you see someone doing research, it’s not too great a leap to infer that they are “in market.” Individual consumers, on the other hand, don’t have procurement standards or approval chains slowing down their purchasing decisions. The purchases they make can involve research, to be sure, but they are more likely to be impulsive or, at best, habitual. Without an in-depth understanding of customer journeys or a comprehensive framework to measure them, defining intent can be a formidable task.
Read the rest at Retail Customer Experience: https://www.retailcustomerexperience.com/blogs/solving-the-intent-data-problem-with-journey-management/