No One Is One-Dimensional
Conversely, it is very easy to update personas, as it is not much different from refitting the models one at a time. And we don’t have to update the whole series every time, either. Just watch out for the ones that do not validate very well over time. With real machine learning techniques around the corner, we can even consider automating the whole process, from model update to deployment of messages through every channel.
The hard part would be imagining the categories of personas, but I suggest starting small with essential categories, and then keep building upon them. Surely, teenage apparel companies would have a very different list than business service companies that sell their services to other businesses. Start with obvious ones, like bargain seekers, high-value customers and specific key product targets.
Connecting personas to actual creatives will require some work in the beginning, too. However, if you plan the categories with set creatives in mind from the get-go, it won’t be so difficult. Again, start small and see how it goes, along with some A/B testing. Ten categories will be plenty for many businesses. But having more than 100 personas won’t take up much space in supporting databases, either. Once the system gets stable, marketers can automate much of the process, as most commercial software can take these personas like any other raw variable.
So, if your marketing team is committed enough to have purchased personalization engines for various channels, get out of the old segmentation method and consider building model-based personas. After all, no one is one-dimensional, and everyone deserves personalized offers and messages in this day of abundant data and machine power. This is not 1984 anymore.
Stephen H. Yu is a world-class database marketer. He has a proven track record in comprehensive strategic planning and tactical execution, effectively bridging the gap between the marketing and technology world with a balanced view obtained from more than 30 years of experience in best practices of database marketing. Currently, Yu is president and chief consultant at Willow Data Strategy. Previously, he was the head of analytics and insights at eClerx, and VP, Data Strategy & Analytics at Infogroup. Prior to that, Yu was the founding CTO of I-Behavior Inc., which pioneered the use of SKU-level behavioral data. “As a long-time data player with plenty of battle experiences, I would like to share my thoughts and knowledge that I obtained from being a bridge person between the marketing world and the technology world. In the end, data and analytics are just tools for decision-makers; let’s think about what we should be (or shouldn’t be) doing with them first. And the tools must be wielded properly to meet the goals, so let me share some useful tricks in database design, data refinement process and analytics.” Reach him at firstname.lastname@example.org.