Persona Marketing Tricks
How does a marketer go about creating the most effective set of personas? The first step is to create the 360-degree customer view out of available data. Personalization must be about the person, not about channel, product or even brand.
For that, all event- and transaction-level data must be rearranged around the target individuals. Often, this data step turns out to be the first major hurdle for the marketers.
Then marketers, along with data scientists, should draw the list of required personas. After all, all analytical work must start with a clear definition of targets, and the targets must be set with clear business goals.
If you could ask for any personas for your marketing efforts, what would they be? Surely, the list would vary greatly depending on the lines of business that you are in. Obvious ones — such as “High-Value Customer,” “Frequent Shopper” or “Online Buyer” could be helpful for all types of retailers.
Going beyond that, marketers must expand their imaginations and think about the list from the customer’s point of view, while keeping a sight on the products and services that are to be offered to them. We must look at this as an ultimate “match-making” exercise between the buyers and the products, way more sophisticated than a rudimentary product-to-product level match (as in “If you purchased product A, you must also be interested in product B”).
The idea is to create personas imagining what you are going to do with them in marketing campaigns. “Frequent Flyer” maybe an obvious choice, but would you need a related but different one called “Frequent Business Traveler”? Would you extend the “Young Family” to “Avid Theme Park Visitors”? Why not both?
For B-to-B applications, we can think of many more along the lines of a “Consumable/Repeat Purchase” persona and “Big Ticket Items,” but the idea is to have both of them on the menu, as one may reveal both types of traits at the same time.
Similarly, if you are in a telecommunication business, what would be a good set of personas for broadband service? What type of personas can explain the “why” part of the equations? Simply for the sales of broadband, we can think of the following set as a starter:
- Big Family
- Home Office
- High-Tech Professional
- Avid Gamer
- Avid Movie Downloader
- Voice-over IP User
- Frequent International Caller
- Early Adopter
- Etc., etc.
The key is matching the propensity of a customer and the product, and showing compelling reasons why they need to purchase a particular product. We all routinely consume all kinds of products and services, but each of us does it for different reasons. Personalizing the message based on known or inferred personal traits is the key to stand out in the age of over-communication.
Once we imagine the list, there are ways to build the personas. I can say that with conviction, as I’ve seen a persona called “NASCAR Fan” being used in an election season. So, don't be shy and start being creative on your whiteboard today.
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 email@example.com.