Companies create buyer personas to simulate their ideal customers. We used to build them by imagining broad demographic details about who we thought would be the perfect target for our products and services. That idea would then get fleshed out through surveys and customer feedback to create a more accurate picture.
Unfortunately, customers are demanding personalized services. They want to believe that a company is catering to them on an individual level. This means that a content strategy with broad buyer personas will only get you so far. How would we ever get all the data necessary and the ability to process it to create these powerful brand experiences that customers now crave?
The answers are Big Data and AI integrated with your content strategy. These two tools are the next level up in creating buyer personas that are more granulated and powerful than ever before. Here are just a few ways that are happening.
Big Data Analysis of Behavior and Demographics
The ability to chew through massive amounts of data to draw out insights is the critical skill of artificial intelligence applications like CONCURED. We generate far too much data for any group of humans to sort through it all. Every insight that is drawn out of the larger pool of customer data can be fed back into right personas or split into new ones. This feedback loop allows companies to do fast iterations of their personas and their approaches to them to see what works best. Eventually, we may have enough public data on ourselves in the cloud and accessible to brands that we won’t need buyer personas. Companies will just be able to look at the profile and know where to go from there thanks to AI. Imagine that!
The best way to learn about an individual customer is to talk and engage with them directly, right? Chatbots allow companies to not only provide customer services at any time, but also to collect data about individual user reactions. Consider, for instance, if you asked for a small piece of information in the course of small talk with the customer after a transaction? The chatbot could easily add that to that customer’s profile. These little pieces of information can be used to flesh out personas and improve content.
The best recommendation engines allow customers to send feedback about what they like or don’t like. Amazon and YouTube are excellent at this. You can dangle an offer in front of your audience in their recommendations and see how many pounce on it, how many ignore it, and how many tell the engine to stop showing recommendations like that. This is powerful feedback from your customers about your product offerings.
Audience Lookalike Tests
This is a technique that Facebook is pioneering. They are taking the audience you have now for your ads and then a bit more information about customers you’d like to target that you aren’t currently reaching. Facebook will take all of that and find people who match the qualities of both camps. This is called a lookalike audience. What this means is that you can experiment with buyer persona qualities that may be a little more out of the box than you are used to using without too much risk. If Facebook can master this technique, it will open a whole new world of audience targeting.
If you are still using educated guesses and manual surveys to build your buyer personas then you are missing out on some very powerful tools. For more information about how you can use content marketing to reach your personas, check out our latest ebook at this link.