One of the biggest benefits of big data comes from a marketer’s ability to segment customers.
That is because customer segmentation allows brands to reach a specific audience in the right place, at the right time, with the right message to engage them in your offer. Such specificity generally means more conversions and better returns on your marketing campaigns. However, as with almost any great luxury, even marketers need to ask themselves:
Even though marketers report a 760 percent increase in revenue from segmented campaigns, the answer here is a definite “yes.” Segmentation works, but only when the division between buyer personas actually warrants its own approach.
This post shows you how to properly segment your customers, including how to know whether you have not done enough segmenting, or if your approach is just too much.
Step #1. Know Your Goal
Though your buyer personas will be different, the goal of your campaigns should be the same. Whether that is converting leads to new customers, upselling existing clientele, building brand awareness, or reducing churn risks, you need to know what it is you hope each of these segments will accomplish. Why?
Because when it comes time to look at the data in your data management platform, it will be easy to start drawing arbitrary lines between potential customers. Just because two customers live in different cities does not mean they represent their own individual segments.
With the wealth of data available, it is easy to get caught up in “slicing and dicing” your customers into buyer personas that do not make sense for your overarching goal. If the aim is to generate new leads, ask yourself how important it is to differentiate messaging between leads in Oregon or California. (Chances are, it will not be worth the extra costs.)
Step #2. Start Broad, Get Narrow
Over-segmenting can be a cyclical problem. Because datasets are smaller when you are working with more buyer personas, it becomes difficult to understand where the problem lies with your campaign. Often, marketers will continue to over-segment in an effort to resolve the issue but instead perpetuate the problem.
The right approach here is to start with fewer segments and narrow your focus as you accumulate more data. Launching a campaign with three segments, for example, gives you the opportunity to see the impact of your campaigns among three separate groups. When measured against one another, the performance of those three campaigns can be very telling. You might realize that a poorly performing campaign has the opportunity for further segmentation, or that a successful campaign might also make sense for a similar audience. Start broad, collect your data, and make intelligent decisions.
#3. Experiment, Measure, Iterate, and Repeat
In today’s data-driven marketing world, finding opportunities for creativity can often feel rare. But the key to successful segmentation is to be constantly testing new things to see what sticks. New channels, new messaging, new delivery times, new CTAs — all are opportunities to get creative and learn more about your target audience.
The key here, though, is that you need to be collecting and unifying your data to continuously improve your experiments. That’s where ReachForce comes into the picture.
ReachForce helps marketers increase revenue contribution by solving some of their toughest data management problems. We understand the challenges of results-driven marketers and provide solutions to make initiatives like marketing automation, personalization, and predictive marketing better. Whether you have an acute pain to solve today or prefer to grow your capabilities over time, ReachForce can unify, clean, and enrich prospect and customer lifecycle data in your business, and do it at your own pace.
To learn more about how ReachForce can help you optimize demand generation and your impact on revenue, get a free data assessment.