Everyone knows all the usual suspects for customer segmentation. Easily collectible demographics data such as age, gender, and location. Are easy wins for companies looking to personalize their marketing materials. In the next few years, the tools that we use for segmentation. Will give companies an even more significant understanding of each customer on an individual level. Machine learning and automation are increasingly being used to improve data analysis. These tools will quickly become the norm for any digital business. Still, there are some common misconceptions about the best practices for segmentation.
In this blog, I’ll show you five factors to consider before you begin segmenting your customers.
Customer Behavior is Just as Important as Customer Details
Effective segmentation digs deeply. It involves an analysis of customer behavior. Not just quickly available data like customer details. What actions are customers taking once they hit your website? Do their actions resemble those of other customers. Does there seem to be a trend. Not many brands dive into segmentation as customer actions as thoroughly as they should. For example, many companies sort customers based on who abandons their cart on ecommerce sites. In these cases, companies might offer a discount or reach out to ask if they. Had any questions about the product.
But what if you segmented that group even further. Further segments could include those for customers who never entered their credit card information, customers whose credit card has been denied, or customers who failed to enter a single detail after adding a product to their cart. By tracking and sorting customers based on their behavior on your site, you can better inform your marketing materials and customize your messages for each customer type. You can then design your landing pages to target specific customer types. Landing page builders like Unbounce are helpful tools for this since they let you design your landing pages and other marketing Qatar Phone Number materials according to your segmentation of customers.
Automation and Machine Learning are Inherent Parts of Effective Segmentation
A big reason so few brands haven’t used segmentation to its full potential is that sorting through all that data can be tedious. It can take days to sift through data by hand and properly adequately categorize each person to ensure your assessments are accurate. And accuracy is important here: you wouldn’t want to send out customer emails only to find that you have miscalculated or missed a data point.
Automation and machine learning have re-shaped digital marketing and segmentation in particular. An excellent engagement platform can provide hyper-targeting that examines the customer journey and then automatically optimizes your marketing materials for specific customer types, helping you interact with customers on a more personal level. These tools will become the standard for all brands doing serious business online, simply because of the added value they provide.