Customer segmentation is a necessary part of the marketing strategy for any industry. Demographics like age, gender, and location provide easy wins for companies looking to personalize their marketing materials.
In the next few years, the tools that we use for segmentation will give every company a greater understanding of every customer on an individual level. These tools will quickly become the norm for any digital business looking to improve their data analysis.
Still, there are some common misunderstandings about the practice on the whole. Before diving in head-first, consider these five factors:
Customer behavior is just as important as customer details
Effective segmentation digs deeper. It utilizes customer behavior, not just your run-of-the-mill data. 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?
We do see segmentation by customer actions, but few brands dive into it as deeply as they should. Many companies sort customers based on who abandons their cart on e-commerce 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 have never entered their credit card, customers whose credit card has been denied, or customers who have never entered 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 custom-craft your messages for each customer type. You can then design your landing pages to target specific customer types. Many landing page builders, such as Unbounce, let you incorporate segmentation into your landing pages and other marketing materials.
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 because sorting through all that data can be tedious. It can take days to sift through data by hand and properly 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. Tools like Optimove’s software 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.
Micro-segmentation builds relationships
Customers love brands that understand them. That’s why it’s so important to speak to their pain points in every piece of marketing that we create. Customers want to know that companies understand their needs, pains, and desires. They also want to be assured that the product you offer will solve their relevant problems.
Micro-segmentation is about sorting your customers into more specific categories. In typical segmentation, you might have customer segments based on who lives in Denver, who has a job title of Vice President, or who is above the age of 50. An example of a micro-segment would be a segment that includes all 3–50+ year old VPs who live in Denver.
According to an Infosys survey, 78% of customers stated that they’re more likely to buy from a company that sends them more targeted offers. Building that initial trust is incredibly important — customers who have been buying from a company for 30 or more months spend 67% more per order than they did on their first purchase.
Micro-segmentation gives you the opportunity to speak to their biggest concerns and win their trust by helping them to address them.
Segment research should inform product development
At its core, segmentation begins with learning more about your customers. The more you know about your customers, the more you can tailor your marketing to their unique problems, preferences, and desires.
Startups often pivot to find a market that needs solutions. But once a company is sufficiently settled within their market and earning a healthy profit, they often shift their focus to other areas of their business.
While no established business is going to do a full-fledged pivot in the same way that a startup would, many could benefit from more customer data involvement in product development.
Segmentation data should go beyond marketing; it should also be used to inform product development. Great customer data is the most powerful tool that companies have available to them, but too many continue to operate based on perception rather than data-backed facts.
Customer journeys and segments are not static
Another big mistake that brands make when segmenting is that once a customer has been placed in a segment, their analysis stops there. These customers will forever remain in that segment — even if additional data is collected in the future.
Customer segments can and should change over time. Today’s customers may be in a completely different place in life than they had been a year prior. Continually working to correctly categorize your customer types will make all aspects of your marketing more effective.
Personalization is the future
Deep segmentation of your audience gives you more opportunities for personalization. It allows you to gain a deeper analysis of each customer and their specific situation and to tailor your sales and marketing efforts specifically to them.
While segmentation itself isn’t a new concept in digital marketing, the tools that we have available have allowed for micro-segmentation to become affordable for companies of all sizes.