Are your segments providing better and more relevant personalized customer experiences?
Most companies rely on segmentation for more targeted marketing, but it’s not effective in reaching consumers on a personal level. Even though marketers are relying more heavily on demographics and other attributes to develop targeted messages, they're still not individualized enough to compel each customer into action.
But providing better and more relevant personalized experiences can pay off in many ways. For example, better-personalized experiences lead to deeper customer engagement, which encourages loyalty. And loyal customers are long-term customers, which increases a brand’s customer lifetime value (CLV), resulting in more predictable and incremental revenue. This also means that a brand isn’t churning customers or having to re-acquire customers who have already churned. After all, as most of us understand, the cost of re-acquiring a customer is much higher than the cost of retaining an existing customer.
Consumers want a personalized experience, and they’re not getting it. For example, say someone is a rewards member who shops at a high-end retailer a few times each year and spends a significant amount of money to refresh their wardrobe for an upcoming season or to buy a fancy outfit for a big event. Yet the retailer keeps sending the shopper $20 off coupons, which is completely out of line with how much money they spend during each purchase. Because this shopper is a loyalty member the brand can track all purchases and the customer is likely part of a segment, yet there is no personalization of what is sent or offered. This experience does not recognize how important this shopper is to the brand, and leaves the shopper at risk of choosing another brand to do their shopping.
Brands know they need to create better personalization for their customers, to alleviate the issues outlined above. Unfortunately, most of the segmentation tools brands are using to create those personalizations are only creating incremental improvements. Today’s tools are not providing the value or end state that consumers are demanding.
Most personalization tech is only focused on creative personalization and not the actual promotional components of an offer, while micro-segmentation or smart segments are still connecting consumers to mass offers. Let’s dig a little deeper into what those tools can actually personalize, and why it's not enough.
Source: Marketing Insider Group
One approach to personalizing generic brand communications is to increase the number of customer segments and tailor messages to each of those segments. Simple macro segmentation often includes first-party attributes such as gender and age as segmentation attributes. As we continue down the spectrum towards micro-segmentation, attributes such as occupation, relationship status, household income, and geographic location might also be incorporated.
This approach poses multiple challenges. First, brands must gather, analyze and keep all customer data current. Second, as the amount of data being used to customize brand communications grows, it generally increases the cost of developing and managing copy and creative assets.
Most brands realize that the cost/benefit of this approach reaches a breaking point long before they’ve collected enough data to truly treat customers as individuals. Collecting customer data on even 10 unique attributes into three distinct categories results in over 1,000 segments, and then brands have to decide which of those attributes to focus a message on.
Drilling down a bit on smart segmentation, how does a brand best deal with the challenge of managing different interactions with each of thousands of segments? Brands really can’t do it well without some sort of machine learning or AI tool. Many tools, in fact, now exist to address exactly the problem of choosing which attributes are likely to be the most important to a customer. Smart segmentation consumes all available data and determines exactly which attributes are most important for effective segmentation.
When you’re looking at smart segments, we as humans still need to write all of the copy and decide what to offer that segment. So, without a machine supporting the personalization, smart segments are merely getting the same types of offers. They might just be focused on women’s clothing versus men’s or align to a season based on geo.
With smart segments, perhaps brands are able to create some 50 kinds of offers rather than just 10, but it is still not scalable with just people managing the process. That means that customers are still getting a static offer, though it’s probably slightly more relevant than the offers from a brand that isn’t even segmenting their customer base.
With smart segmentation, brands consume all available customer attributes with a range of values for responses, potentially resulting in thousands of segments. Accounting for all information known about a customer is an important step toward truly personalized interactions. However, the challenge of managing different interactions with each of these segments remains.
The approach of using “customer journeys” as a guideline for managing customer interactions relies on using key milestones as triggers for specific communications. For example, downloading a merchant’s app might be designated as a signal to offer a discount on the customer’s first app-based purchase. Completing a tenth coffee purchase might be designated as a good time to send an offer for a free product.
Using journeys as a guideline for customer communications can be used with or without additional segmentation data but still leaves some major challenges unsolved. Customer journeys on their own assume that all customers will interact with the brand in a similar, predictable manner. Customer journeys with segmentation may leverage some of this individuality but can add further complexity both for the number of rules a brand employs and the volume of creative or copy assets that must be managed.
Ultimately, despite the best efforts of brands to create personalized messages and offers, the consumer is often left with the same poor experience. Offers are transactional, and brands are losing market and wallet share as a result. In fact, 66% of consumers say the offers they receive are not relevant. What is the underlying reason for this disconnect between brands and consumers specific to offer relevancy? Simply put, brands are not offering what consumers want.
According to Forrester's research, customers are focused on value, while businesses are focused on promoting their products and services. Brands must realign their offer strategy to focus on what is most appealing to their customers. Using analytical resources to optimize at scale, brands can build and execute a personalized offer strategy that delivers business results through high-quality and relevant offers.
Segmentation still has a role in the world of personalized offers and experiences, but it's a very specific role, and it's not what companies are using today. That’s because current micro-segmentation or smart segments are still connecting consumers to mass offers. This process isn’t creating personalized experiences, but it is creating unnecessary complexities for loyalty marketers as well as creating confusion for brands on the real impact of their programs.
Where brands do need to invest time and energy is creating large business segments within which they can organize campaigns and broader corporate objectives. For example, broader audience segments such as net-new customers, brand advocates and lapsed customers should be clearly defined. That way, a company can track how well they’re doing at re-engaging lapsed customers, how much revenue they’re driving from brand advocates, and what percentage of net-new customers convert into brand advocates vs. how many of them lapse.
With these large segments, marketers can apply AI and machine-learning platforms to automate the dynamic offers and personalized experiences that consumers demand. One platform that can help your brand accomplish this is Formation.
Formation's Dynamic Offer Platform (DYNO) can help your organization transition from mass to dynamic offers. Whether you are a loyalty marketer, product leader, data scientist, merchandiser, or driving your organization's digital transformation to dynamic offers, Formation accelerates this process by providing greater insights that grow customer loyalty, using patented and proven machine learning technology that drives business outcomes.
The future of segmentation will enable marketers and business leaders to focus on long-term strategies to improve their business results and then design programs that achieve key growth objectives. Make sure your brand is optimized to succeed by checking out Formation today!