With shifting regulations, the impending demise of third-party cookies, and markets picking back up after the pandemic, there are new challenges and new opportunities to delivering the best customer experience. The good news is that most brands have a wealth of customer data that can help — it’s just a matter of putting it to use.
Data gives brands the opportunity to make intelligent decisions and foster bonds with customers on a deeper level. It’s the key to crafting effective strategies that make customers feel catered to every step of the journey. It’s also a way to troubleshoot common customer-centric problems while ramping up revenue in the process.
We’ve identified five of the most pressing customer challenges businesses face on a daily basis that can be solved with the right application of robust customer data:
Preventing customer churn
Nurturing your best customers
Converting one-time buyers
High-value customer acquisition
Promotion reduction
Read on to learn more about how to use data to address these challenges, leading to happier customers and increased revenues.
1. Preventing customer churn
Nobody wants to lose customers. Besides the fact that it doesn’t feel great, there’s also the hard reality that acquiring new customers is far more expensive than keeping old ones. With more brands in the market than ever before and higher consumer expectations for brands to cater to their needs, competition to keep customers has exploded.
The right analytic models applied to accurate, reliable customer data can help keep customers from leaving. Segment analysis can tell you which of your repeat customers are most likely to churn and when, based on how regularly they purchase. Work backward and figure out what will entice them to stay, guided by the principle that all customers are unique individuals. Instead of using a one-size-fits-all promotion, use automated 1:1 churn triggers based on each individual’s distinct purchase cycle to deliver them perfectly-timed messaging to communicate that you care about their experience.
2. Nurturing your best customers
The top tier of customers is extremely valuable to your business — the top 5% of a brand’s customers typically make up as much as 50% of their revenue. These are the customers who will readily choose your brand over a competitor’s, both because they love your products and services and because they feel a personal connection — maybe to the general vibe, maybe to the mission, or maybe to the way you cater to their needs, and often a combination of all of it. To create and nurture this allegiance, brands must consistently meet and surpass customer expectations.
Customer data can tell you which customers have the highest predicted lifetime value (i.e. the amount they will spend over an extended period of time) and point you to what special offers, perks, and products will appeal to them. Drive home how important they are to your company by serving those top customers with highly personalized experiences that make them feel valued. Instead of delivering the same message, personalize messages for each consumer on varying channels. For example, if you know your target customer has an affinity for high-waisted jeans, make sure high-waisted jeans are front and center every time they visit your website. If your data shows that your customer is highly engaged with emails, send them emails with information that’s personalized to them. First dibs on exclusive items, access to special events — all it takes is following the data to identify your most valuable customers and learn what they like.
Data gives brands the opportunity to make intelligent decisions and foster bonds with customers on a deeper level. It’s the key to crafting effective strategies that make customers feel catered to every step of the journey.
3. Converting one-time buyers
Having a customer buy once and then disappear is a frustrating challenge every brand faces. Acquiring a customer is only half the battle — turning your new customer into a repeat buyer is the real trick, as brands bring in the most revenue from repeat buyers. So how can companies encourage multiple purchases?
Using the data you have available on first-time buyers, identify their personas and then decide what might bring them back. A great place to start is right at the beginning, with follow-up offers and communications. If you serve the customer a compelling welcome series, they’re far more likely to make another purchase. A one-size-fits-all welcome email is a missed opportunity. A far more successful method to drive repeat purchases is by personalizing the welcome series across channels. If a customer bought a pair of hiking boots, follow up by serving them ads for active gear on their preferred channels, then send them an email containing hiking tips.
4. High-value customer acquisition
All customers are not created equal — some may make one small purchase and never buy again, while some will make many big-ticket purchases over the course of months or years. Given the cost of acquiring customers, focusing on finding the ones who resemble your current best customers is a winning strategy.
Doing this starts with knowing who your best customers are. Rich profiles with a range of data including demographics, geographics, psychographics, product preferences, and other historical and predictive attributes like average order size and lifetime value can be used to make lookalike audiences as a basis for finding similar customers. At the same time, good data hygiene can make it easy to ensure that acquisition efforts don’t include existing customers (since nobody likes to receive an offer for something they already have).
5. Promotion reduction
Almost every company has fallen into the promotion trap. It starts off innocently, with a few promotions here and there, then quickly plunges into a promotional downward spiral. Excessive discounting to encourage immediate sales only trains customers to wait for the next promotion, discouraging any future full-price purchases.
The remedy for this problem lies in your customer data. Instead of offering every single customer the same discount, identify the price and promotional preferences your customers have based on past behavior and predictive models. Break your audience up into segments by discount preference and run some tests to see what works. Customers who only buy on discount should receive promotional offers, but with a few variants so you can determine the least amount of discount that will still encourage them to buy. Customers who typically pay full price, on the other hand, represent a segment where you don’t need to offer many promotions, and can reserve it for times when you really want to make an impression.
The foundation under it all
Of course, to tackle any of these problems requires a solid foundation of customer data. It can be tricky to know where to start when trying to drive value from customer data, let alone getting the data into a place where you can even use it. This is where a Customer Data Platform (CDP) comes in.
A good CDP will help make sense of chaotic data, turn it into valuable insights, and fuel personalized marketing campaigns and brand experiences that customers come back for. The first step is getting access to accurate data, followed by deriving intelligence from it. Based on those insights, plan the campaigns and experiences you’ll use to serve your customers and then tweak and refine based on what is or isn’t working — the results of those tests feed back into the customer data foundation adding in new findings, creating a loop toward stronger personalization and deeper customer satisfaction. Today, personalization is just table stakes, and brands that don’t cater to that demand risk losing customers. Even when marketers work off of customer behavior, the data is often so convoluted or difficult to access that it’s easy to miss the best opportunities. Look for a CDP that’s purpose-built to help leap over hurdles in customer-centric marketing by providing access, insights, and connectivity to the right downstream tools to power personalization at scale.
Interested in learning more about using data to personalize your customer experiences? Check out our guide.