This Valentine’s Day, are your customers ready to make a serious commitment or is their love for your brand just a fleeting infatuation? To build meaningful relationships with customers, marketers need to strategically leverage their customer data to gain insights into things like a customer’s total lifetime value, future needs and likelihood to stick around. If you want true, til-death-do-us part customer loyalty, here are a few marketing strategies we recommend to build long-term customer relationships.
1. Start with Genuine Conversations, Not Sales Pitches
Imagine if you were on a first date and your companion suddenly started talking about all the ways you could “optimize” your relationship or shoved their new Etsy product in your face before the appetizers even arrived. When someone starts the conversation off with what you can do for them, it's pretty obvious that they don’t really have your best interests at heart.
Nothing turns a potential customer off more than an irrelevant and impersonal sales pitch. People today don’t want to be “targeted;” they want brands to speak to them like human beings. For a brand to build trust with their audience, they need to move beyond generic marketing phrases and cliches and communicate in a way that takes into context the whole of a customer's experiences, not just a single point of conversation. The customer journey today is a long, winding path as people move between online and offline channels conducting research, comparing shipping speeds, watching video demos or reading reviews from their friends on social media. Very little of the time is spent on actually buying, so brands should design content and experiences that take into account the entire picture.
Global chocolatier GODIVA has mastered the art of sweet-talking customers with personalized messages, such as customizing welcome emails for new customers and sending existing customers personalized reminders and notifications for items they’ve previously added to their wish list or shopping cart. These special touches have a greater impact than a generic “buy now” email blast.
2. Make Customers Feel Special with Exclusive Experiences
We all want to have relationships with people who make us feel like we matter. Little things like remembering your preferred ice cream flavor or sending a funny video from your favorite movie when you’re having a bad day, show that a person is paying attention and cares about you. For marketers, effective personalization, such as exclusive promotional emails for VIP program members or event notifications specific to geo-location, have a greater impact on a customer’s likelihood to engage with a brand and return in the future.
For example, speciality tea retailer DAVIDsTEA runs a “Frequent Steeper” loyalty program for customers and uses a customer data platform to identify high-value customers and personalize the types of messages that are sent to each audience. For example, their website offers different sample boxes to customers who have shown interest in fruity teas vs. black tea. The program also offers gift options for non-tea drinkers who may want to give a subscription to a friend or family member.
Recently, with fewer in-store sales due to the COVID-19, pandemic DAVIDsTEA launched a personalized digital subscription service, the Tea Tasting Club, where customers can select from a variety of teas and accessories based on their preferences (health, sleep, taste, etc.) and enroll in the service either for themselves or someone else.
This is an example of a smart first-party data strategy that mutually benefits both the brand and the customer. DAVIDsTEA encourages their audience to give them direct insight into their own preferences and needs, while offering ongoing value in the form of quarterly subscription boxes that generate long-term loyalty.
3. Understand What Your Future Customer Needs
One of the best life lessons my parents taught me after 30 years of marriage was that the strongest relationships are ones where someone doesn’t always have to ask for the support they need; it’s automatic. Think, would you rather have your partner clean the kitchen after multiple reminders, or already have the chore taken care of before you get home?
Today, marketers have access to machine learning models that can help them more efficiently and accurately anticipate a customer’s wants and needs. For example, fashion brand Lilly Pulitzer applied predictive machine learning models to their customer data to better understand how different age demographics preferred to shop. Lilly Pulitzer used behavior propensity models to identify where, when and how often customers were engaging with the brand and identify those who were at risk of churning. By unifying data from their CRM, in-store purchases, social media platforms and other channels, Lilly Pulitzer recognized that the shopping behaviors of their millennial fans differed from older generations. The data showed that younger Lilly shoppers were more interested in affordable and accessible options compared to older Lilly Pulitzer shoppers.
So when the brand partnered with Target back in 2015, they wanted to cater specifically to this preference. To connect more with their millennial audience, the brand targeted younger customers with discounts and promotional content that was specific to their Target-line. Meanwhile, older customer segments that preferred their boutique experience received different content. The result? Meaningful customer relationships that pass the test of time.
To learn more about how to turn data into lifetime customer relationships in our e-book: Who Are Your Best Customers? Rethinking Customer Loyalty in a Digital-First World.