Data Gathering Helps Build Stronger Relationships
Gathering and analyzing data helps brands cut the information clutter by locating specific information quickly. Data analytics helps efficiently identify the values shared by both customers and the brand, allowing marketers to build loyalty, deliver value, and ultimately provide better service to customers. It helps marketers identify the most profitable customer segments (and previously unidentified segments) and then build real two-way relationships with these individuals through communications, interactions, experiences and transactions that align with their values, streamlining offers to those best suited to the segment and delivering customer experiences that stand out.
As the internet has changed marketing forever, brand affinity is also changing. No longer a matter of who has the best rewards program, building loyalty today involves a customer-centric approach based on establishing long-term relationships.
This is where data analytics comes front and center, because it lets marketers efficiently determine the who, what, where, why, when, and how of building brand loyalty in the age of technology. Which customers are your most loyal and most profitable? Do you have underserved or overlooked customer segments? Data analysis churns out these details to enable brands to create loyalty building roadmaps. Roadmaps that build relationships to the brand transcending affinity to the loyalty brand.
Build Brand Experience Based on Data Analytics
Customers today experience brands across multiple media channels. From the traditional radio, television and print ads to social media like Facebook, Instagram and Pinterest, online shopping, and website content, today's marketers have many opportunities to establish and nurture their brand. Yet this opportunity also brings the difficult decision of where to focus customer-centric branding efforts.
While data gathering is fairly simple, extracting useful relationship-building-related data is more challenging, especially when it comes to brand experience. It requires identifying and extracting only the relevant information needed to create and deliver highly targeted and personalized customer experiences. This strengthens brand experience and builds loyalty. But how do you pinpoint the relevant data? Department store Neiman Marcus used data analytics to focus on identifying the past behaviors of their top customers, then applied today's technology to provide a highly-personalized brand experience.
Neiman Marcus encourages customers to check-in via a mobile app when they are ready for assistance in a retail store. The app also uses their previous purchase activity to link them to their favorite sales associates. Sales associates may access the purchase history and relevant information of customers who have checked in to provide more personalized service in store.
Along a similar line, Nordstrom recently launched a text shopping service where customers can text their personal stylists so they can make purchases on their phones at their convenience.
What Data Best Drives Your Customer Engagement Opportunities?
When it comes to developing engagement opportunities, the best data to review may be the information about your customers' values. Do your customers want mobile app deals, or would they prefer print coupons? Are they open to email special offers, or would they value newsletters with relevant information? What means more to them, providing a better offer or delivering a faster, simpler shopping experience? Leading brands use customer values to make decisions about product pricing, selection, customer processes and even store location, all contributing factors to building brand loyalty.
Data on values can also direct emotional and non-transactional customer engagement opportunities. For example, Aeroplan used data on each customer's personal history to recap and communicate the milestones of their life in the loyalty program, including what they had used their rewards for over the years; which is a clever loyalty-building communication. Most members use their miles for memorable experiences and enjoy being reminded of them. By sharing this information as a "thank you" email to customers, Aeroplan provides a meaningful, customized, and even intimate interaction with each member.
Members are encouraged to enjoy this "portrait" of their Aeroplan activity. This personal record is presented as a year-by-year, month-by-month breakdown of reward redemptions for flights, other travel partners, and activities or merchandise. Aeroplan's creative use of data analytics results in a unique engagement opportunity. As members review their activity, they are strolling down memory lane, remembering times well spent as a result of their Aeroplan rewards.
The Keys to Building Loyalty Today and Tomorrow
Using data to drive and strengthen customer loyalty gives today's brands the opportunity to build personal relationships, and a hallmark of these new, real relationships is transparency. Customers deserve to know that information is collected and used to build better customer relationships. Yet with all the information available to marketers today, brands must tread carefully, protecting collected data while artfully extracting and presenting the most useful information. After all, it is a fine line between harvesting data to provide a differentiated customer experience and creating an "am I being stalked?" feeling among customers.
To optimize data without overwhelming customers, brands must remember a few important points. First, the goal is to use data to nurture customer relationships in order to serve them better. Second, the customer must feel like they are in control. Asking for permission to proceed and transparency in all communications and transactions helps promote this. Third, trust and reciprocity are key elements of the new customer experience. And finally, today's customers are busy people, with no time to waste on useless information and communications. The most effective marketers will deliver value consistently, in each and every communication and transaction. And they will move beyond tactical, targeted offers to data-informed customer experiences.