Marrying Segmentation and Big Data to Help Build Better Customer Relationships
In our current age of Big Data-driven business, retailers have a considerable head start, having spent years gathering and analyzing data to shape everything from marketing strategies to supply chain management.
Despite that head start, and the plethora of ways retailers accumulate data, they only have part of the picture. Every data gathering technique offers great value, but also comes with limitations. Loyalty programs and retailer-issued credit cards provide detailed information and payment history but are limited to a small portion of customers. Transactional data tracks volume and purchase patterns, but lacks demographic detail and the ability to drive prospecting. Third party attitudinal data is helpful but fails to show who or where the customers are.
This fragmentation is a problem, denying retailers a clear understanding of both existing customers and prospects. Much of this data stays siloed – loyalty card data and purchase data clearly have some connection, but may never be viewed together. This makes it very difficult to leverage this data effectively.
Retailers need to unite their data to create a single view of customers. One way to do this is by implementing an actionable syndicated segmentation framework, allowing retailers to better unite disparate but valuable customer data through a single lens, and then use it to adjust other components of their business strategy.
A syndicated segmentation framework can bring together the various types of data available from the retailer’s operations – loyalty cards, retailer-issued credit cards, and sales data – and combine it with a variety of actionable third-party data. This, in turn, helps make it possible to develop appropriate customer treatment strategies, improve the customer experience, and optimize marketing budgets. For example, by using segmentation to better understand exactly who their most profitable and loyal customers and prospects are, retailers can prioritize strategies to develop deeper relationships with these desired customers and prospects.
For retailers aiming to identify and prioritize their desired customers, an ideal segmentation framework should include robust household economic data, which goes above and beyond standard geo-demographic data, providing retailers with an enhanced picture of customers, your estimated share of their wallet, and their potential growth.
With economic insights, such as estimated income, including income from assets, discretionary spending capacity, and credit capacity, retailers can build a better understanding of current shoppers and then sharpen definitions of what their optimal shopper looks like. Segmentation becomes the framework that helps them connect their various data points and make the data actionable.
For example, by combining all of their data and linking it via an economics-based segmentation framework, marketers can look at customers that are heavy frequent shoppers, with a certain spending capacity who also live in the same region and share lifestyle characteristics. This frequent shopper may well represent the optimal customer, and the retailer can now use this profile to prospect similar individuals.
By defining their current and desired customer types and examining any gaps between the two, the segmentation framework can provide a lexicon that internal departments can use to better communicate. Marketing, merchandising and operations are now all aware of the same target customer characteristics. Retailers can maximize sales by adjusting their merchandising strategies, helping reach their desired prospects through marketing campaigns, and translating offline marketing success across channels. The insights can also provide significant input to broader corporate decisions such as store location planning, merchandising mix and overall branding.
Applying segmentation provides insights that help drive profitable relationships. Retailers may not only gain better customers, but they’ll be able to manage interactions to increase the lifetime value of those customers. When segmentation is applied beyond marketing campaigns to understand revenue generation and relationship costs, it can help create more profitable relationships. For retailers, knowledge is wealth. They’ve done a great job building their data reservoirs, but its time to go one step further to fully tap into them.
Previously published in the Retail TouchPoints Blog.
Retail TouchPoints delivers cutting edge content to retail executives designed to improve the customer experience in the new world of cross-channel retailing.
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