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Leveraging Loyalty Data to Deliver a Happy (and Profitable) Holiday Season

For many brands, loyalty has never been just about keeping and rewarding the right customers. While customer retention is indeed a key goal of any loyalty initiative, the best programs use the data they collect to drive customer acquisition efforts as well.  As the 2017 holiday season  quickly approaches — one that is expected to herald a 3.1 percent increase in sales over 2016 — retailers across many spend categories need the kind of loyalty program that can both retain and acquire customers… and pay dividends that go beyond the holiday season as well.

Is that possible? After all, loyalty programs by their nature are designed to reward existing customers and drive repeat purchases, while acquisition efforts are traditionally the purview of separate sales and marketing silos. 

The answer, as always, lies with data.

Understanding what to do with loyalty data

Increasingly, loyalty programs are used as data collection mechanisms that provide insight into member (that is, customer) behavior. This data, analyzed and used intelligently, is infinitely more valuable than the next one purchase coaxed out of a loyalty member. It can be leveraged to create addressable marketing and advertising, identify customers’ positions in the purchase cycle, target messaging for optimal impressions, and refine and tailor offers and rewards. But it can also be used to inform a variety of acquisition strategies, from the development of customer attribute profiles, look-alike modeling, real-time segmentation, and parsing third-party data. This is loyalty reimagined — as adept at bringing in new customers as keeping existing ones.

(Real) customer attributes

Perhaps the most straightforward application of loyalty data in this context is the agglomeration of customer attributes into workable profiles. A good loyalty program, one that is integrated with a CRM program, will be able to identify customers, what lifecycle stage they’re in, their spending history in terms of dollars and purchase frequency within a timeframe, and their preferred purchasing channel (in-store or online). This information allows retailers and brands in virtually any segment to develop a clear picture of their customers — their actual customers, not nebulous “personae” based on generalized assumptions. These attribute profiles can in turn be used to create targeted messaging, or to serve as the basis for look-alike modeling, or both.

1st-party meets 3rd-party look-alike modeling

Once a brand knows what its best customers look like, it can also source third-party data to find other customers like them, and target those look-alikes. The digital marketing channels that brands use to reach new customers can easily identify these look-alikes and facilitate targeting, for example:

  1. A retailer (through its loyalty data), might identify its most high-upside look-alike for holiday shopping as a parent of school-aged children with a moderate-to-high level of discretionary income who engages with similar brands frequently. 
  2. A social media channel like Facebook can identify this customer, who the brand can then target with display media. Incidentally, Facebook is an apt example; 62 percent of 22-35 year olds will consult Facebook before making their holiday shopping decisions this season, according to eMarketer.

Brands and retailers that engage in data-drive look-alike modeling are well positioned to capture those information-seeking customers.

Real-time segmentation

Loyalty data can clearly augment the identification of customer attributes and facilitate look-alike modeling.  When integrated with a CRM program, it can also be instrumental in segmenting customers, allowing brands to create deeper and narrower tranches of customers for micro-targeting purposes. Without integration between the loyalty and CRM systems, this can be a laborious process, but with the right degree of integration and automation, a brand can achieve real-time segmentation. Integrating loyalty and CRM programs ensure that customer data is captured, gathered into a common repository, and associated with the appropriate identities so an automated system can identify micro-segments that are most likely to respond to specific offers and determine which channels are best for those offers. A technology partner with this level of capability is instrumental for brands and retailers who want to reach potential customers as they are making their buying decisions.

Loyalty data gives the gift of new customers

Loyalty programs that can determine high-value member attributes which can be integrated into look-alike models are necessary for retailers and brands hoping to capitalize on a strong retail holiday season. These loyalty-driven acquisition strategies are pivotal ways to capture data, create real-time customer segmentation, and build member profiles. 

Brands that choose the right partner to help them achieve the acquisition benefits associated with a strong, integrated loyalty program will be positioned to have a very happy holiday indeed.

Does your brand have the tools in place to execute smart segmentation and targeting strategies for the holiday season and beyond? Are you using your loyalty data to drive customer acquisition efforts? Merkle can help you optimize your loyalty and data processes. Learn about our acquisition and retention solutions here.