Retailers need to stay ahead of disruption if they wish to continue to win and retain customers. Organizations with large investments in their physical distribution network are under pressure to ensure they are in the right places and are catering to the unique needs of different markets at the right prices.
A critical element of any model build is the data that is received from the client. To put it simply, the more granular the level of detail that a client has about their customer, their locations, and their spending patterns, the better. Customer data, whether derived from a loyalty program or an in-store survey, is foundational to any modelling engagement.
Customer loyalty programs
While the deployment of a customer loyalty program typically falls within the purview of a Marketing team or even a dedicated Loyalty team, the benefits of such a program should be felt organization-wide. The explicit goal of any loyalty program should be to improve customer engagement, acquisition, experience and retention, leading to an increase in sales. An overlooked benefit of a loyalty program is the breadth of ethically sourced first-party data it can yield.
A well-designed loyalty program will allow you to understand:
- Where your customers live
- How much they are spending
- What products they purchase
- How often they are visiting
With this data at your fingertips you can:
1. Inform the development of new offerings
Your customers are a goldmine for figuring out the next dish you should be offering at your restaurant, what new products to stock your shelves with, or how customers want to interact with your product/service e.g. online versus offline offerings. By collecting customer loyalty data, you can start to understand the different types of customers you serve and the products that fit their tastes. Using the email addresses and phone numbers tied to those customers, you can also reach out to them to survey what they like about your current offerings, what they don’t like, and most importantly, what they’d like to see you do next.
2. Win back customers
With customer loyalty data it’s easy to see when a customer has crossed the point of no return; they haven’t come to your store in the last 90 days, for example. By being proactive and reaching out to customers who have passed the threshold, you can run campaigns to win back their business through special offers or discounts.
3. Find better locations
One of the most important strategic decisions for retailers of any size is choosing a suitable location for their new store. Customer loyalty data tells you exactly where your customers are coming from by tying transactions to the customer’s address. You can use this geographic data to derive the demographic and psychographic makeup of “hot” neighbourhoods where your highest spending customers live. You can also use it to determine the actual trade areas of your locations. With this critical information, you can validate each prospective site by checking whether your top shopper profiles exist within the prospective new trade area.
Alternative data collection methods
ZIP Code or Postal Code surveys are also a great way to yield customer data. Performed consistently across your store network, these surveys can link up details between customer locations and purchasing habits, which provides the statistical ammunition to model predictions about customer behaviour and prospective store performance. Companies with multiple banners, concepts and formats can use this data to begin to validate hypotheses around which customers are drawn to which locations, and create a roadmap that aligns market opportunities with the best-suited banner concept.
The PiinPoint Solution
PiinPoint develops trusted models for industry leaders and emerging concepts that predict future success opportunities and prescribe a path towards optimizing online and offline efforts.
By drawing from a broad cross-section of data sources, PiinPoint is able to provide best-in-class model outputs that integrate seamlessly into our mapping platform. Mobile Location Data, Demographics, Points of Interest Data, Household Spending Information and Geosocial data are just a few of the elements that allow PiinPoint to build highly accurate models.
Find out how PiinPoint can help your business use data and analytics to drive growth here and sign up for our newsletter in the column to the right of this post to receive more site selection tips and free resources.