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Retail: Are you activating data quality management in your customer loyalty strategy?
Building customer loyalty means keeping in touch over the long term, and getting to know customers in order to better recognize them. Data quality management optimizes several levers of customer engagement by guaranteeing reliable and unified data, which fosters customer loyalty.
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Customer data is omnipresent in retail, and is collected at various touchpoints, such as stores, websites, mobile applications, social networks, and chatbots. Masterfully using this customer data requires making it reliable and unifying it through data quality. Business line users need to be able to work with reliable data, with contact information that makes a customer reachable and that ensures proper delivery, in a Single Customer View, without any confusion between multiple records.
This added value that comes from data quality management for points of sale, e-commerce, after-sales service, CRM or marketing directly contributes to customer loyalty. Indeed, data quality management provides several tools for better engaging customers:
Keeping in touch with customers through reliable contact information
To maintain customer loyalty, you have to nurture the relationship over the long term, which means making sure that you are able to contact them. However, it is difficult for your retail teams to identify whether or not a phone number is inactive, an email has become invalid, or an address has changed after a move. Data quality provides solutions to improve the quality of contact information in real time when they are entered, as well as when a curative treatment of databases takes place. This quality control of contactability data in the database or at the source provides your teams with reliable contact information to reach customers:
– Collecting complete, country-standard mailing addresses ensures deliverability, which is critical to keeping e-commerce shipments from becoming undelivered mail. Indeed, the mailing address is the data element where errors are most frequent, because postal repositories change frequently from one year to the next. Qualifying the customers who have moved is also important in this context. In all these cases, data quality updates the mailing addresses of your customers and prospects, and makes them reliable.
– Text message campaigns benefit from valid phone numbers to send marketing texts to numbers that are valid and contactable. The same advantage is available for emailing or printed mailing campaigns, with an optimized ROI because your messages are less likely to go undelivered. All of this has a positive impact on the customer experience and on customer loyalty.
Engaging your customers with a seamless experience, starting with the form
In many retail scenarios, both at the point of sale and online, the customer journey begins with the entry of contact information. However, this input can contain many onerous elements for the customer on an online form, or in the store with a salesperson who takes care of it. And the more information your brand needs to collect for customer relations, the more critical the form step becomes.
Data quality provides significant support with input help and autocompletion. By checking the validity of the information entered in real time, the user can quickly correct any errors. In addition, autofilling as soon as the first characters are entered speeds up the process and makes it more reliable. With assisted and controlled entry of customer information, your forms become interactive and the customer experience is much smoother. This will allow you to properly finalize data collection, to increase the conversion rate, and to set the stage for encouraging customer loyalty.
Keeping tabs on your customers in customer loyalty programs
The Single Customer View is essential in loyalty programs for retailers whose customers buy at different touchpoints. Tracking the customer journey and the various transactions is essential in order to accurately count loyalty points and to correctly distribute the benefits associated with the program.
However, when a customer is in the information system with multiple duplicate records, some of which contain erroneous data, triggering the benefits of the program becomes disorganized. Indeed, if the purchase history is scattered across several files, tallying the loyalty points is compromised.
Data quality allows you to deduplicate customer data from multiple sources, and to unify them according to the rules specific to each brand. In particular, specificities such as multi-brand, international presence, or different types of customers (individuals and companies) are taken into account in the rules for unifying duplicate records and accounts. Thanks to this consolidated view of your customers, you can deploy a personalized loyalty program strategy, adapted to your customers’ profiles, and thus foster the feeling of belonging for your customers via data that is exhaustive and reliable.
Mapping your customer database in order to better segment it
Geolocation of customers thanks to geocoding their home address opens up many possibilities for better customer segmentation. As such, mailing addresses provide constant latitude and longitude references that allow you to compose a geographic segmentation with granularity up to your customer’s neighborhood. In addition, data quality allows you to cross-reference this geographical data with public data such as national statistical databases or land registries to better understand the customer context and, by extrapolation, potential buyers.
This type of mapping provides valuable information on each customer, with the possibility of understanding the context (for example, an area that is polluted or at risk, or a neighborhood or street with high traffic), the catchment area. The result is service that is adapted and offers that reinforce customer satisfaction and loyalty. Your marketing department can better target its campaigns, for example by identifying people who live within walking distance of a city center, in order to send them campaigns that associate nearby points of sale.
Data quality contributes directly to making geolocation a relational, commercial and marketing tool to better personalize the relationship and reinforce loyalty.
Personalizing the relationship to serve the loyalty strategy
In an increasingly complex customer journey, data quality captures data that can be used at all touchpoints and allows all parties likely to interact with the customer to personalize the relationship. With accurate and unified customer data, retailers can develop loyalty strategies based on individual customer preferences and behaviors.
Indeed, by eliminating duplicates and the confusion associated with them, and thanks to reliable contact data, data quality gives your retail teams the means to be better acquainted with their customers. Distinguishing a regular buyer from a newcomer, having a clear vision of the potential of each customer with the complete amount of their transactions, and mastering the history of purchase and contact with the company are some of the benefits provided by data quality in order to provide personalized service to your customers, at the right place and at the right time.. This will give your customers every reason to “stay with you”.
For more info, read also: In-store data collection: 5 tips to meet the challenge
About DQE
Because data quality is essential to customer knowledge and the construction of a lasting relationship, since 2008, DQE has provided its clients with innovative and comprehensive solutions that facilitate the collection of reliable data.
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