It’s is a well-known, historic philosophy of customer service. To this day, it continues to signify that helpful and consultative salespeople will guide their customers to the best possible product fit. Should the customer return the product or express any level of dissatisfaction, the salesperson, without hesitation, will make a product adjustment that ultimately pleases the customer.
But it was a slower and simpler time when the early retail giants (such as John Wanamaker or Marshall Field), intoned this mantra. In the early part of the 20th century, the legendary Sears & Roebuck catalogue was often fawned over for many weeks or months prior to customers actually placing a mail order (not to mention the time for fulfillment of goods). Regardless of what you ordered, or if you stopped being a Sears & Roebuck customer, your behavior in no way impacted receipt of the entire catalogue’s next printing – even if the recipient’s name was that of a deceased family member, or the delivery address was for the house next door.
In the brave, new world of the digital business platform, customer satisfaction is supported through integrated and multi-faceted technologies. Consider the confluence of CRM for managing customer data records, ecommerce APIs for the cookies-generating, browsing of products and order entry, streaming and predictive analytics enabling agile and pointed responses to customer needs while enhancing their retail experience - and even the contextual enrichment of sensor data from mobile devices - all coming together to form a 360 degree view of customer.
Unlike our ancestors who thumbed through hard copy catalogues and peered through artfully rendered shop windows, today’s retail shoppers take Smartphone-strolls under the watchful eye of customer systems that contextually project to the buyer what they really want, and how as customers they can anticipate their purchases being “always right”.
MDM Customer Enrichment
Accompanying these technologies is the ever expanding role of master data management or the customer data hub. Customer MDM is going well beyond its early role of merging multiple versions of customer records in order to create a single-version-of-truth. Of course, data governance is still very much about cleansing, matching and reconciliation. But once having stabilized customer master data, enrichment becomes the thing.
Three major examples of customer data enrichment include:
- Geocoding: Having verified the accuracy of addresses, geocoding enriches customer location data with GPS coordinates, thereby by enabling timely product deliveries and replenishment. It enables geographical support for improved customer service by picking alternative resources for in-stock products. Geocoding can also help pinpoint stores that customers frequent, allowing site utilization analysis. From an internal marketing and sales perspective, it is an application enabler for accurately determining market segmentation or sales territories.
- Reference Data/Code Sets: Internally created code sets can be correlated to enrich customer master records that indicate product buying histories, participation in loyalty campaigns and also simply categorizing customers based on buying preferences. In other words, code sets can be used to quickly asses customer profiles.
- Sensor Data: IoT (internet-of-Things) has become the emerging use case of this decade and one of the largest growing contributors to Big Data. The raw sensor data emitted from just a customer’s Smartphone can potentially be harnessed to provide additional information about customer behavior in terms of website activity, interaction with in-store systems (loyalty sign-ups, etc.), and even intra-departmental preferences within one store location.
Since sensor data can be viewed as transactional, or even its own brand of system metadata, it needs to be contextually aligned with the customer data record in order to provide meaningful enrichment.
All this is to suggest, that when we say “the customer is always right”, we can thoroughly document it.