Two kinds of organizations dominate in nearly every industry today. Those which have already employed some system or platform (whether successfully or not is a different matter) to improve their customer experience, and those that are seriously considering one. As a result, only a miniscule number are sitting on the fence or unclear about what excellent customer experience can do for their business. Even those with tight budgets are trying hard to employ some technology that can boost their customer experiences. Customer Data Management (CDM) is one such system that stitches together the fragments of your customer data strewn across departments and allows you to make the best out of it.
Deploying CDM technology is one piece of the puzzle, just as another one is how it functions and the technical expertise to manage it.
However, the real success in CDM lies in developing a vision, etching out a customer strategy, bridging the gap between significant departments, and communicating the desired change across the board. Similarly, building collaborative approaches in the company culture, striving to get rid of poor customer data management practices, and achieving consistent customer data across systems can have a snowballing effect.
Apart from the above, clear segregation of goals—such as ‘nurturing customer relationships, ‘closing leads better,’ and ‘enhanced targeting of customers’—must be the focus. And finally, it is about constantly analyzing how your customers perceive their experiences with your enterprise and your products or services.
In broad terms, it starts with detecting your most significant customer information across various systems, cleansing it (fixing inconsistencies and flaws), creating integrated and trustworthy customer profiles, and placing them in centralized locations. Also, it is essential to tie customer data to other significant data points like other customers in the same household, average ticket size of products, buying channels in use (in-store or online), along with merging customer data with their social and clickstream data, focusing on data governance, and comprehending other related patterns. Finally, it attempts to approach customers from not an ad-tech, but a mar-tech perspective, by shifting the focus to first-party customer data derived from a host of sources.
A customer data platform is a marketing technology that unifies a company’s customer data from marketing and other channels to enable customer modeling and optimize the timing and targeting of messages and offers. It has four primary functions:
| Data Collection | Profile Unification | Segmentation | Activation |
| Refers to ingesting 1st party, user-level data from a variety of offline and online sources possibly in real-time, including but not limited to (data browsing, cookies, names, demographic data, emails, device addresses, page visits, purchase history, etc.) | Refers specifically to unifying customer profiles by matching up duplicate profiles of the same customer. It also pertains to linking (or negating) various devices, email ids of the same customers, even aggregating customers to the same household accounts. | CDP works like an interface that enables marketers to develop and manage segments. It is about developing rule-based segmentation, including automated segment discovery, proclivity models, predictive analytics, and importing and deployment of custom models. | Activation is all about sending across the segments having instructions to execute campaigns that include email, mobile messages, advertising, suggesting recommendations, dynamic, and self-optimization. |
Before enterprises take even a single step further, they must realize that the data they may be looking for might be scattered around multiple departments. For example, some of it may be lying with customer engagement departments (like CRMs, customer support), some at the point of transaction, i.e., with sales and commerce (e.g., at check-outs, payment gateways), some in the back-office systems (like the ERPs), and some with marketing (digital personalization engines, customer identity and access management, multichannel marketing hubs).
Therefore, it is critical to acknowledge the expanse of the customer data ecosystem and that any CDM project that is undertaken will need the support, coordination, and approval from all these systems as well as external partners and agencies.
Recognizing business objectives is the first thing to do, followed by setting up data goals to strengthen marketing aims. Identifying all cross-departmental stakeholders that need to be involved in the intended project should also be a top priority. A three-pronged approach must be adopted:
Before implementing a CDP, enterprises must understand that many customer data software and platforms are often mistaken as data management software. In other words, many of them extract and make good use of customer data but are not data management software or tools. Therefore, comprehending the difference between CDP with customer frameworks like Customer relationship management (CRM), Digital experience platform (DXP), Multichannel marketing hub (MMH), Customer engagement hub (CEH) is an essential part of ensuring that the implementation stays on the right track and delivers what CDP promises to deliver. Though all these frameworks lend support during a CDP implementation and may have some overlapping capabilities, their purposes are quite different.
While weaving an all-inclusive view of customers is at the core of a successful CDP strategy, certain essential considerations must be made right at the start.
Read: Data Management Platforms (DMP) Vs Customer Data Platforms (CDP)
By creating a comprehensive view of customers and their association across the entire business ecosystem, enterprises make sure that every department, especially the data-dependent ones, gets benefitted through the CDP implementation. Therefore, a constant effort must be made to improve customer data quality with every passing day. Every gap must be stitched, as even a single data glitch can affect several departments. To ensure that your customer data is serving you efficiently in your CDP implementations, you can keep track of a few markers:
Pimcore follows best practices while implementing a CDP. Apart from building a strong customer data foundation that includes customer data integration, data-modeling, automation, real-time personalization, and executing all the steps systematically, Pimcore’s best practices ensure that enterprise internal and external relations improve through better collaboration. Pimcore understands that good customer data management is at the heart of enterprise sales numbers or marketing effectiveness. We ensure that every enterprise strategy is backed by customer datasets and subsets relevant to targeted customer segments, demographics, or individual customers.
We also assure that every enterprise CDP strategy includes the right CX stakeholders who have deep and intricate knowledge of enterprise customers, data, and analytics. Lastly, we strongly advocate that CDP should not remain IT-managed but should instead come under the purview of data management.
Read more about Pimcore CDP Platform
Pimcore Helped Northgate markets, a supermarket and a fresh-food industry giant in North America with customer data management
Northgate markets was not able to maintain its customer data, due to no central repository. Multiple profiles of same custmers were present, which hindered the possibility of providing personalized experience to customers. It also severely affected their marketig activities due to no segmentation. No insights could be culled out too. Besides, Northgate had no online presence, therefore targeted brand communication could not be shared with customers.
Pimcore implemented customer data management by introducing real-time data integration with end-user touchpoints for data aggregation at a single location. It also executed data verification and registration by integrating with 3rd party channels such as OFAC for facial as well as address recognition. Apart from this, an online and in-store ordering system was developed for Northgate’s grocery business.
The result was an astounding success in terms of customer engagement through better marketing opportunities, including higher cross-selling and up-selling possibilities, better segmentation, and personalized content for customers, while ensuring lesser time and effort got spent in data gathering, cleansing, and enrichment.
