Customer Data Platform: Toward the personalization of customer experiences in real time

Customer Data Platform: Toward the personalization of customer experiences in real time

  • Jean-Michel Franco
    Jean-Michel Franco is Director of Product Marketing for Talend. He has dedicated his career to developing and broadening the adoption of innovative technologies in companies. Prior to joining Talend, he started out at EDS (now HP) by creating and developing a business intelligence (BI) practice, joined SAP EMEA as Director of Marketing Solutions in France and North Africa, and then lately Business & Decision as Innovation Director. He authored 4 books and regularly publishes articles, presents at events and tradeshows and can be followed on Twitter: @jmichel_franco

Big data has monopolized media coverage in the past few years.  While many articles have covered the benefits of big data to organizations, in terms of customer knowledge, process optimization or improvements in predictive capabilities, few have detailed methods for how these benefits can be realized.

Yet, the technology is now mature and proven. Pioneers include Mint in the financial sector, Amazon in retail and Netflix in media. These companies showcase that it is possible today to put in place a centralized platform for the management of customer data that is able to integrate and deliver information in real time, regardless of the interaction channel being used.

This platform, known as Customer Data Platform (CDP), allows organizations to reconstruct the entire customer journey by centralizing and cross referencing interactional or internal data such as purchase history, preferences, satisfaction, and loyalty with social or external data that can uncover customer intention as well as broader habits and tastes. Thanks to the power and cost-effectiveness of a new generation of analytical technologies, in particularly Hadoop and its ecosystem, the consolidation of these enormous volumes of customer data is not only very fast, but also enables immediate analysis.

As well as this data helping improve overall general customer knowledge upstream; importantly, it also helps organizations understand and act upon individual customer needs on a real time basis. In fact, it enables companies to predict a customer’s intentions and influence their journey through the delivery of the right message, at the right time, through the correct channel.

The Pillars of CDP

To achieve this, the Customer Data Platform must be based on four main pillars. The first pillar is about core data management functions around retrieving, integrating and centralizing all sources of useful data. In an ideal implementation, this system incorporates modules for data quality to ensure the relevance of the information, as well as Master Data Management (MDM) to uniquely identify a customer across touch points and govern the association rules between the various data sets.

The second pillar establishes a list of the offers and “conditions of eligibility”, taking into account, for instance, the specifics of the business such as premium pricing, loyalty cards, etc. The third pillar aims to analyze the data and its relationships in order to establish clear customer segments. Finally, the last pillar is concerned with predictability and enabling, through machine learning, the ability to automatically push an offer (or “recommendation”) that is most likely to be accepted by the customer.

These are the four steps that I believe are essential to achieving the Holy Grail or the ultimate in one-to-one marketing. Before companies tackle these types of projects, it is of course absolutely essential they first define the business case. What are the goals? Is it to increase the rate of business transformation, drive customer loyalty, or to launch a new product or service?  What is the desired return on investment? The pioneers in the market are advising companies to develop a storyboard that describes the ideal customer journey by uncovering "moments of truth” or the interactions that have the most value and impact in the eyes of the customer.

The Path to Real Time Success

Once companies have created their Customer Data Platform, they may begin to test various real time implementation scenarios. This would involve importing and integrating a data set to better understand the information it includes and then executing test recommendation models. By tracking the results of various models, companies can begin to refine their customer engagement programs.

The ability to modify customer engagement in real time may at first seem daunting. Especially given that until now information systems have taken great care to decouple transactional functions from analytics. However, the technologies are now in place to make real time engagement a reality. Companies no longer have to do analysis on a small subset of their customer base, wait weeks for the findings, and then far longer before they take action. Today, all the power companies need to connect systems containing transactional information, web site, mobile applications, point of sale systems, CRM, etc., with analytical information, in real time.

In general, making the transition to real time can be completed gradually. For example, companies could start with the addition of personalized navigation on a mobile application or individualized exchanges between a client and a call center for a subset of customers. This has the advantage of quickly delivering measurable results that can grow over time as the project expands to more customers. These early ventures can be used as a stepping stone to building a Customer Data Platform that enables companies to precisely integrate more deeply the points of contact - web, call center, point of sale, etc. - in order to enrich the customer profile and to be able to personalize a broader set of interactions.

Once all the points of contact have been integrated, the company has the information necessary to make personalized recommendations. It is the famous Holy Grail of one-to-one marketing in real time, with the four main benefits being: Total visibility on the customer journey (in other words the alignment of marketing and sales); complete client satisfaction (no need to authenticate) and therefore loyalty; clear visibility into marketing effectiveness and, in the end, increased revenue due to higher conversion rates. Given that we already know that companies employing this type of analytical technique are more successful that the competition that don’t,[1] moving real time becomes a necessity.

What about Privacy?

The respect of privacy should indeed be a key consideration for anyone interested in the personalization of the customer experience. While regulatory concerns might be top of mind, companies must first and foremost consider how their actions may impact their customer relationships. This is a matter of trust and respect, not simply compliance. Without a doubt, there is a lot we can learn here from what has been implemented in the health sector. Beyond getting an accurate diagnosis, people are generally comfortable being open with their doctors because they clearly understand the information will be held in confidence. In fact, physicians have a well-known code of conduct, the Hippocratic Oath. For companies, a similar understanding must be reached with their customers. They need to be upfront and clear what information is being collected, how it will be used and how it will benefit the customer.

Related Resources

5 Ways to Become A Data Integration Hero

Products Mentioned

Talend Data Integration



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