The market is changing. In historical systems, when data storage was a primary concern and companies frequently required their own on-premise server banks, the primary analytics systems were walled gardens. Closed ecosystems which housed the data in their servers, processed it according to proprietary schemas, and moved it through their ecosystem. This changed with Amazon web service (AWS), Azure, Google Cloud, and Snowflake. With the move to the affordable cloud, opportunities presented themselves. Revolutionary technologies became available à la carte.

Rather than a stack of technologies, one built on other matched technologies, the modern analytics solution is closer to a wheel — a central hub with spokes extending out and all feeding back to the central hub. Customer data platforms, or CDPs, are that hub. Connecting to a multitude of destinations and providing stability and consistent messaging across all touch points, CDPs facilitate true digital experience optimization, and they’re continuing to evolve. Below are some of the key ways CDPs are innovating in 2022.

#1 Integrated Data Ingestion Capabilities

Data connectivity is one of the central roles of any CDP. This is typically done via integrated data connectors which are curated by the CDP firm, or occasionally the destination for the data, however, there are products coming onto the market which feature their own integrated extract, transform, load (ETL) suite (e.g., Rudderstack). While this can add to the setup time versus prebuilt and integrated connectors, if the technology itself lacks the integration (or if it’s substandard), having ETL capabilities built into the product allows for significantly higher portability of the data, with greater control over security measures and intake latency.

#2 Automated Machine Learning for Segment Identification

image representing machine learning

Machine learning (ML) is one of the current major pushes in digital analytics broadly and is quickly becoming a necessity in digital experience optimization (DXO). There’s a wealth of data in every digital implementation, with more available to be created or extracted. Naturally with all this data, ML would be a high value process. There are challenges to building this capability out from scratch however. Firstly, the skill gap between data analysis and a machine learning engineer is very large and will almost certainly require additional hires to facilitate. Secondly, the data used in ML must be highly curated and standardized, as every deviation in syntax or piece of erroneous data can very quickly derail any detailed routine without significant quality controls to being put in place.

CDPs solve for this issue naturally, however, as they’re built for intaking data from every source and integrating those sources together. The result of this integration is a well curated data set, usually with robust data governance tools to ensure that erroneous data is flagged quickly. This allows for true ML in an often-automated format with very little need for in-house ML engineers. Examples of technologies which are doing this well are Evergage and Tealium Predict ML, with more coming on the market regularly with this functionality.

#3 Intuitive User Interface for Marketer Usability

Data, whether first-party, third-party, or zero-party, can be the most valuable asset any company likely has if used correctly. However, there are numerous barriers to enabling it. Segmentation implementations are generally dominated by digital marketing use cases. Directed digital marketing, personalization, and content targeting are all DXO techniques. Allowing marketers to enable and activate on their own use cases can greatly reduce or eliminate the development cycle. Numerous CDPs are angling themselves as being marketer friendly (e.g., Simon Data) and this will be an increasing class of CDP in the coming years.

#4 Customer Data Management / Privacy Controls

business professionals sitting in a coffee shop

The current trend in the data ecosystem is privacy and consent centric, but this isn’t where it will end. Users are realizing quickly both how much data is being extracted about them, as well as how valuable it is, and legislation will follow this. In the future, the right-to-be-forgotten will likely be enacted and a CDP would be an ideal place to handle these requests. Allowing users to see the classifications you attribute to them, fix or add to them, or be forgotten entirely and have their data purged will all be able to be performed in a centralized location, and the first company to enact a system like this prior to legislation will reap the benefits of the positive press coverage. Additionally, a system like this would allow for tagless personalization by users self-selecting their classifications in a zero-party data system.

#5 Automatic Activation

The best insights are less than useless if they’re not put into action. This is one of the primary benefits a CDP can bring to an organization. Putting in place event triggers, segment assignment actions, or listeners watching in real time for conditions or score thresholds to be met can allow you to build a system which is constantly monitoring your data and putting into action routines for churn avoidance, cross-sell, or other real time engagement procedures. Many CDPs already have systems like these in place where, when a segment is assigned, the user is automatically sent to marketing or personalization channels, but more detailed routines are possible. Logical routines can provide intelligent action based on a data monitoring system that never stops watching and looking for ways to increase user engagement.

#6 Modular Ecosystem Facilitation

The market is moving away from closed ecosystems and has been for some time. Cloud computing and storage have facilitated specialized and innovative new solutions, which can be easily mapped into supplemental technologies. Every business landscape is unique, and every business solution should be as well. CDPs should facilitate this modular approach. By cultivating data connectors, or providing integrated ETL/ELT capabilities, CDPs can truly be the central hub which provides stability in your overall data ecosystem. The CDP provides the source of truth for who your customers are and how they engage with your properties which means that data sources can be replaced, marketing technologies can be tested, and the story remains consistent. The benefit of this stability cannot be overstated, as it enables consistent messaging and engagement regardless of the channel, data sources, or data destinations.

A Cultivated Landscape or a Walled Garden

Man and woman walking in office

If you take anything away from these CDP trends, take away that the modern tech stack should be built tailor made for your organization. Every company is unique. Every team has different strengths and gaps. CDPs enable you to build in a way which capitalizes on where your organization excels while mitigating the gaps by providing bridging functionality. A “Walled Garden” approach is safe, but a “Cultivated Landscape” enables your unique strengths and values to be highlighted. No canned solution will fit any situation perfectly. CDPs already help facilitate a cultivated landscape, and they’ll only increase in importance as time goes on.

These “trends” are coming, and it’s likely only the beginning for these types of technologies. If you want to invest in your digital experience optimization (DXO), it’s hard to imagine a better first piece.