Despite efforts over the years to merge transactional and promotional (marketing) communications, it’s still more common than not that these communications continue to be managed and generated in siloed systems, separating their stakeholders in name of privacy and security of the data. Marketing needs to have the freedom to explore any and all options when it comes to lead generation and customer nurturing while transactional communications need to maintain guardrails to retain trust with existing customers by protecting their sensitive data.

Unfortunately, this approach often impacts the customer experience. Inconsistencies in communication look and feel, silos by line of business, disconnected or limited integration between systems ultimately leaves gaps in the customer’s ability to navigate the vast web pages and content available through self-serve. This causes them to turn to support channels such as the contact center, customer service, agents, chats, etc. More often than not, these employees in the front lines of customer support often request patience from the customer as they need to navigate several internal systems in an effort to find the desired information or answers.

While many strategies look to new software, business process automation or to redesign communications as a way to improve the overall experience, the goldmine at the root of every experience is the customer data.

Customer data management is done in a variety of ways within an organization, even within individual lines of business. CRMs are often used to capture information for preference management, CDPs (customer data platforms) are used for website tracking and personalization, often missing the full omnichannel experience tracking. Marketing automation has included lightweight CRMs which are evolving to CDPs but are sometimes just their own database specific to their content-focused used cases. Campaign management is often separate as well, holding its own set of data used for personalizing campaigns and understanding customer behavior within them. Journey management solutions also have a unique set of data not stored elsewhere around the events, actions and behaviors, both planned and reality, that reflect customer interactions. Segmentation is another function that is often solved through custom scripting or home-grown systems or is embedded within other marketing systems but holds valuable insights.

The result is a vast system of siloed data sources that customer experience executives and communication centers of excellence (COE) see a need to address, but it requires a level of attention and effort to sort through. At best, go forward efforts such as zero copy policies helps to reduce adding to this complexity, but can slow down adoption of new technologies.

Adding more complexity are AI and LLMs. Generative or Content AI is really where many communications and data tools have focused to generate or tweak content. However, concerns around intellectual property can limit how organizations want to use these tools. In communications management, assisting content creators to craft messages has shown some value, but is only the tip of the iceberg of the potential value AI can provide to communications experiences. The more data available to be fed into an LLM, the more we can leverage other AI variations such as Insights AI and Responsive AI, which have the potential to analyze the vast amount of data available in these siloed systems and make recommendations for improving customer experiences from individual touch points to the overall sentiment of the business relationship.

Knowing that this data exists today within organizations but in disparate systems is a good problem to start with. Many have attempted to solve this through business process management/automation and integration, but that approach can create complexities of its own. Aggregating all of this data to persist in a single, centralized database is an unrealistic effort that will get shut down by every CIO and IT department. So, how can we address this?

The first step is understanding where this data exists today. A few questions to ask… What systems exist and where? What type of data is stored in these systems? Is it usable? Is it actionable? Where and when is it used and to what extent? For example, can it be used for personalization of content within a communication, personalization of an experience touchpoint or automating orchestration follow ups?

Once you begin to understand the complexity of your organization’s data infrastructure and the valuable data it holds, you open the door to the opportunity to connect these systems with a customer data solution that can provide a powerful, complete view of the customer that is both actionable and insightful.

The work is not done yet. Understanding the personas who need to use this data, creating a data governance strategy and aligning key stakeholders are also critical steps to success. What are the desired outcomes and their respective priorities of this data once it’s aggregated, normalized, analyzed and able to provide a more complete view of your customers and their behaviors? This goldmine of data is powerful and desirable, so having clear priorities is key.

As we know in customer communications, data is sensitive and must be protected but can provide powerful insights that can improve business outcomes and enhance personalized experiences when used correctly. New solutions are becoming readily available that are approaching disparate enterprise data systems with a different approach that does not require ripping out the existing infrastructure. It is important to remember that the software and solutions are only as good as the strategy that is driving the ROI and outcomes of centralizing customer data.