picture of string orchestra from above, with musical charts in front of them
PHOTO: Samuel Sianipar

As data collection methodologies have grown in sophistication and reach, it’s become much easier for marketers to capture data with every visit or click. For companies equipped to handle it, all this data fuels powerful personalization initiatives and provides deep analytical insights into customer interactions. For those ill equipped, dealing with this data can overwhelm already time-strapped marketing teams, leaving data unanalyzed and unused.

Many organizations lack a comprehensive data strategy. As a result, they might invest in marketing and customer experience (CX) technology only to find it that, despite an abundance of data, they can’t effectively improve the customer experience or drive revenue growth. While data is essential for marketing automation, personalization and customer journey orchestration, just having a lot of data isn’t enough. Leveraging this data calls for a structured approach to data management. 

This structured approach requires two things: First, you need a way to consolidate all your data; and second, you need a strategic framework for putting it to use.

It’s 2019: Do You Know Where Your Data Is?

Because customers interact with different parts of your organization, it’s only natural that the customer journey data your organization collects lives in disparate silos. However, to use your data to not only better understand your customers, but to create targeted, personalized experiences and track the overall effectiveness of your efforts, you need to have your data in one place.

A customer data platform (CDP) can aggregate your data into one unified database for consistency and ease of access. Because organizations recognize this need for data consolidation, CDPs still sit atop Gartner’s hype cycle. CDPs address a real organizational challenge, but they do have drawbacks. Creating a central database of customer data, for example, requires continuously moving data across systems, exposing the organization to risk of data loss. This centralization also involves the addition of yet another database to an environment already full of them, compounding rather than alleviating your data management issues.

An alternative to data centralization, and one that in theory can accelerate digital transformation, is data virtualization. When we attended the Digital Customer Experience Strategies Summit recently, “digital transformation” was at the center of discussions around CX. And what we heard was, above all, frustration with the pace of digital transformation efforts, especially in the realm of CX management.

The basic principle behind data virtualization is this: Let data stay where it is, consolidating it in a virtual layer, and connect this layer to your relevant channels. This “virtual CDP” approach not only builds on the broader trend towards virtualization and services-oriented technical infrastructure, but also allows you to both consolidate and operationalize data more efficiently.

Related Article: Customer Data Platforms: The Truth Behind the Hype

Build Out a Data Framework

Consolidating your data, either through a database solution or through virtualization, is just the first step. To operationalize your data, or, frankly, to have a proper data strategy at all, you need a framework. The appropriate data framework will not only help you leverage data to inform specific marketing activities, but it will provide you with a standard for measuring the effectiveness of your customer journey initiatives. 

According to Gartner, messy data results in missed opportunities. In a study the advisory firm published last year, a majority of marketing analytics leaders pointed to data integration and formatting as the tasks consuming most of their teams’ time. This effectively translates into underutilization of the most expensive and talented resources on those analytics teams. Indeed, 45% of organizations in the study reported that data scientists actually spent most of their time preparing data to be analyzed, rather than doing actual analysis.

When resources like these are focused on what amounts to a basic, administrative task, it means they can’t focus on exploring new ways for data to drive innovation or executing on a strategic vision. An articulated data framework, a structured way to collect and store data, frees up data teams to have an ever greater impact on organizational performance.

Productivity improvements aside, in the absence of a clear framework, companies can’t accurately say whether their CX initiatives, particularly those involving customer journey orchestration, are actually working. According to Forrester’s recent report, “The Journey Measurement Framework: Assess and Predict Journey Performance,” (paywall) CX pros often don’t know whether the customer journeys they implement deliver any value to customers, let alone to the brand. CX and marketing teams struggle to understand where the customer journey breaks down, making it difficult to devise and implement systematic improvements or build a business case for further customer journey investments.

In order to rationalize data analysis as well as track and measure journey orchestration efforts, the framework we’ve found to be most advantageous is one built around journey steps.

Related Article: How to Build a Successful Data Analytics Team

Thinking in Customer Journey Steps

While tempting, thinking about customer journeys solely in terms of outcomes — first contact, purchase, repeat purchase, enrollment in loyalty program, etc. — doesn’t give you enough detailed insight to work with. Since customers can engage in numerous brand interactions leading to those outcomes, you need a way to assess specific interactions and analyze what happens when you alter them or introduce new ones. That’s where journey steps come in.

Journey steps are the basic units of customer journeys. Organizing your data around journey steps allows you to model customer journeys and better understand how the individual components of a particular journey relate to each other. This in turn gives you insight into which specific steps have the most influence over specific outcomes, and guides your experiments with ways to shorten or accelerate the journey.

Above all, journey steps offer a guiding principle for data management. Journey steps help you identify critical points of customer interaction and thus also identify the essential data sources that you need to connect to your virtual CDP. Journey steps also help you organize your data by associating specific data sets with concrete moments in the customer journey, making ongoing measurement, analysis and refinement possible.

Ultimately, by measuring activity around as well as across journey steps, you gain practical insight into your journey orchestration efforts. This insight makes it possible to optimize journeys, step by step, as well as establish the return on your customer journey investments.

Orchestrating the customer journey matters to your business and your customers. Without proper data management, however, customer journey orchestration relies more on educated guessing and luck than on strategic vision and data-rich analysis. Smart data consolidation and a data framework built around journey steps enables the latter and helps you avoid the former.

Related Article: Leap Into the Future: Shape Customer Journeys With Context