Optimizing your Digital Transformation with Data Integration

In 2017, we explored the key topics of designing and following through on a digital analytics roadmap, (you can find those articles here and here) a critical piece of Digital Transformation. As we begin to venture further into 2018, the concept of Digital Transformation is still a leading theme in the media and marketing space, and it’s time to take the next step.

The next step in this process is Visitor Stitching, or the integration and connection of your user’s data points across all mediums and devices, allowing you to make more informed and accurate decisions based on your customer’s preferences. However, this is something that even leading brands can struggle to implement effectively. What’s helpful getting you from where you are to where you want to be? A roadmap!
 

Data integration, in a few words…

Let’s start at the very beginning: what is data integration? Conceptually speaking, data integration is simple: combine data from the various data-gathering systems your company uses into one, holistic view. This can be a holistic view of the customer (i.e., stitching data across systems to create a complete view of the customer journey), products, or anything in between that an organization gathers data on.

Don’t let the simple description fool you though; data integration is a complex process that requires both business and technical resources collaborating efficiently across the entire organization to fully align data gathering and storage. One way to ensure that your company maintains an effective data integration program is by setting up a data integration framework.

Our approach to Visitor Stitching simplifies the complexity by focusing on a single point of the customer journey with a simple goal—deliver more meaningful communication to an individual by bringing two data sets together. The simple example of this that everyone sees in daily life comes from emails that retarget based upon products viewed and/or purchased.

Visitor Stitching takes the same concept and applies it to other elements in the customer journey that, historically, an organization may not have thought to optimize or personalize previously:

  • Post-purchase messaging
    • Determine whether a purchasing customer lacks an important asset and message appropriately
      • Lack of a mobile app
      • Lack of a loyalty credit card
  • Recognition of friction in the customer journey
    • Introduce a chat window
  • Initial engagement with a digital experience
    • Transfer behavior from a previous session to “deep-link” a session
      • Home page/screen contains a specific product search that was “abandoned” in a previous session
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5 aspects of designing an effective data integration framework

  1. Understanding why. One of the first (and most natural) questions that comes up for most organizations is why such a large investment of time and resources is necessary. “Aren’t we already using digital data to remarket to key audiences?” the digital manager may ask. The answer is that users are not reserved to just the digital space; there is a host of financial, demographic, and other behavioral attributes that help define a user.

    Understanding and creating that complete picture of a user, versus using an incomplete or fragmented picture, will help drive more efficient business decisions. Simply put, combining data and creating a holistic view of the user enables organizations to provide a better experience to their users.
     

  2. Everyone needs to be involved. While this may be a slight overstatement, the overall point remains true. Integrating data sources across an organization requires buy-in from all of the departments that collect, house, and utilize data. Members from the finance team to the digital analytics team need to be involved in uniting data sources and utilizing this data to make effective business decisions. Data integration does not work well if a branch of an organization refuses to participate.
     
  3. Choose the right technology. For most organizations, data integration will require an investment in a data warehouse or some other data management solution, along with a data connector. While there are general best practices for the data integration process, each organization has at least a slightly different set of data and thus, a slightly different challenge. It’s important to appropriately research what solution will provide the easiest, yet most robust solution for your company. This is where it can be beneficial to seek outside help from media and marketing analytics specialists.
     
  4. Map the Customer Journey. An organization cannot deliver on a proper data activation plan as part of a data integration project, unless the customer journey (online and offline) has been mapped to better understand how the data can be utilized to drive more effective communication and messaging.
     
  5. Identify a Short-term, Medium-Term, and Longer-Term Value. While a data integration project can be a large undertaking measured in years, it is important to utilize the mapping of the customer journey to identify areas where data integration can drive better, more meaningful messaging to the customer that requires the integration of 2 or possibly 3 datasets that require “minimal” effort.  We utilize this approach because most individuals cannot go back to their bosses with a large-scale plan that will only realize value at the very end. ROI needs to be more “Agile” than “Waterfall.”
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Start providing a better customer experience

When it comes down to it, data integration is undoubtedly the future of data for almost every organization. Having one cohesive view of your users and customers that powers targeted messaging and business decisions is an absolute necessity.

With this being such a critical topic in 2018, we recently released part 2 of 3 in our Digital Transformation Viewpoint series on Visitor Stitching (click here to download). This guide helps demonstrate how leading brands can increase their customer intelligence by uniting datasets across every available channel to create one customer-centric dataset, ultimately resulting in more personalized and efficient customer experiences.

Want to learn more about how you too can begin stitching the pieces of the data puzzle together? Speak with one of our data integration experts today by filling out the form below or emailing us at info.US@ebiquity.com.

By Casey Judson
About the Author:

Casey Judson is an Analyst, Team Lead at Stratigent

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