Key Strategies For A High Performing Data & Analytics Program (Part II)

Analytics | January 24, 2019

3 Keys To Creating A High Performing Digital Analytics Program

What are 3 key things brands should focus on in creating a high performing digital analytics program?

1. Identifying an analytics leader who can clearly see the business problems that analytics can address and propose solutions that will generate positive ROI.

Successful analytics programs take a consolidated group effort. Success hinges on how well the organization utilizes internal domain knowledge, supplemented at times by external expertise to monetize data opportunities. Large enterprise companies may be lucky enough to have a Chief Analytics Officer in place with strong executive sponsorship and oversight. A Director/VP of Analytics should be knowledgeable enough to play the connective tissue between the executives and true subject matter experts.

This Director or VP role will make the business case for the programs in play (and the technology that deploys them) and can answer to the ROI of the program. This individual will be tasked with assessing people, processes, and platforms needed. He or she must also be able to decide when to buy, borrow, or build talent and technology to address the opportunities at hand.

The most common failure point for an analytics program stems from not having a clear and universal alignment on what problem the analytics team is trying to solve for. Companies invest in staff and technology to pump out models and insights – but left unguided, those solutions may not specifically address a business problem. Those squandered hours reduce the expected ROI of the program. Once it becomes a frequent issue, the Finance Team (or even the CFO) starts questioning the value of the program and the technology driving them. Without clear alignment, analytics programs may see their future budgets reduced and their perceived value in the organization diminish. Getting the right person involved up front, and identifying the problem the team is looking to solve will help drive successful outcomes.

2. Focus on the foundational elements of measurement. Evaluate and define the business requirements, create and update a Solution Design Reference (SDR) that maps to the requirements and then implement it.

An SDR is a Solution Design Reference spreadsheet that documents all business questions and proposed variables that capture data relating to those questions. It is the foundation of any analytics implementation and its quality can be the difference between success and failure.

The SDR is a blueprint of a digital analytics implementation. SDRs provides many benefits to an organization but three acute benefits are they help:

  • Define business requirements identified by stakeholders
  • Map those requirements to variables in the analytics solutions
  • Facilitate staff understanding the implementation and variable definitions

Creating and consistently updating an SDR is a critical first step in creating a high performing digital analytics program. The process will enable organizations to capture the right data, instill trust in that data, and then allow downstream actions to be taken with confidence.

3. Invest in the necessary technology to accurately capture data, store it, make it accessible for analysis, and enable real-time action to be taken on it.

A technology stack needs to work together. The solutions and systems within that stack need to be robust and cover an organization’s business, as well as their data supply chain to provide the desired end-to-end outcomes. At the very least, a company will need several tools in their marketing technology stack – a tag management solution, a data enrichment and management platform, a data visualization tool, a method to store and extract data, and a seamless way to deliver optimal customer experiences at scale. An organization may have the right leader, identify the right problems, have all of the documentation, and be collecting the right data – but ROI on that data will not be achieved without having the right technology stack in place.

There are 2 ways technology can deliver ROI to an organization:

  • Technologically-empowered marketing efforts across channels (optimization and personalization, email channels, in-app experiences, push notifications, etc.) provide a direct way to reach customers in real time and actually change the outcome of their digital experience – thus driving measurable ROI.
  • Insights discovered from digital properties uniquely highlight how users are engaging with a brand and can surface powerful information to the rest of the organization. Digital programs and technology allow for first-party data capture and insights gleaned from them can direct overall brand strategy and competitive differentiation, inform in-store decisions, and better equip customer service channels.

It’s important brands identify an analytics leader who can effectively identify the business problems at hand, institute and follow accurate measurement processes, and invest in the necessary technology. These three steps will provide a head start in ensuring a high performing data and analytics program.

NOTE: This content was originally posted by Tealium in an Industry Expert Series, and can be found here.


Reid Bryant is responsible for building a world-class team focused on creating and capturing value through the sophisticated application of data science to analytics, optimization, and personalization. He brings over 13 years of expertise in quantitative fields and has led high performing optimization and analytics programs at clients like Microsoft, Barnes & Noble, Bank of America, Viacom, the Gap, Humana, Johnson & Johnson, and Chic-fil-A. He is a co-founder of the Raleigh Chapter of the Digital Analytics Association and provides digital marketing analytics lectures at the Institute for Advanced Analytics at NC State University as well as Duke University’s Fuqua School of Business.