Recently, we had the opportunity to chat with Thomas, PhD. in Astrophysics and VP of Digital Client Experience at a leading research and advisory company. While the company’s core product is precise and reliable research, that data is of little value to their clients if it is not rapidly accessible digitally, easily digestible, and instantly applicable. This is where Thomas plays a critical role as Group VP responsible for maximizing the value of the company’s research through the client’s multi-platform digital experience. In our interview together, he shared how his team is able to operate with startup-like speed by approaching tough challenges and questions with the scientific method, and pulling from that data to drive their decision-making.
The objective of Thomas’s team is fairly conventional: “Every company that has a web presence is concerned about the digital client experience. We’re simply asking, ‘How can we make our experience work really well?’” Of course, serving clients in over 10,000 enterprises spread across 100 countries adds several layers of complexity. Expanding on some the challenges his team faces, he explained, “In every company, especially larger, more established ones, there is always tension between adding capabilities or features, and enhancing usability from what’s already there.” In his line of work, this tension is felt regularly with questions like, “Should we invest in new ways of slicing and dicing our data, or should we invest in ways of making the data truly effortless to digest?”
Situations like these are common in every company. There’s an opportunity to innovate or a gut feeling that something needs to change, and the question is asked, “What should we do?” Unfortunately, in many larger organizations, those questions quickly begin to pile up unanswered. What is far less common, and what sets Thomas and his team apart, is a process to systematically address these questions, and then hypothesize, test, and measure the success of the solutions: the scientific method scaled for the enterprise.
While there is an infinite amount of metrics to chart, Thomas’s bottom-line measure of success (or “one metric that matters”) is the renewal rate of the company’s subscription-based access to research. With that goal in mind, the prioritization of different initiatives and experiments can be vetted by hypothesizing how much that metric will be impacted (if successful).
When it comes to designing experiments to improve that metric, here Thomas bows to data’s expertise: “We don’t know what we’re doing; the client does.” Leaning into client data and learning to trust customer insights over industry’s conventional standards or personal opinions derived out over months of meetings is how his company has been able to consistently improve their research and delivery methods. “We try to be as much like a startup as possible and apply Lean Startup principles wherever we can.” How these principles translate for Thomas is trusting their data to make decisions faster.
In order to have enough data to inform their decisions, the research company invests in large sales and service teams so that they can engage with and understand their clients at various stages–a “luxury” Thomas recognizes that true startups can’t often afford. While they make use of surveys when quantitative data is needed, such as trying to assess the estimated monetary value gained from certain research provided, most of their engagement with clients is in the form of loosely-structured interviews or in-depth conversations. “Surveys just won’t give you the same amount of information from a client that a real conversation will,” said Thomas.
By investing in qualitative and quantitative data from their clients, this has created a wealth of knowledge that not only enables them to consistently identify opportunities to innovate within their company, but also to react quickly and confidently to changes in their clients’ industries and technology. In an effort to move faster, more and more companies sensitive to implications of the digital revolution will be following Thomas’s model and leaning heavily into data-driven decision making.
Differential is a digital innovation agency. We use a startup-like approach to enable partners to invent, prototype, test and build digital products that drive growth and keep them ahead of the innovation curve.