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Today’s understanding of “Analytics” has become very flat. I’ve encountered a lot of folks who think of Analytics as a one-dimensional “dump” in the form of a massive, untranslated, data-filled spreadsheet. This hasn’t always been the case; over the years Analytics has been viewed as being all-encompassing; siloed into specializations (such as web, media, social, CRM, etc.); focused on reporting and advanced data collection; etc. Whatever you think of when you hear the word Analytics, I’ll bet it falls somewhere far short of what a true Analytics team can actually achieve for your business.
The marketing industry and the technology supporting it have evolved drastically over the years, but the role of Analytics hasn’t kept pace. Yes, there’s more data than ever and more ways to use it. But the current state of “Analytics” as it’s understood in the industry — solely focused on reporting, with little measurable value — is far from where we want to be at 3Q. We’ve built a very different practice, one with a much broader focus that strategically aligns with our clients’ needs; we’ve defined our team and roles to accommodate (and take advantage of) the evolution of our industry.
For these reasons, we’re announcing a rebranding of our Analytics team to Decision Sciences. The decision (no pun intended) was influenced mainly by the reasons mentioned above, but most importantly it better represents what our practice is capable of delivering: broader coverage and support across all measurement, data technology, performance, insights, and optimization needs. Why “Decision Sciences”? By definition, Decision Sciences is a collaborative approach involving mathematical formulae, business tactics, technological applications, and behavioral sciences to help make data-driven decisions.
Our strategy exemplifies our differentiated thinking. We’re thinking very three-dimensionally and across a more of a complex spectrum, focused on end-to-end coverage for our clients’ data needs. This begins with the planning and strategy for data collection, includes delivery of insights from that data, and builds confidence in the decisions that data enables. Our goal is to leverage the available platforms to help our clients begin to better understand their customers (and future customers) and the experience that they’re creating for them.
Decision Sciences in Three Stages
We want to do more than make sure that we’re helping our clients reach maturity in data strategies, collection, and proper use of the technologies. Our use and understanding of the data has three stages: why something happened (Descriptive); what we should be doing about it (Prescriptive); and what else may happen from it (Predictive).
This helps us reach the “holy grail” of being able to better identify the right audiences, the right messaging, and the right moment/channel for engagement.
Different Brands Need Different Support
We fully recognize that brands today sit at different levels of maturity on the spectrum, with some having well planned-out and executed data strategies and collection in place and others struggling to reach this stage. We’ve made sure to align our thinking along that spectrum so that we can better partner with our clients at their respective levels of maturity. This will allow us to help them further evolve and grow in the areas that they’d like to strengthen — which we’ve broken down into measurement, data management, performance, insights, and optimization.
While we see each of these five categories as dependent on one another, we tend to look at each individually because we believe that every brand can have different levels of maturity within each category. For example, a brand may have their analytics platforms implemented well — but not comprehensively, perhaps because of a lack of a measurement strategy or because of insufficient planning. We define each of these five categories so that we can help our clients better understand, for each, both their maturity and our ability to support growth.
Lastly, what would a good Decision Sciences team be without robust and comprehensive data technology? We’ve got that covered: tag management and data collection; campaign and behavioral analysis tools that pair with attribution; and data management providing full visibility into your investments, understanding of cross-channel impact, and insight into your users and customers. This comprehensive stack enables brands to leverage these platforms along with our expertise in order to drive optimization leading to growth and efficiency across their experiences, investments, and media execution.
That’s a mouthful, right? If you take nothing else away from this post, remember this: analytics as you know it is capable of much, much more than you think. The right partner can turn that massive spreadsheet of years past into a wealth of insights and strategy that can unlock serious growth for your business.