Applying research and data across the organization
Editor’s note: Matt Schaefer is senior director, research and insights, GBK Collective.
While every company aspires to make data and insights actionable, the reality is that many research and analytics investments fall short or fail to deliver the desired impact. According to Gartner (registration required), 54% of CMOs and VPs of marketing aren’t impressed by the insights their research or data analytics team provides. They cite “poor data quality, unactionable results and nebulous recommendations” as the top reasons.
The inability to demonstrate ROI directly maps to how companies approach research and apply insights and data across their organization. Too often, we see firms conduct quick-turn studies that lack focus or attempt to boil the ocean. The result is a buffet of data disconnected from strategy, and before long the report ends up sitting on the shelf, gathering dust.
In marketing, for those tasked with insights and growth, few things are more advantageous and rarer than clarity. Your business and marketing challenges do not fit into a neat box. And neither should your research.
Maximizing the impact of research
To achieve clarity and unlock new insights to apply to decision-making across marketing, product strategy or other areas, you need to understand your company’s specific business goals.
Who are your customers and what are their needs? What are the strategic priorities? What business decisions does the research and data need to inform? What are the three to five most important questions that you need to answer about your customers – or non-customers – to make better, more confident decisions?
It is these questions – and their unique answers – that should guide the design of your next research project. Clarity rarely comes in a box.
Start with the end in mind
Here’s an approach I’ve found helpful when thinking about how to design a project:
- Start with the customer need, the business questions you need to answer.
- Translate those business questions into a product brief – high-level research questions that need to be answered to address each business question.
- Translate those research questions into product specs – the actual survey questions and techniques that will address each research question.
- Collect data and develop a deliverable, a product, with business needs in mind.
Thinking ahead is key. As my colleague, Brian Smith, shares, “To improve ROI, marketers first have to think deeply about the business problem and identify the key strategic questions they need to answer through data and customer insights. In addition to taking a hypothesis-driven approach, companies also have to have the right analytic tools and processes in place to effectively apply better data across the organization. That’s the only way to make the best use of their team’s time and their research and analytics partners. To help our clients, we need to be business strategists first and foremost.”
Design around a problem, not a “solution”
Let’s say you have a central business question: How can our brand best and uniquely compete in the marketplace? As a consumer insight professional, how might you start to answer that question? Don’t reach for a “solution” just yet. Start by translating the business question into the high-level research questions that need to be answered to address the business question. These questions might include:
- How do attitudes and behaviors differ for our customers vs. our competitors’ customers?
- How do purchase motivators differ by customer segment?
- How do brand perceptions differ for our customers vs. our competitors’ customers?
Once you – and key stakeholders – are confident that these are the right research questions, then you can start to design a survey outline – and eventually a survey – that breaks down each research question into concrete survey questions and techniques (e.g., MaxDiff). Then, review and prioritize.
Which of these answer the research questions as you’ve outlined them? Are there any other questions you need to add? Are they phrased in a clear and effective way, where you will confidently and reliably be able to interpret the results? Which questions are essential vs. nice-to-have? What do other stakeholders think? Last, but not least, are there any blind spots?
When you take the above approach, you can connect the dots between your research questions and the ultimate business questions you need to answer. As a result, you will be able to make a compelling case to stakeholders that you are taking a strategic and prioritized approach, ensuring the output of the research truly delivers value and maps to the needs of the business.
Keep the end in mind and focus on the story behind the data
We know from neuroscience research that stories are critical to understanding data. Without a story, reports can feel like an amalgamation of loosely associated data points. Instead of throwing everything but the kitchen sink into the body of a report, it is more impactful to focus on the insights that matter most. (If everything’s important, nothing’s important and the forest is lost for the trees.)
I find it worth asking: What data and insights are immediately actionable? What are the key takeaways for different stakeholders that ladder up to the company’s priorities? Where are important and relevant nuances among different groups of respondents (Where is there heterogeneity?)? And where can we bring qualitative insights and desk research to the fore to bring the findings into high resolution? What does the resulting data mean for the business?
Each section of your presentation needs to serve a purpose in telling the story behind the data. In addition to slides with clear headlines that capture each research question you answered, you may also want to call out:
- Fundamental truths about each customer base.
- Significant differences between customer bases.
- Stakeholder hypotheses that had been validated or rejected.
Research needs to be presented in a way where the story and key takeaways are shared in a strategic context. Analytics techniques like MaxDiff, fair share analysis and XGBoost key driver analysis can uncover hidden, but meaningful, patterns in the response data. Layer in secondary data sources. Ultimately, you want to make sure that the report is insightful and easy for stakeholders of all stripes to understand, absorb, discuss, debate and act.
Increasing impact and actionability of research
If you use the above approach as a guide, you can increase the impact and actionability of your research. You’ll provide more clarity for your stakeholders. Few things are more advantageous and rarer than clarity.