If you’re a research & analytics professional, one of these scenarios is probably familiar: You send a hyper-detailed data report to a manager and hear nothing for weeks. You show a colleague pages of methodology and their eyes glaze over. You summarize every finding in a data set for a marketer (beyond the scope of their request) only to be asked to explain “so my five-year-old can understand.”
While we’re comfortable working with raw data (and for the true geeks, even salivate over it!), most people see it as complex, technical and challenging to grasp. That’s exactly why they’ve turned to us to handle it.
In a previous job, I worked with a guy I’ll call Jeremy who was a sharp thinker but had a short attention span. Whenever I talked to him about a project, I’d have to grab his attention, get to the point quickly and offer clear instructions on what to do next. I came to think about him whenever I started a new project. It turned out the “Jeremy template” served as the perfect executive summary for most readers. From there, I tailored the body of the report to the audience at hand. I learned quickly that audiences want inspiration, information and instruction. I find out how much they need by asking myself the following questions:
- Do they want to speak or read?
- What’s their technical knowledge and understanding of research and analytics?
- What’s their attention span/how much time do they have?
- What do they need to know?
- What do they want to do with this information?
- What specific piece(s) of information will delight them?
After 14 years in this field, I’ve developed a framework that I apply to every interaction - whether I have 2 minutes or 2 hours to share. The goal is to prompt an “Oh wow!” from my audience 3 times:
“Oh Wow! I didn’t know consumers wanted that / needed that / felt that.”
“Oh Wow! You did your homework.”
“Oh Wow! We can totally do that.”
Step 1: Present your findings
(Goal: “Oh wow! I didn’t know consumers wanted that / needed that / felt that.”)
Whether they’re statisticians, marketers or corporate executives, show your audience you’ve researched their needs and tailored the learning to them. You can’t get away with a one-size-fits-all approach.
Step 2: Present your methodology
(Goal: “Oh wow! You did your homework.”)
Flex your analyst muscles. But remember: if your audience doesn’t have the same expertise as you, they won’t be impressed by the fact you did structural equation modelling – and they may entirely miss the big takeaway in your findings. They might need to know nothing more than that your work comes from “rigorous math”.
Step 3: Present your recommendation
(Goal: “Oh wow! We can totally do that.”)
When you delivered your findings, you told your audience something powerful and created a point of tension. Now you have to tell them what to do with those findings. For a marketer, that may be advice on how to shape their campaign. Whatever your recommendation, this is where it’s most important to step away from the technical and highlight what elements are actionable in clear language.
As a data specialist you’re doing the work of a translator: finding patterns in the numbers and making them digestible. Be brief, be brilliant, and be gone.