Communicating Research for Impact
Simple strategies for researchers in tech to drive change
Clear, crisp, and actionable communication is key for researchers in tech to influence product and business decision making at scale.
Abstract or lengthy research reports and presentations often fall flat because stakeholders — especially leaders — don’t have time to comb through these deliverables identifying key findings or what to do next. Consequently, important research not only goes to waste, but poor communication can erode a research team’s reputation and long-term ability to deliver value.
These communication strategies can help researchers have the most impact, especially as companies grow:
- Start with the most important insight
- Curate instead of saturate
- Have a point-of-view
Researchers often receive little training on how to frame their work even though it’s just as important as prioritizing the right research question, selecting an appropriate research design, and conducting rigorous analyses. The framework presented here serves as a simple and repeatable starting point to turn data into insights that get implemented.
Start with the most important insight
Think back to the last research presentation you attended. What content was shared first? Nine times out of ten, it started with background information and methodology. While both provide useful context, they shouldn’t go first.
Instead, researchers should open with the main insight from their work. Going directly to what matters most avoids what journalists call “burying the lede,” which can distract or cause viewers to tune out. Don’t give your audience another reason to check their phones.
A research “insight” is a data-driven finding, plus an explanation for why it’s relevant (e.g., the what + the so what). In my experience, the primary insight from a project isn’t the result of a single data-point, but rather the amalgamation of multiple findings that demonstrate a larger, and often less obvious, theme.
Identifying the most important insight takes reflection and iteration. Here are a few tips to help:
- Return to where you started: Revisit your primary research question and UX (business/marketing) goal. Circling back to why you did this work is a good starting point, but you’ll likely need to dig deeper for more precision and nuance.
- Track what’s surprising: Record potential insights as data come in. It’s easier to identify something you’re actively looking for, instead of waiting until the end of a project. Documenting learnings also helps you remember what was initially compelling even after spending a lot of time with the same data. Be careful of bias due to ordering effects. Is this the most significant insight or just the first/last thing you learned?
- Make it personal: Connect the dots between this research and what stakeholders care about and need to deliver. Make sense of the material for them so they don’t have to.
- Keep it short: Your most important insight should be 1–2 sentences. It can help to separate the insight from supporting evidence to highlight later.
- Find the right level of specificity: Avoid being vague or too detailed. It’s useful to have a specific leader in mind when determining the right altitude for insights. If your CEO will find it compelling, you’re probably on the right track.
Curate instead of saturate
Both qualitative and quantitative research can generate a lot of valuable and exciting data. Unfortunately, it’s possible to have too much of a good thing when excessive data overwhelm an audience. To prioritize the right content, focus on data that directly support your insights or recommendations. While you don’t want to cherry pick findings (because this introduces bias), you should be strategic about selecting and presenting evidence to corroborate them. Ten charts are often less persuasive than a single one with the right information.
Have a point-of-view
To drive change, It’s important that researchers make recommendations on what should happen based on their work. For example, what’s the right product strategy to address opportunities or challenges the research revealed? What UX updates should be implemented before launch and why should they be prioritized? Recommendations shouldn’t focus on doing additional follow-up studies, even when necessary, because this misses an opportunity for researchers to add value as subject-matter experts and thought partners.
Making recommendations empowers researchers to articulate next steps instead of waiting for others to do so — which might not happen. It also elicits real-time feedback to identify misalignment and gives cross functional partners something to respond to. Even if they disagree (which they often will), suggesting a specific course of action, rather than asking them to generate on-the-spot solutions through hypotheticals or “how might we” prompts, makes it easier to come up with concrete next steps.
As tech companies continue to operate at unprecedented speeds and more data become available, it’s never been more important to communicate research in ways that drive impact. The framework presented here is a starting point to help researchers communicate content effectively and meaningfully. Getting these basics in place not only makes it easier to get insights implemented, it also creates room for researchers to develop an authentic style and communicate in new and creative ways.