5 Takeaways from an Intellus Newbie

5 Takeaways from an Intellus Newbie

Having spent 25 years in the consumer research sector (finance, CPG, retail, tech, etc), I am used to attending conferences and seeing many familiar faces. Now, with a switch to Life Sciences, I just attended my first Intellus Summit in Charlotte, and was surprised that for such a “small world” industry, I didn’t run across a single person I knew. While I missed my conference buddies, I loved the opportunity to make new connections! I met a lot of super smart folks and learned a tremendous amount about this ever-changing industry. 

While the context of the discussions might have been different from the consumer side of the world, the challenges are largely the same. The market research world is evolving fast, and this year’s key themes were all about integration, speed, and making insights truly actionable.

Here are my five takeaways:

1. Analytics & Insights Must Be Integrated
Secondary data is no longer an afterthought—it’s essential. The ability to merge it seamlessly with primary research leads to faster and more impactful decision-making. Segmentation is the prime area where secondary and primary data are merged, and that allows for more robust and longer-lived models than we’ve seen in the past. However, to do this effectively, teams need the right in-house skill sets (such as data scientists) for data aggregation.

2. Storytelling is Non-Negotiable
Executives (and increasingly client-side researchers) expect insights to be delivered in a compelling, actionable way. This trend has been around for a while in consumer research, but it’s new to pharmaceutical research. Storytelling is focusing on the business challenge (and solutions) and not solely on the research question. This is an opportunity for us to step in, differentiate, and help the listeners (and research users) digest information and provide action steps to ensure insights don’t just sit in a deck but actually drive decisions.

3. Speed vs. Quality – It’s Not Either/Or
We need to challenge old assumptions about trade-offs between speed and time. Effective and iterative collaboration may be the key here: often there’s no reason to wait for the qual phase to end to start with quant. Similarly, if you’re running 20 IDIs, and after 12, the story is clear, repurpose the rest for something else that helps you deliver answers to the business problem. Move faster without sacrificing depth by thinking differently, improving communication, and using rolling deliverables.

4. AI is an Enabler But Not Always the Answer
AI was a hot topic at Intellus, with the consensus that it would transform tasks like coding, transcription, and data cleaning. However manual methods still hold their own in many cases. The key? Knowing when AI is worth the investment (and not just financial, but time!) and when traditional methods get the job done faster and better. Sometimes, preparing the grounds to use AI for a task takes more time than doing it the “old-fashioned” way.

5. Knowledge Management is a Hidden Gold Mine
AI-powered repositories are game-changers for insight mining. It has been said, “Whoever owns the data owns the world” and this cannot be more true today. As we develop reports and findings that go into knowledge repositories, we have to think about making it easy for companies to search these resources. Using metadata to tag and structure research streamlines the process of locating and utilizing past learnings effectively.

The common thread? Research is becoming more dynamic, integrated, and strategic. As we navigate these shifts, those who embrace innovation—while keeping an eye on practicality—will have a competitive edge. And while technical know-how is table stakes, true value comes from business acumen and a deep understanding of the core business. Researchers who can connect the dots between data, business strategy, and technology will lead the way. Looking forward to next year and seeing familiar faces!

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