How Brand Insights Organizations are Adapting and Evolving in Order to Succeed

OGC Global had the pleasure of moderating an insightful panel at IIEX, featuring thought leaders who are at the forefront of transforming insights practices: Gregory Wester, CMO at Digital Turbine, and Ken Athaide Senior Manager at Cox Business, moderated by John Schiela, GM at OGC Global. Additional insights from guests not on the panel include Khary Y. Campbell, MBA VP of Consumer Research and Insights at Comcast, and Serena Li at Strava. 

Our discussion centered on the critical challenges that insights organizations face today—from shrinking budgets and the need for faster turnaround times to the quest for deeper and more actionable insights. The panelists shared their experiences and strategies that have reshaped their operations to not only cope with these challenges but also to excel in delivering value. 

Key Takeaways Include: 

Strategic Sourcing: Developing a balanced framework for evolving your insights approach through a smart mix of in-house and outsourced resources. 

Data Management: Leveraging trackers and syndicated data effectively to continuously unearth fresh and impactful insights. 

Technological Advancement: How AI and enhanced observational data are setting new benchmarks in insight generation.

Data Integration: The transformative power of merging internal data with marketing analytics, third-party data, and survey research to create a holistic view.

Read on to explore specific questions we asked at the conference and the invaluable perspectives our panelists shared. 

 

In an era where business agility and deep insights are paramount, how do brand insights organizations adapt and thrive?

1) Insights teams must continuously align their trackers and syndicated data with evolving business objectives to deliver impactful insights. How do you tackle these challenges?

Ken Athaide: 

• Trackers need to be heavily structured so that new entrants/products/campaigns can be fit into the right places and in the right ways.  Having a tight structure allows you to insert/remove/adjust components as the market evolves. What may seem counter-intuitive is that the tighter the structure of the tracker, the better able you are to adjust to changes and be responsive to the needs of the business.
• In analysis and reporting, when updating a tracking program it is critically important to adjust for market changes by clearly communicating pre/post changes to key metrics and, at times, continuing to report the historic metrics with the new ones until the business has adjusted.

Serena Li: 

• The business objectives are evolving faster today than ever, and it’s especially true for a tech organization like us. One way we tackle this is by working with our agency partners to build maximum flexibility into our research studies so that we can adapt in response to the changing business needs. It also means anticipating and planning for all possible scenarios and making sure we have room to maneuver. Keeping our research partners very close is key, and making sure they’re updated with the latest has also been helpful in re-aligning the research to address evolving needs. For example, we have weekly check-ins with our agency partners even when it’s not the research planning or reporting period, so they’re always up to date with what’s going on with the business.

 

2) As budgets tighten and timelines shorten, the fast-paced business environment— fueled by technology, instant media, and consumer demand — requires research insights that are both impactful and swift. How do you see the challenge of delivering better, faster, and cheaper insights evolving, and how have you addressed this through agile research platforms, a mix of in-sourcing and outsourcing, or other strategies?

Serena Li: 

• Both our internal team and our agency partners are utilizing agile research platforms quite a lot. It has been effective in answering certain questions and delivering actionable insights. For us, there’s an increasing appetite for more swift research and questions around whether the traditional large-scale research still has value. While I believe research can be done faster and cheaper in a lot of places, I think we need to be careful as agile research is not for answering all business questions. Without the right methodology, the findings can lead to bad business decisions. A mix of in-sourcing and outsourcing is where we’re going. 

Ken Athaide: 

• One of the most difficult issues in this faster-paced world is figuring out which market changes are significant and when/how to adjust your business accordingly. Marketing and Sales organizations need time to understand, absorb, and develop changes in response to market events.
• The temptation is to react quickly and to have the organization swing from one competitive response to another – a process which often diminishes the value of the research in the eyes of those who have to respond quickly. The challenge, therefore, isn’t really about obtaining and processing the data. It’s about determining which market events require a response and which ones don’t, at least not in the short term.

Greg Wester: 

• As a bit of contextual background, our firm conducts research for various business goals. Within Marketing, we primarily invest in research for thought leadership, content marketing, PR, and overall awareness. For me, “better” means rare, differentiated, not yet discovered, and offering a unique angle that prompts media coverage. “Faster” refers not only to the execution of the research but also to its integration into our sales materials, social media, paid media, and earned media. This requires significant focus and executional cadences. 
• Finally, I view “cheaper” as a barter deal. If my team can identify truly “better” research and effectively get it picked up by the media, it often leads to barter deals with our research vendors, swapping soft costs for mutually beneficial PR, stage, or media time. We strive to achieve all of this within a holistic go-to-market plan for all of our research.

 

3) The buzzword of the conference has been AI, how do you see AI impacting the research world, and where have you or are you looking into deploying it within your organization?

Khary Campbell: 

• I think AI is going to make the biggest impact in research if you can integrate it with your overall ecosystem. Find a way to take the capabilities and plug in other data sources, and into decision points that happen in your business. If you’re in a larger organization, it might get you to some of the outputs or the consideration points for an LRP process. If you’re running a smaller business, it might help you with doing some of the administrative task work so you can focus more on research and execution. I just think the more people are willing to try new things and challenge themselves to get away from what they’ve known in the past and find a new way to evolve it, all those things will be a big factor. I’m very optimistic about what is to come. 

Serena Li:

• I see AI help us in 2 ways: 1) Increase operational efficiency, especially for qualitative research: Many of my peers have already been implementing AI into their work for this use case. I think many can attest to the fact that AI significantly boosts productivity for qualitative researchers. However, with the AI we have today, I don’t see it replacing human researchers any time soon, as it tends to generalize things and miss the nuances, which is exactly what we need human researchers to look for in the research.
• 2) Provide creative inspiration: AI can be a valuable tool for kickstarting the creative process, generating ideas, and providing thought-starters that might eventually lead to real-world outcomes (e.g., product or marketing concepts). At IIEX, Steve from Zappi talked about how researchers can do a reverse takeover of marketing. With the help of AI, researchers can turn insights into marketing concepts. It will help elevate the research function and help researchers make a greater impact.

Ken Athaide: 

• I first would like to see AI prove its value in automating the mundane tasks of data acquisition, merging, cleaning, and loading. As I shared at the conference, a good researcher can sniff out bad data pretty quickly and easily. Data has to pass the “smell test” before you do anything with it.
• Perhaps AI should focus on this sense of smell and be applied to identify (and maybe fix) data anomalies and inconsistencies that nearly always show up in research and analytic projects.

Greg Wester: 

• I’m seeing AI impact us in two areas currently, and I’m hopeful for one other area ASAP. The first area is in the creation of survey instruments. A couple of tools we use greatly simplify the transition from writing questions in a Word doc to having a functional survey. The second area is around the querying of syndicated research databases. Not having to know the source, survey variable, or question, and rather being able to query in English, transforms speed and discovery.
• The area where I haven’t seen anything yet but am very hopeful is the use of generative AI to, for example, scan a research report on, say, the automotive intender audience, which is based on a large sample of data, then create a duplicate report that, let’s say, is focused on the traveler or high-tech enthusiast audience. That would be a game changer for B2B marketers.

 

4) Many organizations possess vast amounts of research data, internal data, observational data, and licensed third-party data, often siloed and producing conflicting insights. How do you think you could address this challenge and effectively integrate these diverse data sources to generate better insights?

Khary Campbell: 

• So, most organizations have more data than they’ll ever use or need and it’s pretty understandable why. There are many teams, groups, and organizations in the enterprise, so they need different types of data for different reasons. The first step is understanding where all the data is coming from. What is it? What is it used for? Do you have an actual data strategy? And from there, how do you recognize what is going to be the source of truth for your data, because we have so many different streams of data coming in, it can create some very confusing metrics that are different from each other. 
• The way I try to explain to people is I used to call it a kind of insights triangle. Now it’s a bit of an insight square, and it works well for my setting. And so, you have what consumers say they’re going to do, and you have what consumers are doing. So how do we take what consumers are doing, what they say they’re doing, or their perception, and understand the why? And then that next corner is how happy are they doing it. Data in a lot of places exists in those four corners. 

Serena Li: 

• Three key elements need to work in harmony to effectively integrate the diverse data: the people, the process, and the technology.

• In terms of people, we formed a committee with data and insights leads that consists of those responsible for research data, internal data, observational data, and licensed third-party data respectively. The committee has an agreed process for sharing insights with the wider organization, where the insights leads meet and discuss the findings prior to any share-out to avoid conflicting voices. As for technology, we’re constantly trying to bring all data into one single platform. No matter where the data comes from, be it ad-hoc market research or syndicated data, we try our best to feed the data into our data warehouse so that we have one source of truth.

Ken Athaide: 

• We have a large set of data from internal operations, third-party providers, and market events. At the moment, we are building frameworks to integrate these into our internal data lakes.
• While we are often approached by third-party data integrators who promise to align everything, we have yet to move forward with any integration options as we feel we have the best understanding of the strengths and weaknesses of the data sets.

 

5) An insights organization must first gather quality data, then extract insights, and finally tell a compelling story. How do you ensure each step receives proper attention? Could you share examples of how your organization not only crafts insightful stories but also effectively communicates and disseminates them?

Ken Athaide:

• This takes time or, at least, it has taken a lot of time in the past. It’s very hard to provide useful insights without fully understanding the data, particularly how it is used appropriately. Each step in the process requires some level of discussion, review, and refining, understanding that the best insights come through collaboration and testing of ideas. 
• As I shared at IIEX, we (try to) start every project with a written “brief” in which the end users are asked to provide details about exactly what they want to find out, who’s the audience and what time and budget limits they have. When we do this, we can obtain the right data. Then we move to a collaborative analytic program where we share preliminary results, gather additional questions, and continue to probe the data to get clear and simple answers (which can be found if you write the brief properly).

Serena Li:

• While researchers put a lot of blood, sweat, and tears into ensuring we gather quality data, I don’t think internal stakeholders care much about the hard work that went into the process of extracting insights. Internal stakeholders need an answer to their business question and clear recommendations and directions on what to do next.
• The communication of insights is arguably the most important step. Without effective communication, the whole project fails. For us, to increase audience engagement, we’re constantly trying creative ways to socialize the insights, including podcasts, newsletters, and short-form presentations at company all-hands. When disseminating insight stories, we almost need to aim for over-communication to get the proper level of attention.

 

6) What are the biggest challenges facing you today and what would you like the industry to offer to solve these challenges?

Ken Athaide: 

• I think understanding data is the biggest issue we face. Our data is fairly clean, but there are lots of intricacies to it and those are sometimes only known by very experienced analysts and database experts. 
• When this data is shared, the context must be also fully shared so that we avoid misuse or misinterpretations. At the end of the day, I need the industry to train stronger analysts who understand data, are less enthralled with models and tools, and are more conscientious about the data inputs, processes, and quality.

Serena Li:

• With the increasing amount of data, we have access to today and the world becoming more data-driven, there’s more and more pressure to measure what used to be immeasurable and quantitatively understand the “art” part of marketing. I’d like the industry to help make the intangible tangible and draw a clearer line between what we measure and the business outcomes.
• To be very specific, one thing I’d like the industry to help solve is the age-old question around the correlation between brand equity and business growth. We all know the importance of building brand equity, but as an industry, I don’t think we’ve quantitatively proven how the increase in brand equity score influences sales. I think this is one reason we’re seeing more and more budget being allocated to performance marketing, where there’s a clearer connection between investment and return.

Greg Wester: 

• The main and first step is actually coming up with great hypotheses. Most people can’t. They tend to say, “Hey, let’s add this question to our omnibus or next survey.” I’ll ask them to “start at the end.” Rather than writing questions, write the sexiest headline imaginable. Make it a game. Reward the most creative and thoughtful story.
• Great insight and great storytelling are also very tough for the same person. I’d suggest splitting that responsibility and accountability, not having the same person accountable for both. Empowering one person or one function to do both undermines your impact. I believe that marketing starts with stories . . . numbers of power stories . . . and research powers numbers. But completing this cycle requires coordinated teamwork. Finally, coach storytelling. Most business people suck at storytelling, including too much info, too much about us, and no narrative. In marketing, the job of a story is not to impart information, it is to accelerate change. Stories must be sharp to cut into the mind of the customer.
• And for all marketing managers: this year, stuff your team’s holiday stockings with the book “Presenting to Win” by Jerry Weissman. My team has heard me utter, “What’s your Point A, what’s your Point B, and what’s the WIIFY?” a thousand times.