Table of Contents
- The Great Reshuffle’s Impact on Insights Teams
- The Role of Storytelling in Insights
- Insights Repositories: Technology for Story-based Insights
While the full impact of The Great Reshuffle on the insights industry remains to be seen, there’s little question that our current high turnover environment presents insights teams with some unique challenges.
It’s likely that UX, CX, and market research professionals have spent more hours in training over the past 18 months than at any time before. And while fresh faces and new perspectives can add significant value to an insights team’s production, this environment creates unique challenges for teams that are serious about crafting and weaving holistic, continuous research narratives into their deliverables – stories that empower decision-makers with not just data snapshots, but the fuller context they need to make fully-data-driven decisions.
The fact is: The only way to combat secular economic – specifically, labor-force related reshuffling – trends on an insights team is to adopt methodologies and insights repository applications centered around storing, organizing, and democratizing insights in a way that allows important research narratives to live on through successive and transient research team generations.
The Great Reshuffle’s Impact on Insights Teams
According to recent reporting by NBC News, the US tech industry has eliminated tens of thousands of jobs in 2022. Tech executives and industry leaders cite inflationary concerns, rising interest rates, and new challenges in digital advertising ROI as crimping their financial outlooks.
The insights industry, of course, either overlaps or sits inside of the tech industry (depending on how you categorize these industries). Among the firms reporting mass layoffs is Momentive – in October 2022, it said in a regulatory filing that it had laid off 11% of its staff. Figures from privately-owned companies are, of course, harder to come by. But anyone with eyes on the insights space — or first-hand experience with on-the-ground research teams — is well-aware that workforce reduction has been a major theme of the past 9-12 months on insights teams around the world.
How High Turnover Impacts Insights Teams
High turnover makes life difficult for any team or department. But on insights teams where workflows and even insights themselves are not logged in any existing repository, high-turnover environments can be especially problematic.
First, high turnover can diminish the volume and quality of an insights team’s institutional knowledge. Team members who leave their jobs take with them a deep understanding of their team’s workflow processes. Training new team members to “pick up the slack” or replacing a team with a smaller team or a new specialist can be an expensive process.
Further, institutional knowledge extends far beyond workflows. On teams without an effective system-of-record in place, departing or laid-off team members take with them hosts of unrecorded or goes-without-saying information about their brand’s product or service that cannot be easily replaced. For example, research gaps and cross-project themes that have been of particular interest to researchers may not have been recorded like the insights gleaned and analyzed on a research project. Additionally, “negative” insights – that is, what insights teams learn by what’s not in the data – often have significant influence over how a research team plans and progresses. It’s simply not realistic to expect that every valuable insight driving an insights team’s efforts is recorded, codified, and easily accessible – especially without the aid of a research repository.
Additionally, of course, high turnover creates a sense of instability and uncertainty on an insights team. This goes without saying. When coworkers are laid off, remaining team members worry about their job and work quality often declines. And without the support of an insights repository that remains part of a team no matter who leaves, remaining researchers often express frustration at the inability to discover existing insights – ones previously known to researchers who have moved on to other companies or the location of which is not pegged to the logic of any centralized repository.
The Role of Storytelling in Insights
Before exploring the ways, a high-turnover UX, CX, and market research team’s primary goal is to deliver valuable insights that can help guide decision-making within your organization. To do this effectively, it’s important that insights teams take a holistic view of the research and insights they gather, and present them in a way that is both comprehensive and easily understandable to those who will be using them to make important decisions. This means going beyond just presenting raw data and numbers, and instead weaving a compelling narrative that illustrates the key insights and their significance.
In other words, effective insights deliverables (and, for that matter, research itself) is all about storytelling.
There are a few key reasons why a story-based — or storytelling — approach is so important for UX, CX, and market research teams.
First and foremost, a holistic, story-based framework for presenting insights helps to ensure that they are easily understood and actionable. When insights are presented in a clear and compelling way, decision-makers are more likely to be able to grasp their significance and use them to inform their strategies and actions. In contrast, when insights are presented in a fragmented or disorganized manner, they can be difficult to interpret and may be overlooked or ignored.
Additionally, a story-based approach to presenting insights helps to put them into context, which can be particularly valuable for decision-makers. By providing a clear picture of the background and context surrounding the insights, you can help decision-makers understand not only what the insights are, but why they matter and how they can be used to inform strategic decisions.
Another key reason why it’s important for UX, CX, and market research teams to be storytellers is that these kinds of stories build trust and credibility. When you present insights in a clear, holistic, and story-based manner, you are demonstrating a commitment to providing high-quality, reliable information that decision-makers can trust. This can help to establish your insights team as a valuable resource and partner within your organization and can help build trust and credibility with external stakeholders – clients, partners, etc.
Today’s Challenge for Insights Storytelling
In the context of high-turnover, and having established the unique importance of storytelling on insights teams, the challenge for insights teams today is clear:
When researchers come and go in rapid succession, how can an insights team manager maintain continuous stories across this revolving door of personnel? Stories that, ultimately, are required if decision-makers expect to make data-driven decisions in the context of the larger trends and narratives that give insights deliverables any meaning whatsoever?
Insights stories are ultimately about trends over time. Stories involve a succession of events – developments in the industry, advancements in technology, changes in consumer preferences, and how an insights team’s work has tracked these changes against their brand’s performance. No matter how many new faces might be on an insights team, a brand’s customers are part of a long and extended story.
Without a clear understanding of what kind of research has already been done, these stories are not forthcoming. And when researchers come and go at high frequency, connecting these dots becomes an almost impossible task. A study that may have added considerable value to an existing insights narrative – for example, one that confirms the direction of consumer sentiments regarding a particular product line – might
Solving the Stories Problem
By now, any tuned-in insights team is acutely aware of the importance of an insights repository solution toward helping researchers more easily access historical projects, identify trends, and share findings in the larger context of what methods were used to discover those insights.
An insights repository is a centralized platform or database where research and insights can be stored, organized, and accessed by members of an insights — UX, CX, or market research — team. This provides a number of benefits and makes possible a host of value-adding capabilities, including:
- Easy access to historical projects and insights. With an insights repository, researchers can quickly and easily access past projects and findings, which are valuable for identifying trends and patterns over time. This empowers researchers to build a more comprehensive (and shareable) understanding of their customers, markets, and other key stakeholders, and can inform the design and execution of future research projects to maximize their value to larger corporate initiatives.
- Improved organization and collaboration. An insights repository also helps to improve the organization and collaboration within a UX, CX, or market research team. By providing a centralized platform for storing and accessing research and insights, team members can more easily collaborate and share their findings with one another. This ensures that all team members are working from the same set of information, and can also help to prevent duplication of effort and reduce the risk of mistakes.
- Enhanced sharing and dissemination of findings. An insights repository can also make it easier for UX, CX, and market research teams to share their findings with other departments or teams across their organization. Because all insights are stored in one single database, it’s easy to connect projects across programs or research initiatives that help to color in details about the same larger trend.
It should be obvious why high-turnover and in-flux teams create unique challenges for insights storytelling. We’ve covered this already. But then how can this problem be realistically solved, and in a future-proof manner that accounts for not just our present high-turnover environment, but also up-and-coming trends (like generative AI) that will undoubtedly impact the insight space?
The answer is technology. Yes, the management of insights teams will shift in response to changing labor force conditions. That goes without saying. But without a strong plan for implementing technology that, too, accounts for these developments, insights teams will forever play catch-up, always one step behind where they need to be.
Insights Repositories: Technology for Story-based Insights
When it comes to insights technology applications (rest-tech or in-tech), there have traditionally been two highest-level categories of applications:
- Data Gathering: These applications empower insights teams to gather data from of-interest populations (customers, target market consumers, etc.). These include survey platforms, community engagement platforms, tools for recording interviews and user behavior, and other observational tools designed to equip insights researchers with firsthand knowledge of their target populations.
- Data Analysis: These applications make it possible for insights teams to interpret and analyze the data they harvest. They include an AI-powered NLP to
For the past few decades, this has been the primary framework for thinking, at the highest level, about insights technology. But over the past few years, a new need has arisen and been met by insights-focused development teams in the form of insights repositories.
An insights repository is a built-for-insights “second brain” platform. It empowers researchers to organize, explore, search and discover all their research data—past and present—in one organized place.
Insights repositories sit squarely between data gathering and data analysis applications, filling a gap that has only widened as the volume of data being gathered and stored by insights teams around the world has reached a critical mass — a threshold, that is, whereby a whole new set of insights can be discovered simply by parsing, indexing, and analyzing data that already exists.
In this way, insights repositories aid research in the process of continuous discovery and story-building. More often than not, stakeholders and researchers complain that they have little visibility into the kinds of research that have been conducted or historical data, and reports aren’t available to make sense of or even compare to. An insights repository solves that problem by enabling organization-wide access to insights project data, no matter the scale or types of research — qualitative, quantitative, 1-1 interviews/customer research, or even behavioral research from existing data.
Think of an insights repository as a “second brain” for insights teams, business stakeholders and clients, and decision-makers where there is a way to retrieve and summarize past studies, build upon existing insights, see the progression of cross-project knowledge graphs, and most importantly, eliminate research duplication and minimize the time and cost of future research.
An effective insights repository ensures the intelligent indexing of your existing tech stack of research, collaboration, and communication tools. The best of these applications allow for workflow management, vendor API access, real-time status and notifications, and an AI-driven tool for churning out smart insights in a scalable manner.
The insights repository consists of three fundamental levels of data:
- Insights: At a holistic level, the insights desk consists of tagged, indexed, and unified insights. This is from past and existing studies of different research types, including qualitative and quantitative studies, user research, custom studies, advanced research modeling studies, and more. All of these insights are easily searchable with the use of business taxonomy and meta-tags. These insights also monitor cost spends, ROI of studies, and other factors that provide an insight into time and resource spends.
- Observations and nugget-ed information: The secondary level of the insights hub aims to provide information at an even more granular level of studies a certain team or product conducts, insights from longitudinal tracking studies, product enhancements, marketing messaging, or a campaign that emanated from a given initiative. This level also stores presentations and outcomes, so that tribal knowledge from siloed studies is available for all to see.
- Raw research data: The final component of this repository is the actual data, including customer calls, vendor research data, questionnaires, business taxonomy tagged studies, qualitative and quantitative data, IDI’s, customer behavioral data, and more. All of this is unfiltered data that can be looked upon and leveraged as and when required.
All in all, an insights repository is a second-brain tool that empowers insights researchers with democratized and in-context research project data. And it makes possible the existence of story-based insights across time and teams. This is because, by storing not just project meta-data and raw data files, but hosting projects in context (that is, displaying how projects connect to larger themes and to other projects in the repository), stories exist by default. Research projects don’t live in silos, nor is any dataset divorced from the tools used to create and analyze them. The full lifecycle of research projects is stored in an insights repository, accessible to all insights (and other departments) team members across an organization.
In this way, insights teams can begin storing insights as stories, thereby coloring their deliverables with the context needed for anyone, anywhere to understand how a dataset or deliverable contributes to the larger story that is a brand’s historical, continuous, and ongoing relationship with customers.
The best insights are not delivered in a vacuum. They are presented in the context of where they add the most value. Likewise, insights should not be stored in a way that is meaningless to everyone except those who, in their minds, understand the significance of the intangible and unrecorded trends and narratives therein.
Insights repositories are the solution to this problem. All insights belong to a story. And while narrating every possible story is inefficient (and probably impossible), a smart built-for-insights repository can make it possible for these stories to emerge and evolve across teams and eras.