Customer Research Trends: What's Changing in 2026
The customer research landscape is evolving faster than ever. From AI adoption to the democratization of research, here are the eight trends shaping how product teams understand their customers in 2026.
Koji Team
Customer Research Trends: What's Changing in 2026
The way product teams understand their customers is undergoing a fundamental shift. Gone are the days when customer research was a bottleneck that slowed down product development. In 2026, the teams that listen to customers fastest are the ones that win.
Based on data from 800+ product professionals and insights from research leaders at companies like Adobe, Cisco, Broadcom, and GoodRX, we have identified eight trends that are reshaping the customer research landscape. Whether you are a seasoned researcher or a product manager just getting started with customer conversations, these trends will help you understand where the industry is headed and how to stay ahead.
The State of Customer Research in 2026
Before diving into the trends, let us look at the current landscape. Customer research is no longer a nice-to-have; it is a competitive necessity.
62% of product professionals report that demand for customer research has increased over the past year. This surge is driven by three factors: a growing appreciation for customer insights, the need for innovation in competitive markets, and a decisive shift toward data-driven decision-making.
The business case is clear: organizations that embed research into their strategy and operations report 2.7x better outcomes compared to those that rarely incorporate customer insights. They see enhanced brand perception (5x better) and more active users (3.6x higher).
With those stakes, it is no surprise that customer research is evolving rapidly. Here are the eight trends driving that evolution.
Trend 1: Customer Insights Are Driving Business Growth
Customer research has moved from a tactical function to a strategic driver of business success. Organizations are no longer asking "Should we do research?" but "How can we do more research, faster?"
The Impact Numbers
When customer research is embedded into product development and decision-making, the results speak for themselves:
- 83% report improved product usability
- 63% see higher customer satisfaction
- 35% achieve better product-market fit
- 34% experience increased customer retention
87% of organizations now leverage customer research to inform critical decisions. This is not just about building better features; it is about building the right products for the right customers.
What This Means for Your Team
The teams that treat customer research as a strategic investment, not a cost center, are pulling ahead. If you are still fighting for budget or buy-in, these numbers are your ammunition. Customer research is not slowing you down; it is helping you build products that customers actually want.
Trend 2: AI Adoption Is Accelerating
The biggest shift in customer research is the widespread adoption of AI tools. What was experimental in 2024 is now mainstream in 2026.
The Numbers Tell the Story
- 58% of product teams now use AI in their research workflows
- This represents a 32% increase from 2024 (when 44% used AI)
- 37% use AI in some research projects
- 21% use AI in most of their studies
AI is not replacing researchers; it is amplifying them. The most common use cases focus on eliminating manual work so teams can focus on strategic thinking.
How Teams Are Using AI
Product teams are leveraging AI to automate the most time-intensive components of research:
| Use Case | Adoption Rate | |----------|---------------| | Analyzing research data | 74% | | Transcription | 58% | | Generating research questions | Growing | | Running automated interviews | Emerging |
The result? Teams report:
- 58% improved efficiency
- 57% faster turnaround times
- 49% optimized workflows
The Human-AI Balance
While AI adoption is accelerating, teams remain thoughtful about implementation. The most effective approach combines AI automation with human oversight. AI handles the heavy lifting of data collection and initial analysis, while researchers focus on interpretation, strategy, and stakeholder communication.
As Daniel Soranzo, Lead UX Researcher at GoodRX, puts it: "I'm excited to see how AI could help with tasks like prototyping or running interviews, and how our roles will evolve alongside AI. I'd like to think that because of AI we're moving into more strategic roles beyond usability testing, which allow us to focus on higher visibility, higher-impact business decisions."
Trend 3: Automating Manual Research Tasks
The number one use case for AI in customer research is not fancy analysis; it is eliminating the grunt work that has always slowed teams down.
Where Time Gets Lost
Research has always been bottlenecked by manual tasks: scheduling interviews, transcribing conversations, organizing notes, and synthesizing findings. These tasks are essential but do not require deep expertise. They are perfect candidates for automation.
The Automation Priority List
Teams are automating in order of impact:
- Data analysis (74%): AI tools can identify patterns and themes across hundreds of interviews in minutes, not days
- Transcription (58%): Real-time transcription with speaker identification eliminates hours of post-interview work
- Insight synthesis: Automated summaries and highlight reels make sharing findings faster
- Participant recruitment: AI-powered screening and scheduling reduces coordination overhead
The Time Dividend
When you eliminate manual work, you create space for what matters: actually talking to more customers and thinking deeply about what you learn. Teams using AI report they can conduct significantly more research without adding headcount.
Trend 4: The Researcher Role Is Evolving
As AI handles more tactical work, the role of the customer researcher is transforming from technical executor to strategic educator.
From Doing to Enabling
Historically, researchers were the gatekeepers of customer insight. They designed studies, conducted interviews, and delivered findings. But as demand for research grows and AI tools become more accessible, the most effective researchers are becoming enablers who help entire organizations understand customers.
The Educator Mindset
Today's research leaders are focused on:
- Training teams to conduct quality research independently
- Building frameworks that ensure consistent, reliable insights
- Setting standards for ethical, unbiased research practices
- Connecting insights to business strategy and decisions
This shift does not diminish the researcher role; it elevates it. Researchers become strategic partners who shape how organizations understand and serve customers.
What This Means for Product Teams
If you do not have a dedicated researcher on your team, this trend is good news. AI tools and democratized research practices make it possible for product managers, designers, and founders to gather meaningful customer insights directly. The key is having the right tools and frameworks to maintain quality.
Trend 5: Research Is Becoming a Team Sport
Customer research is no longer a solo activity. The most effective organizations are making it a collective effort across product, design, engineering, and go-to-market teams.
Who Is Conducting Research?
The data shows research is happening across roles:
- Product designers: 61% conduct research at their organizations
- Product managers: 38% are actively involved in research
- Marketers: 17% are gathering customer insights
This distribution reflects a healthy trend: customer understanding is becoming everyone's responsibility, not just the research team's domain.
The Benefits of Democratization
Teams that embrace democratized research see significant benefits:
- 2x more likely to report that research influences strategic decisions
- 1.8x more likely to see research impact product decisions
- 1.5x more likely to discover new product opportunities
When more people talk to customers directly, empathy becomes embedded in the organization's DNA. Decisions are made with customer context, not assumptions.
Maintaining Quality at Scale
The challenge with democratized research is maintaining quality. Without proper training and tools, well-intentioned team members can introduce bias or miss important insights. The solution is a combination of:
- Clear research guidelines and templates
- AI-powered tools that guide non-researchers through best practices
- Researcher oversight for high-stakes studies
- Centralized repositories for sharing and building on insights
Trend 6: Customer Interviews and Usability Testing Lead
Despite all the new tools and methods available, the fundamentals remain the same: direct conversations with customers provide the richest insights.
The Most Popular Methods
The top research methods have remained consistent:
| Method | Adoption Rate | |--------|---------------| | Customer interviews | 86% | | Usability testing | 84% | | Surveys | 77% |
These methods work because they create space for customers to share their experiences, challenges, and needs in their own words. No amount of analytics data can replace the insight you get from hearing a customer explain their problem.
The AI Enhancement Layer
While the methods remain the same, AI is changing how teams execute them:
- Interviews: AI moderators can conduct preliminary conversations, enabling teams to interview 10x more customers
- Usability testing: AI analysis can identify patterns across sessions automatically
- Surveys: AI helps write better questions and analyze open-ended responses at scale
The combination of proven methods with AI-powered execution is the sweet spot for 2026.
Trend 7: Time and Bandwidth Remain the Top Challenges
Despite all the progress, product teams still face significant constraints. The number one challenge is the same as it has always been: there is not enough time.
The Challenge Landscape
| Challenge | Teams Affected | |-----------|----------------| | Time and bandwidth constraints | 63% | | Recruiting the right participants | 48% | | Recruiting participants in time | 39% |
Product teams are under constant pressure to move quickly. Research, no matter how valuable, competes with an endless list of other priorities.
How Teams Are Responding
To address the growing appetite for customer insights while managing constraints, 75% of teams plan to scale research through:
- Increasing research studies (51%): Simply doing more research, often by involving more team members
- Leveraging AI tools (31%): Using automation to make existing research more efficient
- Training for democratization (30%): Enabling non-researchers to conduct quality research
The teams that solve the time problem will have a significant competitive advantage. AI-powered tools that reduce the time from question to insight, from weeks to hours, are becoming essential infrastructure.
Trend 8: Research Is Driving Strategic Decisions
Customer research is earning a seat at the strategy table. It is no longer just about optimizing existing products; it is about shaping the direction of the entire business.
The Strategic Integration
The data shows research is being applied at multiple levels:
- 42% use research primarily for product decisions
- 37% integrate research into both product and business strategy
Companies that use research for business strategy, not just product decisions, report 2.7x better outcomes.
From Insights to Impact
The most mature research organizations are connecting customer insights to:
- What to build (product roadmap prioritization)
- Who to target (market segmentation and positioning)
- How to win (competitive differentiation)
This strategic application of research requires moving beyond individual studies to building a continuous flow of customer insight that informs decision-making at every level.
What These Trends Mean for Your Team
The customer research landscape in 2026 is defined by two major forces: AI acceleration and democratization. Together, they are making it possible for every team to understand their customers deeply, regardless of whether they have dedicated research resources.
Action Items for 2026
Based on these trends, here are the priorities for product teams:
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Embrace AI tools thoughtfully: Start with automation of manual tasks (transcription, analysis) before exploring AI-moderated interviews. Maintain human oversight for quality.
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Democratize with guardrails: Enable your entire team to conduct research, but provide training, templates, and tools that ensure consistent quality.
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Connect research to strategy: Move beyond ad-hoc studies to build a continuous research practice that informs product and business decisions.
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Invest in infrastructure: A research repository, shared frameworks, and AI-powered tools are now essential infrastructure, not nice-to-haves.
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Measure and communicate impact: Track how research influences decisions and outcomes. The teams that can demonstrate ROI will get more resources.
The Future Is Customer-Led
The trends are clear: the teams that understand their customers best will build the products that win. What is changing is how accessible that understanding has become.
AI is eliminating the busywork that made research slow. Democratization is spreading customer empathy across organizations. And the business case for research has never been stronger.
The question is no longer whether you can afford to do customer research. It is whether you can afford not to.
How Koji Fits Into These Trends
At Koji, we have built our AI interviewer specifically to address these trends. We believe every team should be able to conduct meaningful customer conversations at scale, going from questions to insights in hours, not weeks.
Our platform enables:
- AI-powered interviews that feel natural and conversational
- Automatic analysis that surfaces themes and insights across all your conversations
- Democratized access so product managers, designers, and founders can run research independently
- Time savings that let you talk to 10x more customers without adding headcount
The future of customer research is not about choosing between speed and depth. It is about having both.
This article draws on industry research including data from 800+ product professionals across enterprise, emerging, and SMB organizations. The insights reflect the current state of customer research practices as of early 2026.