“Talk to your users!”
Seems simple enough. But anyone who’s tried knows it’s rarely that straightforward. Truly understanding your customers is a complex endeavor, yet crucial for building products they’ll love.
But the struggle to find the right participants is real. So is the pain of low survey response rates from participants.
Why does the process of actually talking to your customers remain so hard, painful, and manual?
It’s this very challenge that led Oren Friedman to build Rally — a research operations platform — with Alec Robins. When Marvin’s co-founder and CEO Prayag Narula chatted with Oren, he knew he had to discuss the transformative role of Research Ops and its future in user research.
Watch the entire conversation on unlocking the potential of research ops. Or read ahead if you want to go through the key insights now and dive deep later.
Laying the Groundwork
Oren described research ops as the “infrastructure layer” of the research process, responsible for building the systems and processes that enable effective user research at scale.
When we translate Maslow’s hierarchy of needs for research teams, recruiting participants is at the base of it. Why? Oren said, “Because no participants, no research. And even worse than no participants are bad participants.”
Speaking to users who don’t fit your target persona can result in flawed insights and misguided product decisions. To build a product that truly resonates with your audience, you need to understand their needs, and that starts with talking to the right people.
And that’s where research operations come into play. They provide the essential groundwork, ensuring researchers connect with the right participants to build a solid foundation for user insights.
“There will never be enough researchers for the amount of research that needs to get done. So inevitably, an organization needs to start thinking about democratization,” Oren explained.
Traditionally, user research is a responsibility that rests with dedicated research teams. However, more companies are adopting “democratized research,” where everyone in an organization can gather insights directly from their users.
This shift brings new challenges.
Why Research Ops Matters
Imagine a product manager or a designer trying to conduct a quick user interview to understand customer needs better.
Before they talk to their users, they have to jump through multiple tasks:
- Find the right participants for the interview
- Make sure their questions are unbiased
- Schedule interviews
- Manage incentives
- Ensure data privacy (the most important step)
For a person without a research background, the entire process is intimidating and often falls apart without the right support. That’s where research ops comes in to build systems that streamline user research, making it accessible to everyone in the organization.
Oren explained why a company cannot give unfettered access to just anybody:
“This is not the same thing as going to an external panel and finding a couple of people to do research with who have no connection to your organization. These interactions matter. And who else will think about all of these nuances, intricacies, and little steps of the process? It’s research ops. They are the key to enabling this.”
Research ops aims to simplify research tasks and reduce manual effort for whoever is doing the research. They build panels of willing participants and create secure systems for managing data, all while ensuring compliance with regulations.
The Evolution of Research Ops
“The rise of research ops has coalesced with the rise of democratization within organizations and the expectation and reality that everyone should be able to talk to customers,” said Oren.
Research ops has evolved beyond just recruitment. The goal is to build a research-first culture where user insights drive every business decision. And when it comes to the relationship between design ops and research ops, he acknowledged three typical structures:
- Where research ops reports to the head of research
- Where research ops reports to the head of design
- Where research ops is a part of a centralized ops function.
Interestingly, he sees the most successful research ops teams as part of a centralized operations function alongside sales ops and marketing ops.
Oren explained that this structure allows research ops to:
- Understand how research fits into the company’s overall operations and business strategies
- Share resources and expertise with the rest of the company efficiently
- Improve cross-functional collaboration
- Foster stronger peer relationships that lead to better alignment with the rest of the teams.
Prayag acknowledged the logic of this approach, comparing it to “how DevOps supports sales and marketing teams.”
Oren emphasized that this structure is still relatively uncommon. Yet, it’s the most effective way to truly democratize research and drive user-centric decisions across the organization.
Like sales and marketing teams use CRMs, research teams need a dedicated research CRM to manage participant data effectively. This allows them to integrate valuable research insights into the company’s broader customer data strategy.
The Future of Research Ops: Where Does AI Fit In?
Research ops is all about streamlining and optimizing the research process. Simply put, it’s the engine that drives successful user research. And AI can take over repetitive tasks like scheduling sessions or taking notes, freeing researchers to focus on research.
AI’s Impact on Participant Recruitment
Oren highlighted the progress made in using AI for knowledge management and insights synthesis: “AI is now starting to impact earlier stages of research, such as recruitment.”
AI can help with:
- Optimizing email copies: AI can help you choose the most effective messaging for recruiting participants based on customer data, leading to higher response rates and less wasted effort.
- Automating workflows: AI can streamline the end-to-end recruitment process, reduce manual work, and make it easier for researchers to connect with the right participants.
- Bridging the gap between PMs and users: AI can simplify the process of gathering user feedback, making it more accessible to product managers and other non-researchers.
Prayag painted a future where “AI can automate more of the research process, potentially filling calendars with the right participants based on specified criteria.” He also pointed out the potential for AI to improve conversion rates by helping researchers target the right audience and craft more effective communication.
Can AI Replace Researchers? (No)
Oren shared real-world data on response rates, noting that cold outreach typically yields a 2-4% response rate, while opted-in panels can achieve 20% or even 50% response rates.
“AI can help achieve higher response rates by enabling better targeting and personalization,” Oren said.
The conversation also touched on “synthetic participants” (AI-powered simulations of real users). Oren acknowledged the potential of this technology and saw it as a valuable tool for refining research questions. However, he emphasized the importance of real human interaction. He believes in “talking to real humans, especially when designing products for human users.”
AI can be your perfect research assistant that turns raw data into customer insights in minutes —but it will never be a replacement for a human researcher.
Building a Research-Driven Culture: Key Takeaways from Q&A
Oren and Prayag received lots of great questions from the audience. Here are a few of our favorites.
How can Research Ops Break Down Silos and Demonstrate its Value With Metrics?
Start by understanding the priorities of different teams. What are their goals, and how can Research Ops help them achieve those goals? For example, if leadership wants user feedback to inform product decisions, track the percentage of features released with supporting user research.
Metrics should align with organizational goals. If the goal is speed, track the time it takes to recruit participants. If the goal is cost-effectiveness, track the cost per study. Connect these metrics to business outcomes, such as increased customer retention or revenue.
When Does a Team Need a Dedicated Research Ops Role or Platform?
Oren suggested that when you have around 10 or more people conducting research, it’s time to consider investing in a research ops tool.
Why? At this scale, challenges like governance, inconsistent communication, and inefficient workflows start to emerge. A dedicated role or platform can help streamline processes, ensure compliance, and improve efficiency.
What If My Team Is Too Small For a Dedicated Research Ops Role or Platform?
Early-stage companies can leverage relationships with other teams like sales and marketing to access users. “Be scrappy and creative in your recruitment efforts. If you’re in a highly regulated industry, prioritize data privacy and compliance even with limited resources,” Oren said.
How Can Research Ops Navigate the Legal or Compliance Hoops Safely, Especially in Industries Like Finance or Healthcare?
Start with service design. Map out the current workflow for connecting with users, including all the steps and stakeholders involved. This will help identify potential compliance issues and areas for improvement. Work closely with legal, compliance, and HR teams to ensure your research practices are compliant and ethical. Be proactive and seek their input early on.
The Bottom Line About ReOps
By building the infrastructure for efficient, ethical, and accessible research, research ops teams ensure that the voice of the customer informs every decision. It is the unsung hero of impactful user research.
Ready to supercharge your research efforts and unlock the power of user-centricity? We can help!
If you’re looking for an amazing ReOps platform, go to rallyuxr.com.
And if you’re looking for a research repository and a place to conduct research, you’re already in the right place. Request a free demo to find out how Marvin’s AI can improve your research workflows.
