Meet GetWhys: Because Instant Customer Research is a Superpower

A decade doing research in tech

My cofounder Tyler and I started doing market research for tech’s biggest names in 2015. We helped high-performing B2B Product, Marketing, and Sales teams beat their revenue targets and the competition, by shaping their regular workflows with insights.

How? And what does ‘regular workflows’ even mean?

Tyler and I talked to so. many. people. We’d do (anonymous) interviews with competitor ex-sellers and build battlecards for sales teams; we’d run focus groups with CISOs to build buyer personas for cybersecurity marketers; we’d do pricing analyses to help product teams prioritize their roadmaps.

Whether we were working with the leadership team of a midmarket company (e.g., Smartsheet, Dashlane, OneLogin), or with a narrower team inside larger enterprises (e.g., AWS, Microsoft, Google), our goal was always the same: help our clients truly understand their customers.

Customer-centricity matters. If you’re in a customer-focused role, applying a deep understanding of your customer’s firsthand experiences makes everything you do more effective.

• If you know the words they use (and why), you can write more compelling messaging.
• If you understand their workflow, you can build more compelling products.
• If you know where their competition fails, you can close more deals.

We became experts at interpreting what customers said, and infusing that understanding into our clients’ workflows.

Traditional approaches to customer research are limiting

Objectively, our work was really impactful. Our research helped create entire business units for our customers—and eviscerate competitors. It was also slow and expensive, invariably in the 10s or 100s of thousands of dollars for an individual project.

Most frustratingly, we always felt like we were leaving value on the table.

Interview notes got lost in Google Drive, the research report was only read by product marketing. Product research wouldn’t make it over to marketing; and vice versa. (Fun fact: Tyler and I once did a competitive intelligence project for a large accounting software firm that we delivered the week our customer acquired that competitor!)

This happened so frequently that we’d notice patterns. At some point in their life cycle, every enterprise research team creates a ‘central research database’, and works to get their stakeholders to engage directly with it. Despite their best intentions, these would invariably fail, because even when stakeholders can find old materials, sifting through errata and repurposing relevant pieces was always challenging. Organizing and analyzing isn’t easy—which is a shame, because those past investments yielded a lot of useful information!

Invariably, it was easier to start a new research project.

tl;dr: In my experience, customer research can unlock incredible value for GTM teams—but it’s expensive, slow to gather, and suffers from a short shelf life.

How LLMs are unlocking fast, custom insights.

And then LLMs showed up. LLMs are really good at analyzing large bodies of text, quickly and inexpensively.

Tyler, Viet*, and I started envisioning a better world—without kickoff meetings, or research decks that customers skim once and forget. By building LLM-powered products that abstracted away research, we could help customer-centric clients apply customer perspectives to their output without the friction of traditional research.

Now, LLMs certainly enable this vision, but they can’t accomplish it on their own. Their output is only as good as the data they can access.

We knew that combining organizations’ internal datasets with the Internet would be insufficient for client needs, because we were often hired for novel research.

We’d only be able to accomplish this enormous vision if:

1. We built an engine that captures information that’s never been documented before. We knew that the best way to get high-quality data is to have in-depth interviews with real people. So, that’s exactly what we did. We have a small army of interviewers who talk to our customers’ target markets every single day. We specifically orient our data collection machine to capture information that is relevant to our users—as our customer base grows, so does our dataset. We call it InsightDB.
2. We used that data (InsightDB) to augment our customers’ own datasets. They’re already recording every sales and success conversation (and they have no shortage of vendors promising to “unlock the value of that data”). We’d be able to merge the customer conversations they’re already having alongside the conversations they’re not invited to (in Win-Loss parlance: “deals not invited”).

Putting this together: if you’re in a customer-focused role, most parts of your output could be improved with customer insights, but you’ll never have the time or budget to apply insights to everything. By applying AI to our combination of datasets (ours+theirs+the internet), we can eliminate those barriers—and apply customer insights directly to our clients’ work.

Why customers are choosing GetWhys today and where we're going.

We rolled out an initial version to pilot customers (DocuSign, Commvault, Docker, etc.) last year—here’s what they love about GetWhys:

• Trusted primary research. Everything GetWhys products produce can be traced back to real people having real conversations.
• Rapid research. 70% of the time, our data provides an immediate answer to customer queries. When we don’t have coverage of an existing topic, our clients leverage the AnswerSLA included in their subscription. We have a >96% success rate of ingesting sufficient data on the topic (via new interviews) within five business days.
• Low, consistent cost. Our customers love our pricing—we can charge a flat fee for unlimited access because we use LLMs to analyze our proprietary dataset. An annual subscription typically equates to:
  • 15% of what our customers would have spent on expert networks, or
  • 1 traditional market research project.
• Insights as an asset. We think that every sales conversation; every past research project; every customer success call is an investment organizations make in learning about their market. Rather than gather dust on a shelf, GetWhys helps those investments accrue in value. And, because GetWhys products tailor outputs to the user (based on who they are, where they work, and what their goals are), our customers never have to make sense of a PowerPoint deck built months earlier for someone else.

We think that the future for customer-centric teams comes from applying insights directly to their workflow, instead of breaking their workflow to engage with insights.

Our pilot customers have become familiar with our investigative research tool, Compass, which abstracts away the market research process. Today, we’re launching Echo, to help clients write content that drives revenue. More workflow-centric products are on the way.

Big data (& quantitative analysis) dominated the past two decades. Now, we can analyze qualitative data at scale—instead of observing your target audience, it’s time to ask them what they’re thinking.