In his now iconic 1997 letter to shareholders, Jeff Bezos wrote:

“We want to share with you our fundamental management and decision-making approach so that you, our shareholders, may confirm that it is consistent with your investment philosophy: We will continue to focus relentlessly on our customers.”

And so began entrepreneurs’ and venture capitalists’ obsession with customer obsession.

Companies began to orient their decision-making processes around working backward from customer needs. Teams increasingly relied on data-driven, customer-centered decision-making, and employees were given ownership to identify and solve real customer problems. Specifically for UX Research teams, customer obsession was evident in the hiring trends for research roles, which steadily grew YOY between 2010-2022 until the COVID-19 pandemic hit.

But if we shine the spotlight on UXR teams, a question comes up: how customer-obsessed have research teams actually been?

The metrics of customer obsession

One way to answer this is through the lens of input and output metrics.

Output metrics are the more common way to think of customer obsession. There are industry standard baselines that enable teams to compare their results with others. For example, companies may track:

• Customer Satisfaction (CSAT) and measure how happy their customers are with their product.

• Net Promoter Score (NPS), tracking customer loyalty and willingness to recommend the company to others.

• Customer Retention Rate (CRR) the percentage of customers who continue to do business with a company over a specific period

A company should expect that the more customer-obsessed it is, the better its output metrics will look. However, several industries, including healthcare, finance, government services, retail, and telecom companies, have typically struggled to attain strong positive output metric scores.

Some would claim that the nature of these businesses imposes limitations on customer satisfaction, but most would also acknowledge that a lack of customer obsession and the lack of tools to be customer-obsessed are also major hindrances to the success of these industries.

To be fair, we’ve yet to meet a founder, leadership team, or venture capitalist who wouldn’t want to be more customer-obsessed and improve their company's performance across any sector.

This brings us to the second type of metrics: Input metrics. What does it look like to be customer-obsessed? These metrics are trickier because there are no industry standards for what applied customer obsession looks like. Companies could track metrics like:

• Weekly or monthly # of customers interviewed

• Research coverage across geos or key segments

• Strength of research connections with customers, i.e., follow-ups, longitudinal insights, time between research sessions, etc.

Again, though the notion of customer obsession has existed for close to three decades, few, if any, frameworks clarify what it looks like for a research team on the ground.

The vision of customer obsession

Allow us to pose the question to you. If we envision a hypothetical customer-obsessed UXR team, who have no resource limitations at all, what would that look like in practice?

Here are a few thoughts on what such a team might do:

1. Researchers might choose to engage with any customer who wishes to provide feedback because of a sub-optimal (or excellent) experience they had.

2. Research would follow up with customers, for example if they interviewed someone before a product launched, they would also interview the same person afterwards and ascertain whether the product truly met their needs. Or, if a customer gave a poor satisfaction score, a researcher could immediately follow up and understand why.

3. Researchers would interview customers from all over the world across key segments and do so in the participants' native language at a convenient time.

4. Research teams would observe real-time trends in log data and immediately deploy researchers to investigate the phenomena they notice.

5. Researchers would simultaneously test any number of concepts necessary to ascertain the precise nuances influencing customer adoption, satisfaction, and retention and, therefore, the ideal concept to launch.

But if you’re currently on a UX Research team, you know all too well this is not the reality you exist in, not even close. And the situation has only gotten worse since the pandemic and economic shifts. UXR teams are leaner, and researchers are working harder than ever to simply connect with customers, not to mention obsess over them.

Thus, it’s clear that in the first era of customer obsession, we have been constrained by our ability to reach our customers relentlessly and understand their lived experiences to the depth we strive for at the speed we wish.

The (AI-powered) second era of customer obsession

The advent of AI-based research tools is catapulting us into a new, second era of customer obsession.

With Genway AI and the power of AI-led research, the hypothetical scenario listed above becomes a reality. Our platform removes constraints imposed on research teams, enabling UX Research leaders and individual contributors to extend their work and glean insights at unprecedented scale and speed.

As we mentioned in a previous article, we’ve talked about “customer obsession” for decades but couldn’t truly support it because of tooling limitations. Customers expect our best, and the most successful companies in the world provide best-in-class experiences by deeply understanding what customers mean by that.

This is why Amazon has always had customer obsession as one of its leadership principles:

“Customer Obsession: Leaders start with the customer and work backwards. They work vigorously to earn and keep customer trust. Although leaders pay attention to competitors, they obsess over customers.”

At Genway AI , we’re dedicated to supporting teams transitioning to the second era of customer obsession. An era in which AI tools enable companies to be more connected with their customers than ever before. Genway AI's end-to-end user interviewing solution leverages the latest AI technology to conduct user research autonomously, augmenting research by Insight Generating Functions with actionable insights on broad, diverse populations in real time. We offer a solution that benefits any company that strives to be customer-obsessed.

If you’d like to learn more about what we’re up to at Genway, check out our website at www.genway.ai. We’re working hard to leverage AI in ways that benefit our society and help us build technology inclusively.

We’re always looking for feedback; If you’d like to try Genway, reach out at natan@genway.ai or DM me on LinkedIn.