There's a paradox happening in the workplace right now where we have more data than ever, yet somehow, decisions feel more complex, not simpler.

This challenge was at the heart of our conversation with Beth McGrath, Senior Director of Product Marketing at Lyft. She leads marketing for a company that sits at the intersection of real people, real money, and real time, where riders and drivers make decisions every minute based on what's happening in their lives and their local economy.

On May 12, Beth joined SurveyMonkey's Katie Miserany, Chief Communications Officer and Head of Marketing of SurveyMonkey, to discuss how to make decisions when both your data and your customers are constantly shifting.

Watch the full session here.

Here are five lessons on how to stay customer-obsessed in the age of AI.

1. Curation is power when it comes to AI

McGrath shared a quote that stuck with her: "In a world of abundance, curation is actually the power."

With AI pumping out insights, analyses, and recommendations constantly, the real skill isn't generating more, it's deciding what matters.

At Lyft, they're not looking for the algorithm to tell them what to do. They're looking at what the algorithm surfaces, then applying judgment and experience to decide how to act on the data.

"We're using our own judgment as to whether or not what you're getting back is actually what you believe is right," she said. "And we're making sure that we have the right operational systems and processes to get that data on a regular cadence, and creating moments for synthesis."

Takeaway: Don't ask AI to make decisions for you. Instead make sure you have a team of people who can use their expertise to curate the outputs and make decisions more confidently. That's where your competitive advantage sits. 

2. AI amplifies whoever's using it

There's anxiety about AI replacing human judgment. But McGrath thinks about it differently.

"AI is very malleable," she said. "What you feed it really can determine the direction that it can go."

At Lyft, they've noticed something interesting: their most seasoned marketers use AI to work through complex strategic questions. They feed it context, assumptions, and spreadsheets. The output is sophisticated strategic thinking at speed.

On the other end of the spectrum, she’s noticed the effect for people early on in their career. AI is giving these people the ability to actually shorten their learning curve and use it as an intern.

"AI is in the hands of its operator," McGrath explained. "The greater your lived experience within the industry, the better your AI prompts, the better your results."

Takeaway: Use AI to supercharge your team's skill set at every role level. Encourage team members to share their prompts, tips, and best practices. This means investing in people matters just as much as investing in tools.

3. Keep "focusing facts" in front of your team

Here's a tactic you can steal from Lyft that is key to helping their team cut through endless data. 

Every week, McGrath sends her team what she calls "focusing facts"—a digest of the company's critical KPIs for the week, but with human context woven in.

A quick example: If there is a big weather event, she doesn't just share that driver availability dipped. She shares that drivers stayed home because of safety concerns, but for some drivers, that means they lose supplemental income they depend on. A driver who uses Lyft to make up income on the side just lost a paycheck.

This additional context is a huge factor in the team’s strategy and decision making. Understanding what drives customer loyalty goes beyond product-usage stats and analytics. 

Takeaway: The teams that stay customer-obsessed aren't the ones drowning in dashboards. They're the ones who translate data into continuously providing value to their customers and user base. Create a practice of regularly gathering customer insights to inform your strategy.

4. Dig deeper to uncover what your data is hiding

Sometimes the obvious insight is the wrong insight.

Miserany shared a concrete example: the team made a change to their homepage. When they looked at it holistically, the impact appeared flat with no significant gain or loss.

But when they dug deeper into traffic performance by channel, they saw something worth investigating. Their top-converting channel (organic search) actually dipped when they made the change. A closer look revealed several paid channels had new activations go live at the same time, which masked the decline at the aggregate level.

They almost missed it.

"It's the depth of expertise of the people looking at that data," McGrath said. "The specificity with which you can really dig in and understand the trends that are happening. That can be so important."

Staying close to the data and questioning assumptions is what separates decisions made with confidence from decisions made with luck.

Takeaway: Connect your data streams to allow you and your team to gather deeper insights that surface patterns, trends, and gaps in performance, faster. 

5. Real human judgement still can't be automated

Here's the thing that gives McGrath confidence her job isn't going away: "I'm excited about AI helping with the mechanics," she said, "but the hard work of sense-making and using feedback to drive improvement—that's still going to be human mediated."

AI can speed up analysis, flag patterns and generate hypotheses. But it can't read a weather forecast and understand that drivers need to make up income somewhere else. It can't see that seniors in your community have lower conversion rates and realize they might need a different product experience. It can't be empathetic.

When Lyft launched Silver (a product for older riders), it came from noticing that customers over 55 weren't converting at the same rate as other cohorts. They asked why. They built something that actually worked for that group and now almost a fifth of Lyft's riders are over 55 and reporting that the product has restored their independence.

You can't get there with data alone. You need people who care about the answer.

Takeaway: The companies that actually move the needle are the ones that refuse to choose between moving fast and staying curious. They use AI to handle the mechanics so people can focus on the judgment calls to drive innovation and build products users actually need.

Put this into practice

Lyft's advantage isn't that they have better data than competitors, it's that they've built a culture where that data stays connected to the real people using their platform everyday. 

If you're managing a team in a fast-moving space, start with McGrath's framework: customer obsession first, speed second, AI as the amplifier, not the decision maker.

Because the best marketing decision in the world still comes from one place: listening to your customers and understanding what real people actually need.

Learn how SurveyMonkey can help you make more confident decisions today. 

Want to watch the full conversation between Lyft and SurveyMonkey? Check it out at CuriosityCon.