Most organizations have more consumer data than they realize. The problem is that it lives in dashboards, gets stripped of context before it reaches the teams that need it, and rarely connects to business outcomes in any meaningful way.
WeatherBug changed that by equipping teams across the business with the intelligence to act.
In our most recent webinar, Resonate CMO Meredith Albertson sat down with Gundeep Hora, President and General Manager of WeatherBug, and Rachel Peterson, Director of Account Management and Ad Operations, to talk through how WeatherBug built a consumer intelligence foundation that now runs across sales, brand strategy, and AI.
During the course of the conversation, Hora and Peterson shared the key challenges WeatherBug faced before their intelligence evolution and how they incorporated predictive intelligence to conquer those challenges. Let’s take a look at the journey with three key themes from the session.
The Challenge: Going from Reach to Real Audience Intelligence
WeatherBug had tens of millions of users checking their app and website constantly. But when they walked into advertiser meetings, they could only talk about reach and impressions. They knew they had the right audience for their advertisers, but they struggled to prove it. It was still difficult to answer questions like, “Do you have my customer?” or, “Are they in-market for my product?” WeatherBug had to find a way to extract deeper audience insight so they could win those conversations and win business.
With 95% of their users on the mobile app, they needed a solution that could surface audience intelligence across both app and web and surface the attributes that truly matter to advertisers. They also needed to get that intelligence into the hands of the team that was speaking directly with advertisers and closing deals. Closing that gap became the starting point for everything that followed.
Takeaway 1: Start With the Questions Your Team Can’t Answer
WeatherBug didn’t build a data strategy by asking what data they could get. They started with the questions their sales team was already hearing from advertisers.
“We started with the questions that our sales team was already getting asked and that they couldn’t answer,” Peterson explained. “And that became our requirement list. What do the advertisers want to know? We kind of worked backwards from there.”
That requirement list became a rubric for the kinds of audience insights they needed to prove value to advertisers. “We prioritized attributes that would move needles for advertisers,” says Peterson. This meant matching audiences with the traits that translate to customers. Peterson says these traits included things like “household income, in-market shopping signals, intent to travel, dog owners, lottery [players]. And these are the things that let the brand say, ‘Oh yeah, that’s my buyer.’”
But some of the most valuable questions aren’t the ones advertisers are already asking. They’re the ones nobody thought to ask yet, because the data to answer them didn’t exist. That’s where intent data changes the equation.
As Peterson put it, “The money really sits in what people are going to do in the future. Resonate asks those intent questions: how much do you intend to spend in the next three months? How much do you intend to travel? Where do you intend to go? And we have the ability with Resonate to take those intent audiences and use them as first-party data to target campaigns against.”
For brand marketers and media teams, that’s the real opportunity. Start by closing the gaps in the conversations you’re already having. Then use intent intelligence to get ahead of the questions your advertisers haven’t thought to ask yet.
Takeaway 2: Intelligence Doesn’t Belong to One Team
One of the most important decisions WeatherBug made was putting consumer intelligence directly in the hands of their sales team rather than routing it through a centralized analytics function. WeatherBug President Gundeep Hora described what happened after this shift.
“The moment you give the underlying data or platform access to the sales team, you see them take a much more entrepreneurial approach, to start clicking around, looking at which other data sets they might be useful,” Hora says. “They’re coming up with those follow-up questions on their own…a story then very organically comes together.”
But WeatherBug didn’t stop at sales. The same intelligence informed a full rebrand, the development of new product features built around weather-relevant categories like travel, and the strategic direction for AI. Peterson was direct about why: “When only one team owns the data, the value is capped. When you have sales, marketing, branding, and product all pulling from the same data foundation, the compounding effects are significant and everybody’s on the same page.”
For marketing and media leaders, this is the organizational argument for treating consumer intelligence as shared infrastructure. The ROI doesn’t come from one team using the data well. It comes from every team using it together.
Takeaway 3: Proof Before the Buy Changes the Sales Conversation
Before WeatherBug had deep audience intelligence, their sales conversations looked like those that most publishers have: reach metrics, impressions, geographic coverage. These were things that other competitors could offer, too. WeatherBug needed an intelligence differentiator.
With Resonate, the conversations shifted. “We were able to walk in [to a pitch] with: here’s what we know about our user, and here’s how we see it matching with your customer,” Peterson said. She described going to a discount footwear retailer with data showing a large segment of WeatherBug’s audience were discount shoppers.
“It shifted it from us trying to pitch them to them seeing their customer in the data. We said, ‘Hey, this is your customer base, they’re on our platform, run a campaign with us.’ And they did.”
Timing was another consequential change. “We can offer proof for the buy before the buy even happens,” Peterson noted, “which shortens the sales cycle and builds confidence in the relationship earlier.”
That shift, from post-campaign reporting to pre-campaign proof, is where predictive consumer intelligence (the individual-level understanding of why consumers act and what they’re likely to do next) produces its clearest business impact. Brands and media teams that can show a prospect their own customer in the data before a single dollar is spent are running a fundamentally different conversation than the ones still leading with reach metrics.
Ready to See What Your Audience Intelligence Can Do?
WeatherBug’s story is a useful model for any organization sitting on consumer data that hasn’t fully reached the teams that need it. If you’d like to hear more from their team, you can check out the full, on-demand webinar now. And if you want to explore how Resonate’s predictive consumer intelligence can power your own intelligence strategy, schedule time with our team today.
