Latest / The Local Marketing Podcast with Fexingo: Small Business, Google Maps, and Local SEO / How a Food Truck Uses Google Maps Insights to Find the Best Locations
Transcript
- Lucas: There's a food truck in Austin called El Fuego Rápido that starts every day by checking Google Maps search volume. Not for its own listing. For the city. Luna: Wait — checking search volume for the city? Like, how many people are searching 'tacos near me' at any given hour? Lucas: Exactly that. The owner, Maria, pulls up Google Trends for 'tacos near me' in Austin, but she also uses her Google Business Profile insights — specifically the 'search queries' report — to see which neighborhoods are generating the most queries on weekday mornings. Luna: So she's literally following the demand in real time. That's a different kind of market research. Lucas: It is. She mapped out five possible parking spots across the city — downtown, near the university, a business park in the north, a residential area in the south, and a shopping plaza. Every morning at 6 AM, she checks which zone has the highest spike in 'tacos' or 'food truck' searches within a 1.5-mile radius. Luna: One point five miles — is that the radius Google uses for local pack results? Lucas: That's the general rule of thumb, yes. Google's local algorithm heavily weights distance, so if you're within a mile and a half of a searcher, you're more likely to appear in that three-pack. So Maria goes where the searchers already are. Luna: Okay, but does she just go on search volume alone? I'd think you'd also want to know if those searchers actually convert into visits. Lucas: She cross-references two things. First, her own profile's 'direction requests' — that's people asking Google Maps for directions to her truck. Second, 'phone calls' — generated by her Google Business Profile listing. She tracks those by location over the past week. Luna: So she spots a neighborhood with high search volume and also checks if that area has historically delivered actual direction requests or calls. Lucas: Right. And here's the concrete number: within three months of doing this, she doubled her daily revenue. From about $400 a day to $800. No ads. No paid promotions. Just showing up where the demand was highest. Luna: That's impressive. But I have to ask — does this only work for mobile businesses like food trucks? Can a brick and mortar coffee shop use the same data? Lucas: They can, but the application is different. A fixed-location business can't move, but they can still optimize their Google Business Profile based on what the search query data tells them. For example, if a coffee shop sees a high volume of 'cold brew near me' queries in the summer, they can update their profile to feature cold brew photos and add 'cold brew' to their description. Luna: So it's more about content optimization for a stationary business, versus physical relocation for a food truck. Lucas: Exactly. But there's another layer. Maria also looks at 'photo views' — how often people view photos on her Google Business Profile compared to competitors in the same area. She noticed that when she parks near the university, her photo views are 30% higher than when she's at the shopping plaza. Luna: Because students are more likely to browse photos before deciding where to eat? Lucas: That's her theory. So she started posting more photos on her profile — especially of the food with clear, bright lighting — and she uploads at least three new photos every week. That alone boosted her profile's engagement metrics, which Google seems to reward with higher ranking in the local pack. Luna: I want to go back to the data source. Is this all available in the standard Google Business Profile dashboard? Or do you need something like Google Trends on the side? Lucas: She uses both. The profile dashboard gives you 'search queries' — the actual phrases people typed — and 'direction requests', 'calls', 'photo views'. But Google Trends helps her spot city-wide patterns she might miss. For instance, she noticed 'breakfast tacos' searches spike at 7 AM downtown but at 8 AM near the business park. Luna: So she adjusts her schedule based on that. That's remarkably granular. Lucas: It is. And the best part — this is completely free. No ad spend, no third-party tool. Just the data Google already gives you. Luna: I'm curious about one potential flaw: what if the search volume is high but so is competition? Like, if she sees 'tacos near me' spiking downtown, but there are ten other taco trucks there — wouldn't that dilute her chances? Lucas: Great question. She actually uses a competitive metric for that: she checks the number of Google Business Profiles in that area that use 'taco' in their name or description. If it's more than five, she skips that spot. She learned that when there are too many similar listings, Google's local pack tends to show only a few, and her click-through rate drops. Luna: So she's factoring in supply and demand. Smart. Lucas: And she's got a backup plan. If her top two spots are oversaturated, she goes to her third choice — the residential area in the south. There are only two other food trucks there, but the search volume is 20% lower. Still, she consistently gets direction requests because the competition is minimal. Luna: Let's talk about the photo views metric a bit more. She saw 30% higher photo views near the university. Did she test that deliberately? Lucas: She did. She spent two weeks at the university, then two weeks at the shopping plaza. At the university, photo views per day averaged 150. At the shopping plaza, about 110. She also noticed that on days she posted a new photo, direction requests would increase by about 15% the next day. Luna: That's a clear causal link. Post a photo, get more directions. Lucas: Exactly. So now she posts a photo at 7 AM every day — of the breakfast taco special — and she sees a consistent bump in engagement. It's like a daily signal to Google that her profile is active. Luna: And that activity helps her ranking, especially in a competitive market like Austin. I bet a lot of food truck owners don't realize how much data they're sitting on. Lucas: You know, a handful of listeners chip in monthly through buy me a coffee dot com slash fexingo, and that's literally what funds making episodes like this one — where we can dig into a specific tactic like Maria's photo-posting strategy. It's listener supported, no ads, and that small group already keeps it going. Luna: Yeah, and it means we can keep diving into real examples rather than generic advice. Appreciate everyone who does that. Lucas: So back to Maria — she also uses the 'calls' metric to decide whether to adjust her menu. At the business park location, she noticed call volume spiking around 11 AM, and most calls were asking about catering. Luna: So she started offering a catering option specifically for that area? Lucas: Exactly. She added 'corporate catering available' to her Google Business Profile description, and within a week, she booked four catering orders from that same business park. The calls had been coming in anyway; she just made it easier to convert them. Luna: So she's using the call data to identify unmet demand and then adjusting her offering. That's a full feedback loop. Lucas: It is. And it cost her nothing except a few minutes editing her profile. No new website, no ad campaign. Luna: I want to ask about the 'direction requests' metric specifically. Is that a reliable indicator of actual foot traffic? Lucas: It's not perfect, but it's close. Google counts a direction request when someone taps 'directions' on your listing. Not everyone who requests directions actually shows up, but Maria tracked her own sales and found that on days with 20 direction requests, she'd see about 12 to 15 customers. So roughly a 60% conversion from request to visit. Lucas: Roughly. It varies by industry, but it's a good baseline. Maria's numbers are for a food truck with relatively cheap items — tacos — so high conversion. For a high-end restaurant, conversion might be lower because people are more price sensitive. Luna: Right. So the data is directional, not absolute. But still incredibly actionable. Lucas: One more thing she does: she looks at 'photo views' for competitors. Her Google Business Profile allows her to see 'how your photos compare to others' — a chart that shows average photo views per day for similar businesses in her area. Luna: I didn't know that was available. Is that in the 'insights' tab? Lucas: Yes, under the 'photo views' section, there's a benchmark comparison. She saw that her photo views were below average when she first started. That motivated her to post more frequently. Within a month, her photo views went from below average to above average, and she noticed a corresponding increase in direction requests. Luna: So there's a direct correlation between photo engagement and visit intent. That's a powerful insight for any local business. Lucas: Absolutely. And it's all free data. You just have to look at it. Luna: I think the takeaway is: your Google Business Profile is not a static listing. It's a live data stream that tells you where demand is, what people want, and how they find you. Lucas: And Maria proves you can act on that data without a big budget. She's a one-person operation, and she's competing with trucks that spend thousands on Instagram ads. Luna: So for a small business owner listening: start checking your insights every day. Look at search queries, direction requests, photo views. See if there's a pattern you can act on. Lucas: And if you're a fixed location, you can still use the competitive photo benchmark. If your photo views are below average, post more photos. It's that simple. Luna: Alright, next time I want to dig into how Google's local algorithm weighs these metrics differently. But that's for another episode. Lucas: Agreed. For now, go check your insights.