ShieldGuard Pest Case Study

The Challenge

Patricia Dominguez knew the moment she saw the first palmetto bug complaint of March that her summer was about to get difficult. In Tampa Bay, pest season runs from March through October, and during those eight months, ShieldGuard Pest’s daily call volume nearly doubled. The 14-technician team that handled 50-60 jobs per day in winter suddenly needed to manage 70-100 calls daily. The jobs were there. The capacity, on paper, was there. The routing was the problem.

Every morning, Patricia printed daily job sheets from PestPac, ShieldGuard’s scheduling and CRM system. The sheets listed each technician’s jobs sorted alphabetically by customer last name. Adams in Clearwater, Baker in Brandon, Chen in Carrollwood, Delgado in Dunedin. It looked organized on paper. On the road, it was chaos.

Technician #3’s typical Tuesday during peak season told the story. His first job was a routine inspection in Clearwater, on the north end of the service area. His second was an initial treatment in St. Petersburg, 30 minutes south. Third stop: Largo, back in the middle. Fourth: Clearwater again, five minutes from where he started. By noon, he’d completed four jobs but driven nearly 90 minutes of pure windshield time between them. A geographically sequenced route would have cut that drive time in half.

The consequences of alphabetical routing compounded during peak season:

• Overtime as the default: With 7-9 jobs per day and inefficient sequencing, most technicians couldn’t finish before 6 pm. During peak months, ShieldGuard spent $4,200 per month in overtime. That wasn’t an anomaly. It was the baseline from March through October.
• No visibility for emergency dispatch: When an emergency call came in (a rat in a kitchen, a wasp nest over a front door), Patricia had to call technicians one by one to find someone available and nearby. She’d check the printed job sheet, estimate where the tech might be based on how many jobs they’d completed, and start dialing. Finding the right tech took 10-15 minutes. Sometimes the customer called back before Patricia had even dispatched anyone.
• Zip code grouping didn’t work: Patricia tried sorting jobs by zip code instead of alphabetically. It helped slightly, but zip code boundaries in Tampa Bay don’t follow road networks. Two addresses in the same zip code might be separated by a 20-minute drive across a bridge or through downtown traffic. The improvement was marginal, and Patricia went back to alphabetical sorting after two frustrating weeks.
• Technician burnout: Two experienced techs raised concerns about the summer workload during a team meeting. They weren’t complaining about the number of jobs. They were frustrated by the wasted time between them. “I’m not tired from treating houses,” one of them said. “I’m tired of driving to them.”

The frustration peaked during a particularly busy week in June. ShieldGuard received 14 emergency calls in a single day. Patricia spent the entire afternoon on the phone, pulling technicians off their routes and redirecting them. Three scheduled appointments had to be pushed to the following day. Two of those customers left negative reviews. Patricia’s boss asked her to find a routing solution before the next peak month.

The Solution

Patricia found Upper after reading a forum post from another pest control office manager who described a similar alphabetical-routing problem. She signed up for a trial on a Friday afternoon and spent the weekend testing it with the following Monday’s job list.

The test was straightforward. She exported Monday’s 84 jobs from PestPac as a CSV, uploaded the file into Upper using the spreadsheet import, set different service times for each job type (20 minutes for routine inspections, 45 minutes for initial treatments, 60 minutes for commercial service, 90 minutes for termite work), and optimized across all 14 technicians.

Service-Time-Aware Routing That Accounts for Job Complexity

Not all pest control jobs take the same amount of time, and routing software that ignores that distinction builds inaccurate schedules. A routine quarterly inspection takes 20 minutes. An initial bedbug treatment takes 45 minutes. A commercial warehouse service takes a full hour. Termite treatments, which involve drilling, trenching, and applying product along foundation walls, can run 90 minutes.

Upper’s route optimization lets Patricia assign a service time to each job based on type. The optimizer factored those durations into sequencing decisions, so a technician with two 90-minute termite jobs and three 20-minute inspections received a route with appropriate spacing. Techs stopped running late in the afternoon because the schedule accounted for reality, not just addresses.

The result showed up immediately in the numbers. Average daily jobs per tech jumped from 6.8 to 8.9 during peak season. That 30% increase came entirely from eliminating wasted drive time, not from asking anyone to work faster or longer.

One Map, 14 Techs, and 90-Second Emergency Dispatch

Before Upper, emergency calls were Patricia’s most stressful task. A homeowner spots a wasp nest above their toddler’s play area at 2 pm. They call ShieldGuard, expecting immediate help. Patricia had no idea which technician was closest, who had finished their last job, or who had the lightest remaining schedule. She’d call three or four techs before finding one who could respond.

Upper’s live tracking dashboard changed that process completely. Patricia could see all 14 technicians on a single map in real time, along with their remaining stops and estimated completion times. When an emergency call came in, she identified the nearest available tech, added the stop to their route, and the tech received the updated route on their phone. The entire process took about 90 seconds.

Specific Time Windows That Customers Actually Appreciate

Pest control customers expect a time window for their appointment, but “sometime between 8 am and 5 pm” is barely better than no estimate at all. Homeowners don’t want to spend an entire day waiting for a technician. Before Upper, ShieldGuard couldn’t provide specific windows because they genuinely didn’t know when each tech would reach each stop. The routes were too unpredictable.

With optimized routes and accurate service times, Patricia could now assign realistic time windows. Upper’s customer notification feature sent each customer a message with a specific one-hour arrival window: “Your technician will arrive between 2 pm and 3 pm.” Customers knew exactly when to expect service, which reduced no-access situations and eliminated most “when are you coming?” calls to the office.

The improvement in customer satisfaction was difficult to quantify precisely, but the review trend was clear. ShieldGuard’s Google rating climbed from 4.2 to 4.6 stars over four months, with multiple reviews mentioning the arrival notifications by name.

The Impact

ShieldGuard Pest’s first full peak season with Upper produced results that Patricia summarized in one sentence during a team meeting: “We did more work with less stress and spent less money doing it.”

The overtime numbers told the financial story. Peak season overtime dropped from $4,200 per month to $800. Over the eight-month peak period, that represented more than $27,000 in savings. But the more significant change was operational. Technicians finished their routes 1 to 1.5 hours earlier on average, which meant they could accept late-afternoon emergency calls without pushing into overtime. The company absorbed a 30% increase in daily job volume without hiring a single additional technician.

Patricia stopped printing alphabetical job sheets entirely. Each morning, she exported the day’s schedule from PestPac, imported it into Upper, optimized across all 14 techs, and dispatched. The process took about 15 minutes. The rest of her morning, previously consumed by phone calls and route troubleshooting, was now available for customer follow-ups, scheduling, and the operational planning she’d never had time for.

ShieldGuard’s owner approved a commercial pest control expansion into two new zip codes for the following season, something that would have required two additional hires under the old routing system. With Upper’s optimized routes, the existing team could absorb the growth.

Performance Metrics