Google Cloud Commercial and Professional Services United States

Proforce Pest Control

Customer Service Automation · Enterprise Knowledge Search · Real-time Analytics

Headquartered in Boca Raton, Florida, Proforce Pest Control provides residential pest control across 13 branches in five Southeastern and Mid-Atlantic states. The business grew out of a series of acquisitions, inheriting a team of 80 field employees and thousands of customers. But, crucially, it was without an established technology infrastructure needed to run the business effectively.

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22% less fuel per appointment after route optimizations

50 hours of contact center labor saved daily with Gemini

50% less time spent building daily routes

Proforce built a Google Cloud foundation from day one to operate smarter, serve more customers, and scale across 13 markets.

Reported impact

Business outcome

22% less fuel per appointment after route optimizations; Up to four extra stops each day per driver with route optimizations; 50 hours of contact center labor saved daily with Gemini; 50% less time spent building daily routes.

Solution

Proforce had its data infrastructure up and running in just a few months. Charles Fox, Proforce's Chief Strategy Officer, describes BigQuery as "the central nervous system of everything we do." The company built custom Python pipelines running on Cloud Run to pull customer data straight into BigQuery. Looker connects directly to the same dataset, meaning every dashboard and report across the business—from dispatcher screens to executive reporting—draws on the same live data. That live connection enables Proforce to automatically remove past-due accounts from service lists before daily routes are built, eliminating wasted visits and unpaid work. "It sounds basic," says Shorr, "but it's incredibly impactful." By deploying AI-powered transcription and summarization through Gemini in Google Workspace, Proforce eliminated that step in almost all cases, saving roughly 50 hours of agent time every day.

Data flow

stored or unified in BigQuery, and surfaced through Gemini, Looker, Cloud Run, Google Maps Platform

Solution architecture

5 components · 2 layers

Storage
- BigQuery Stores and queries the analytics and AI-ready datasets that power the workload.
Serving
- Gemini Powers natural-language reasoning, summarization, generation, or assistance inside the workflow.
- Looker Provides the governed semantic layer, dashboards, and self-service analytics used by business teams.
- Cloud Run Runs application services and proprietary code in a managed container environment.
- Google Maps Platform Adds geospatial context and mapping capabilities to the user-facing application.

Architecture clues

"The choice of which platform to use was obvious," says Shorr. "I’d already had such a positive experience working with BigQuery, Looker, and several other Google Cloud tools in my prior role."
50 hours of contact center labor saved daily with Gemini
After following Afi Labs , a Google Maps Platform specialist, on LinkedIn, Shorr reached out, explained the problem, and together they built the Proforce Route Planner on top of the Route Optimization API.
Cloud Run Routes Optimization
Proforce built a Google Cloud foundation from day one to operate smarter, serve more customers, and scale across 13 markets.
There wasn't even a question of which platform to work with. I’d already had such a positive experience with BigQuery, Looker, and every other aspect of Google Cloud in my previous role, that it was a no-brainer.

Evidence from the source

22% less fuel per appointment after route optimizations

50 hours of contact center labor saved daily with Gemini

50% less time spent building daily routes

Proforce built a Google Cloud foundation from day one to operate smarter, serve more customers, and scale across 13 markets.

Up to four extra stops each day per driver with route optimizations

Transparency Evidence & methodology 95/100 reference value · 79% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value95/100

Problem clarity20/20
Measures whether the customer's operational problem is specific enough to compare.
Implementation depth20/25
Rewards named components, data flow, integrations, and architecture detail.
Outcome specificity20/20
Measures whether the reported benefit is concrete rather than a generic claim.
Quantified impact25/25
4 metrics describe measurable impact.
Deployment scale10/10
Rewards evidence of a live or scaled deployment and meaningful integration scope.

Evidence confidence79%

Source authority20/25
The main evidence is an official vendor-published customer story.
Claim traceability21/25
10 of 12 key fields link to a named source.
Direct evidence20/20
5 direct source quotes retained.
Date provenance0/10
The publication date has no documented provenance.
Source transparency8/10
1 source reference document publisher, URL, authority, retrieval, and supported fields.
Implementation specificity10/10
Rewards source-backed components, data flow, quantified impact, and a specific outcome.

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

Google Cloud
Proforce Pest Control customer story

First-party
https://cloud.google.com/customers/proforcepestcontrol

Source type
Vendor-published customer story
Supports
- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes

Date evidence

First archived Jul 25, 2026 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
Open date source
Sitemap last modified Jul 23, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.
Open date source

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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