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Case Study — Field Sales & Location Intelligence

Geofencing & Dwell-Time Verification for Field Sales Coverage

A GPS-based geofencing and dwell-time engine that tells a sales leader, for every assigned customer, every day, whether a field rep genuinely made the call, without relying on the rep's own word for it.

PlatformManager Web Dashboard + GPS Field App
DurationProof-of-concept engagement
TypeField Sales & Location Intelligence
Stack8 technologies
PROJECT OVERVIEW

6

Distinct visit outcomes captured

<5 min

Minimum dwell time defining a real visit

2

Independent signals verified per visit

THE CHALLENGE

WhatsApp messaging gets complicated at scale.

Field sales is one of the hardest functions to manage remotely. A sales leader assigns a rep a beat plan, a list of customers to visit, in order, with an objective for each stop, and then has almost no reliable way to know what actually happened out in the field until the numbers come in at month-end. Visit reporting is self-reported, coverage percentages can lie in both directions, drive-past visits go undetected, route and territory compliance is unverifiable, tracking gaps look identical to deliberate misconduct in naive systems, and manual audits cannot scale across a distributed sales force.

Challenge 1

Visit reporting is self-reported. A rep files a check-in with an outcome note, and the manager has no independent way to confirm the rep was actually at that customer when they filed it.

Challenge 2

Coverage percentages can lie in both directions. A rep can look like a top performer on paper while skipping real work, and a rep who did everything right can look like a poor performer because of a missed check-in or a dead phone battery.

Challenge 3

Drive-past visits go undetected. A rep can pass within sight of a customer's shop without stopping long enough to actually make a call, and a simple "was the rep nearby" system will still count it as a visit.

Challenge 4

Route and territory compliance is unverifiable. Without location evidence, managers cannot confirm reps are covering their assigned territory in the planned sequence rather than cherry-picking convenient stops.

Challenge 5

No distinction between misconduct and bad luck. A tracking gap caused by a dead battery or a basement showroom with no signal looks identical, in a naive system, to a rep who deliberately went dark.

Challenge 6

Manual audits don't scale. Spot-checking a handful of reps by phone call or surprise visit cannot cover a distributed sales force across dozens of territories every day.

Measurable Impact
6Distinct visit outcomes captured, not just "visited / not visited"
2Independent signals cross-checked on every visit
5Real-world failure modes independently and correctly identified
<5 minMinimum on-site dwell time to count as a genuine visit
WHAT WE LEARNED
01

Coverage percentage is meaningless without independent verification: it can be perfect and still hide the most serious problem on the team.

02

Dwell time (continuous presence, not just proximity) is what separates a genuine sales call from a drive-past.

03

Every disagreement between GPS and self-reported data deserves its own explanation, not a single generic failure flag, because "unprovable" and "contradicted by evidence" are very different situations with very different consequences for the rep involved.

04

A verification policy that is visible and tunable builds trust with both managers and field reps: nobody has to take a black box's word for it.

Technologies Background
Our Technologies

Built with technologies we trust.

GPS Geofencing
Dwell-Time Analytics
Visit Verification Engine
Device Integrity Detection
Live Policy Tuning
Manager Dashboard
Route Mapping
ERP/CRM Sync

Project Goals

Build a geofencing and dwell-time engine that can tell a genuine customer visit apart from a drive-past, using GPS evidence alone.
Cross-verify that GPS evidence against the rep's own manual check-in, so agreement between the two signals, not either one alone, is what counts as a confirmed visit.
Give every disagreement between the two signals its own distinct, explainable status, instead of collapsing everything into a single pass/fail flag.
Make the underlying policy (geofence radius, minimum dwell time, coverage threshold) a business decision managers can see and tune, not a hidden black box.
Separate genuine integrity concerns (spoofed location, impossible travel speed, a check-in filed from a customer the rep was never near) from honest operational noise (tracking gaps, low battery, an unfiled check-in on a day the rep was clearly on site).
Fit into the sales organization's existing customer and territory data rather than becoming a second, disconnected system of record.

The Outcome

The proof of concept showed that a coverage percentage alone is not a trustworthy metric: a rep can show 100% self-reported coverage and still be the most serious integrity concern on the team once GPS evidence is checked, while reps with legitimate tracking gaps were correctly cleared instead of penalized, proving the value of independent, evidence-based verification over self-reported coverage.

Conclusion & Impact

"Field sales has always run on trust: a rep says a visit happened, and a manager mostly has to believe it. Geofencing and dwell-time verification don't replace that trust; they give it something to stand on. By requiring two independent signals to agree, and by giving every kind of disagreement its own honest, explainable status instead of a single pass/fail flag, the system turns a distributed, largely invisible field sales operation into something a manager can actually see, measure, and manage fairly."

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