← Commercial Intelligence Engine 02 · SpotOn

Know exactlywhat to do next.

In the traditional channel, the distance between the plan and the shelf is where the strategy gets lost. SpotOn turns what you decided in planning into the specific stores each rep visits tomorrow and what to do in each one, with every level of the commercial structure reading the same data and the metrics they are actually measured on.

One solution: Commercial Intelligence. Two engines in sequence, and what the field reports comes back to sharpen the intelligence.
01
Network Expander
The complete store universe, scored by potential
02
SpotOn
The universe turned into daily direction for every role
Failure 02 of 2 · The strategy fails in translation

Strategy does not survive the trip to the shelf

Your commercial strategy fails twice in the traditional channel. Network Expander closes the first failure, the market you cannot see. This is the second one. A decision made in planning has to travel through a director, a supervisor and a rep before it becomes something that happens in a store, and every handover costs a little of it.

01

Direction gets diluted on the way down

What was a specific commercial priority becomes a general instruction by the time it reaches a route. Each level reinterprets it against a different spreadsheet, and no two versions of the week fully agree.

The costThe plan that runs in the field is not the plan you set.

02

What actually happened comes back too late to fix

Execution is reported on paper, in chat threads, or at the end of the month. By the time a store going off-route is visible to anyone who could act, the week it belonged to is over and so is the chance to recover it.

The costNo signal on whether your decisions are working at all.

The most valuable insight is worthless if it does not survive the journey from the director’s screen to the shelf.

Not a dashboard

The order of the day is calculated, not assigned.

A route has always been somebody’s judgement. A supervisor’s read of the territory, last year’s map, or the order the stores happen to fall in on the way home. SpotOn does not ask anyone to make that call better. It takes the call away.

Underneath every screen are the same proprietary models that built the universe. They have already worked out what each store could buy, how likely it is to be lost, and where it sits in its own commercial life. The route a rep opens in the morning is the output of that calculation, ordered by what each stop is actually worth rather than how easy it is to reach.

That is the difference between intelligence and a dashboard. A dashboard puts numbers in front of a supervisor and leaves the decision to them, usually at the end of the week, when it is already history. The model decides first, and hands the decision to the person who has to act on it, in the only form they can act on: this store, this order, today.

Nobody in the field has to understand a model to use one.

They see stops, in order, with what to do at each one.

Intelligence at every level

One database, three jobs

Everyone involved in the strategy gets a view of execution built for what they actually do, with the metrics that role is actually measured on. Same models underneath, different decision on top.

RepThe daily mission

Opens the day to a routed list of stops on a map, ordered by what each store is worth rather than what is convenient. Each stop carries task-level direction: what to check, what to sell, what to fix on the shelf. Reporting back is one or two taps at the door, not a form filled in at night.

TracksStores visited against plan, orders per visit, tasks completed, exceptions raised.
SupervisorThe week under control

Sees execution against plan as it happens, so a rep running behind or a store dropping off route is visible the same day rather than at month end. Exceptions can be reassigned while the week is still recoverable, which is the difference between managing a team and reading about it afterwards.

TracksEffective visit rate, coverage against plan, open exceptions, team performance side by side.
DirectorStrategy against shelf

Sets a target anchored to real potential rather than last year plus a percentage, hands it down, and then watches whether it reached the store. SKU distribution against strategy, predicted against actual while a campaign is still running, and where the gap between decision and execution is widest.

TracksDistribution against target, volume against plan, coverage gained, execution compliance by region.

One shared source of truth.

Every role reads the same database, so direction does not change shape on the way down and nobody spends the first hour of a meeting reconciling three versions of the same week. When the rep marks a store, the supervisor and the director are looking at it too.

Adoption

Your reps will use it, because it pays them back

The usual reason this kind of project fails is that it watches the field without giving the field anything. SpotOn is built the other way round. The rep gets the stores worth their time ranked first, a route that earns more in the same day, and exceptions reported in one or two taps instead of a form filled in at night. The supervisor gets their week back. The director gets a read they have never had. And we do not hand it over and leave: our team rides routes during rollout, because adoption is won or lost with the supervisors and the reps, not in the launch meeting.

It sits above the app you already run.

A field sales app records that a rep was at a store. That is a record of activity, not a decision about where the activity should have gone. SpotOn is the intelligence layer on top: it chooses which stores matter and what to do at each one, and it can feed those decisions straight into the SFA or CRM you already have rather than replacing it.

Built for a phone in a shop doorway.

The rep view assumes one hand, a few seconds and an unreliable signal, because that is the real condition of the job. Nothing in it requires a rep to interpret a dashboard or understand the model behind the ranking. It tells them where to go and what to do there.

Trusted by consumer goods leaders

These models read the channel, not the company. A traditional channel has the same structure whether you ship a million cases a month or a fraction of that, so the same models run for the largest bottlers in the region and for teams a tenth their size. Nothing here is an enterprise product scaled down. And these models were not adapted for Latin America. They were built in it, inside the channel structures the region actually runs on.

The loop closes

What the field reports feeds the models

Execution is not just the end of the process, it is the best data source in it. What each store actually ordered, what was on the shelf, whether it is still open and still buying: all of it goes back into the potential estimate, the churn risk and the visit frequency behind Network Expander’s ranking. So the universe gets more precise the longer your team works it, and the next decision starts from better ground than the last one.

That closes the second failure. The first one is where the universe comes from.

See Network Expander Execution is only as good as the intelligence behind it. Engine 01 builds and scores the complete store universe the routes are drawn from.
FAQ

Questions commercial teams ask

Will our reps actually use it?

That is the right question to ask, and it is usually why this kind of project fails. SpotOn is built so the rep gets something back rather than simply being monitored: the stores worth their time ranked first, a route that earns more in the same day, and exceptions reported in one or two taps. Our team also rides routes during rollout, because adoption is won or lost with the supervisors and reps, not in the launch meeting.

Does this replace our field sales app?

No. It sits above it as the intelligence layer. Your app records what happened; SpotOn decides where the activity should go and what to do at each store, and it can feed those decisions into the SFA or CRM you already run. They track. We decide.

What does each role actually see?

The rep sees a routed list of stores with task-level direction per stop. The supervisor sees execution against plan in real time, with exceptions they can reassign the same day. The director sees SKU distribution against strategy and whether the decisions made in planning reached the shelf. All three read the same database, each with the metrics that role is measured on.

How does this change what a supervisor does day to day?

It moves them from reconstructing the week afterwards to steering it while it is happening. Instead of collecting reports and assembling a picture on Friday, they see coverage against plan on Tuesday and can move a rep before the week is lost.

How long before we see results?

Commercial results follow the first execution cycle, because the model only pays once the field acts on it. The store universe it works from is typically ready in about four weeks. We agree the success metrics with you before we start and report against them.

Turn the strategy
into tomorrow’s route

A 30 minute call, then an audit of one territory, so you can put a number on the opportunity you are not working yet.

Talk with an expert

Tell us how execution reaches your field team today, and what comes back.
We will walk you through how the same week runs when every role works from the same ranked data.

  1. 1A 30 minute call. You describe how direction reaches the route today.
  2. 2We show you the same week run as one shared plan, from the director’s target down to the stops on a rep’s route.
  3. 3You get the audit findings, and we scope the work from there.

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