A minimum advertised price policy sets the lowest price a reseller may advertise your product at. It does not set the price they sell at, which is a distinction worth keeping straight: MAP is about the advertised figure, which is why monitoring it means watching listings rather than watching sales.
Brands put these policies in place to stop a race to the bottom that damages the product’s perceived value and undercuts resellers who honour the agreement. The policy itself is the easy part. Knowing whether anyone is following it is the hard part.
Why manual checking does not scale
The usual approach is for someone to search for the product periodically and look at what comes back. It works at small scale and then quietly stops working, for reasons that have nothing to do with effort.
The product count multiplies. Every item has its own MAP figure, and a catalogue of any size means a search per item rather than one search.
The reseller count multiplies again. The same item appears across marketplaces, reseller sites and storefronts you did not know existed.
Timing defeats it. A listing that breached MAP on Tuesday and was corrected on Thursday is invisible to a check run on Friday, and those are often the ones worth knowing about.
And the results are noisy. Search for your own product and you get secondhand units, bundles, unrelated items with similar names, and listings from other regions. A person can tell the difference, which is exactly why it takes a person so long.
The result is predictable: monitoring happens when someone has time, which is to say when something has already gone wrong.
What automated monitoring actually does
The version we build runs on a schedule and does four things, in this order.
It checks reseller listings on a recurring schedule rather than relying on occasional manual searches. That is the part that turns monitoring from an event into a process.
It compares the observed pricing with the minimum advertised price stored for the relevant item. The comparison is item-level, against your own stored figure, not against a market average or a competitor set.
It preserves the exact price difference on the flag, so the brand team can review what was found and why it was classified as a violation. This matters more than it sounds. A flag that says “violation” is an assertion. A flag that says “listed at this price against a MAP of that price, on this date” is evidence.
And it suppresses the noise with keyword rules, filtering secondhand and unrelated results that would otherwise create false positives. This is the step that decides whether the output gets read. A monitor that cries wolf gets ignored inside a month.
On the ERP we built for a US consumer electronics brand, that automated monitoring process checks reseller listings for MAP violations and flags them, and reseller pricing is now monitored continuously against MAP agreements rather than checked occasionally.
Where it belongs
We build this inside the system that already holds the item data, because the MAP figure is item data. It belongs on the item record alongside cost and price, not in a separate tool with its own copy of your catalogue.
That has a practical consequence. When a new product is set up, its MAP figure is captured in the same place as everything else about it, so the monitoring covers it automatically. In a separate tool, new items are covered when somebody remembers to add them, which is the quiet way monitoring coverage decays.
It also means the flags sit next to the commercial context. Whoever reviews a violation can see the item, its cost, its own pricing and its channels without opening a second system.
What to do with the results
This is where brands differ, and it is where software should stop making decisions.
A flag is a finding. What follows is a policy question: whether to contact the reseller, whether a first breach is treated differently from a repeat, whether the account is restricted, and what evidence you want on file before any of that happens. MAP enforcement terms, and what action a brand can take on a breach, are a matter for the brand’s own policy and its legal counsel rather than for an engineering decision.
What the monitoring should give that process is a clean record: what was observed, at what price, against what stored MAP, on what date, with the noise already filtered out. Everything after that is the brand’s call.
The pattern we see work is a review step rather than an automated action. Flags land in a queue, a person confirms them, and the confirmed ones feed whatever enforcement process the brand already has. Automating the detection is valuable. Automating the consequence is a decision nobody should let a scheduled job make.
Where to start
The first question is not technical. It is whether your MAP figures are recorded anywhere a system can read. If they live in a contract PDF or in one person’s knowledge, that is the first piece of work, and it is worth doing even if you never automate the monitoring.
Once the figures are item data, the monitoring is a scheduled comparison, and the design effort goes almost entirely into the false-positive filtering rather than into the comparison itself.
We build this as MAP monitoring and brand protection inside the ERP that already holds your items, alongside the wider channel and pricing work on Amazon seller services. The system it runs in is described in our multi-marketplace ERP case study. If reseller pricing is something you currently check by hand, get in touch and tell us where your MAP figures are recorded today: could a system read them without someone typing them in first?
Common questions
How often should monitoring run?
On a recurring schedule rather than on request, because the point is to catch a listing while it is still live. The right interval depends on how fast your reseller pricing moves rather than on a general rule.
What stops it flagging secondhand listings as violations?
Keyword rules that suppress secondhand and unrelated results. Without that filtering, the volume of false positives is usually enough for a brand team to stop reading the output.
Does the monitor decide what counts as a violation?
It compares an observed price with the minimum advertised price stored for that item and records the difference. Whether that difference is actionable is a judgement for the brand, not for the software.