Why manufacturers selling through distributors lose price conversations — and how to turn it around in a few weeks

Problem 1: your distributor knows your online channel better than you — and they know it

The sales-through-partners model has information asymmetry built in. The distributor looks at competitor prices every day because their own sales depend on it. The manufacturer looks at the online channel only when something starts to happen — usually when the distributor tells them something is happening.

In practice this means:

• Every price conversation starts from the partner’s narrative. They define what the “market problem” is, and you react to their version of reality.
• Low-margin arguments are hard to verify in real time. Before the sales rep checks 20 offers from different retailers, the conversation is long over — and the next tranche of commercial terms has already been agreed around that very argument.
• You lack an objective reference point for your own recommended pricing policy (MSRP / MAP). You don’t know whether it is being respected, who is undercutting, by how much, and how often.

The result is rarely one dramatic concession. It is a steady drift — successive small margin, promotional, logistical concessions — which after a year turns into a visible dent in the manufacturer’s P&L. And it’s hard to reverse, because each of those decisions can be rationally justified on its own.

Problem 2: manual checking no longer keeps up — and this is not about your team’s goodwill

Ten years ago a manufacturer’s sales team could do a round of a few key stores once a month and have a decent picture of the situation. Today the same assortment can be sold by dozens of retailers — on their own stores, Allegro, Amazon, comparison marketplaces, in “product of the week” promotions at a specific chain.

Yokohama described it in their deployment bluntly:

“Price knowledge is available — the offers are public. But their sheer volume makes it operationally inaccessible. Nobody can track it without automation.”

It’s a very apt framing and worth pausing on. The problem isn’t that the data isn’t there. The problem is that it is — but scattered across several hundred URLs, changing several times a day, and no human can cover it without a tool that does it for them. Every attempt to maintain “manual” monitoring ends the same way: the team covers 10–20% of the market and makes decisions as if it covered 100%.

And here we reach the mechanism Yokohama called the reactive model — prices were only checked when one of the partners flagged a discrepancy. That approach has two costs that don’t show up in any report:

• It limits the scale of verification. You check only what someone asks about — not what actually matters.
• It extends reaction time. By the time the problem reaches you via a partner, it has usually been going on for weeks.

Yokohama case: what changes when a manufacturer starts seeing its own channel

Yokohama is a Japanese tyre manufacturer selling in Poland through a distributor network. The sales team is responsible for partner relationships and analysis of the online pricing situation — and until recently did so in the reactive model described above.

The Dealavo deployment in their case covered:

• 1,500 key references under permanent monitoring,
• 4 key e-commerce sources relevant to the tyre industry,
• one consolidated weekly report for the sales team,
• ad-hoc checks on the same data — on demand, in response to a specific signal.

The decision to deploy didn’t come from outside. It was Yokohama’s internal initiative, because the team themselves wanted to stop relying solely on signals from partners. First conversations — November. Testing on a real portfolio — December. Regular use of reports — from the start of the following year. In other words: from decision to operational use of the tool took roughly two months, with no internal IT project and no building anything from scratch.

Effect 1: no more “he-said-she-said” conversations

This is the effect that alone justifies the whole deployment — even if nothing else came up. The Yokohama representative describes it like this:

“During conversations with one of our key distributors, arguments appeared regarding low margin levels and prices. On the basis of available reports we were able to clearly demonstrate that the presented information did not reflect the actual situation. The data presented confirmed our position, which allowed us to close further discussion on this matter.”

Note the last sentence: close further discussion. Without that data, the same conversation would have gone on — and would probably have ended in some form of concession “for the sake of the relationship”. With a hard report in hand, nothing had to be conceded, because there was no actual problem to solve.

Effect 2: a real picture of market structure, not just the top 3 players

The online channel in the tyre industry — and in most industries with distribution — is not homogeneous. Alongside a few large platforms there are smaller retailers with their own, often aggressive pricing policy. They most often trigger the “resonance effect”: a visible price at a small store becomes a big distributor’s argument in their conversation with you.

Permanent monitoring with price history lets you separate these: see whether a low price appears at one retailer as a one-off, or is the lasting policy of a particular channel. Cross-referencing this with your own commercial terms explains most price differences better than any conversation. That is exactly what a solid price monitoring setup is for.

Effect 3: seasonal anomalies caught in the week they happen

Tyres are an example of an extremely seasonal industry. But the same logic applies to air conditioning, garden, back-to-school electronics, holiday cosmetics, heaters, toys. Peak season is the moment when one distributor’s sudden discount can destabilise prices for the others for two weeks — and at the scale of seasonal sales that means real money.

Monitoring doesn’t take away the distributor’s right to set the final price (because that can’t be taken away anyway), but it lets you notice and ask the question in days, not weeks. And in the peak of the season, the difference between “I spotted it this week” and “I spotted it next month” is the difference between an intervention and a loss.

Effect 4: the sales team stops being a manual-scraping team

It’s a mundane effect, but in practice the fastest to feel. Instead of hours a week spent comparing offers in Google, the team receives a report and can get back to what they were hired for — conversations, analysis, decisions. In Yokohama’s case, 1,500 references stopped being “an item in someone’s manual workload” and became a backdrop against which strategic work can happen.

Three moments when market data changes the manufacturer’s game

If you’re not sure monitoring is for you at all, read the three scenes below carefully and check how many times a year you deal with any of them.

1. Negotiating commercial terms for the next quarter. The partner argues using margin or “competitor prices”. Without objective data you discuss their interpretation of the market. With data — you discuss numbers.
2. Peak season. A sudden, unagreed discount at one of the channels. The question isn’t “will you notice”, but “when”. Monitoring shortens that time from weeks to days.
3. A decision on MAP / recommended pricing policy. Any such policy lives only as long as it is enforced. Enforcement without systematic monitoring is fiction.

What to monitor and what not to — because that is a decision too

In the interview Yokohama said something that is an important hint for other manufacturers:

“Yokohama cared primarily about price monitoring, because price is the most directly comparable market indicator. Logistics terms, delivery costs and other costs are specific to individual counterparties, so they are hard to compare directly between distributors.”

That’s a healthy, pragmatic choice. The online price is the only element that is fully comparable across all market participants and publicly available. The rest — rebates, annual bonuses, payment terms, logistics costs — is a contractual world in which even the best tool won’t replace a commercial relationship and a history of cooperation.

A well-designed monitoring setup is therefore a tool that completes the picture, not one that replaces it. It delivers the hard, objective layer (market price), to which you add the soft layer (commercial terms, knowledge of the partner, knowledge of their channel).

Sources and methodology

• Yokohama × Dealavo case study (Polish deployment, 1,500 monitored references, 4 e-commerce sources, weekly report + ad-hoc checks) — quotes from material authorised by a Yokohama representative.
• Observations from the Dealavo client portfolio in the manufacturer → distributor segment (industries: automotive, home appliances, power tools, cosmetics, premium FMCG).
• Dealavo operational data on price-monitoring infrastructure (as of 2026).