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TOP 7 Most Popular Methods of MAP Deviations: Rating by Pricer24
A recent study by Harvard Business Review among manufacturers using a MAP (Minimum Advertised Price) policy found that unauthorized sellers deviated from MAP 50% of the time. Among authorized resellers, the level of deviations reached 20%.
In this article, you’ll learn about the tricks retailers use to get around the manufacturer’s suggested retail price.
Methods of MAP deviations
The Pricer24 team has been working with e-commerce businesses for over four years. Based on the experience of performing various client tasks, our experts have compiled a rating of the methods of MAP deviations, which online stores resort to most often.
Please note that the deviation methods in the table are listed from critical for the vendor (strongly affecting prices in the entire market) to less critical (not strongly affecting).
Method No. 1. Open price
On the website of the online store, the price, which is lower than the MAP, is openly displayed: it is available to all buyers and is indicated in advertising messages.
The reason for the MAP deviations can be a chain reaction, that is, one retailer automatically lowered the price in response to a drop in the price of another. As a result, there is a snowball effect: the price falls throughout the market.
The degree of criticality for the vendor: high. The entire market is falling, and quite quickly, because in many online stores the “robot” automatically changes prices, focusing on the price change of competitors. For example, the algorithm establishes a rule: if the MAP of a direct competitor is deviated, then set the price for X $ less than his price.
The solution is the automation of data collection for monitoring and regular price parsing.
Method No. 2. MAP deviations according to the schedule
It happens if the partners, having technical data or other sources of information, know that control will be made. At the time of the control, the price is approximately equal to the MAP, and at other time intervals, it is lower than the MAP.
The degree of criticality for the vendor is high (the entire market is falling).
The solution is regular and automated data collection, the absence of a schedule for the parser to pass through partner sites, as well as the use of the Pricer24 report “History of Deviations” (by time and number).
Method No. 3. Deviations at night and on weekends
They happen because the vendor’s managers do not respond to them during non-working hours.
The degree of criticality for the vendor is high (the entire market is falling).
The solution is the automation of MAP monitoring with frequent parsing without a standard parser pass schedule.
In Pricer24, all deviations at night and on weekends fall into the report “History of Deviations”. The manufacturer’s manager can look at who deviates from the MAP at night and on weekends, see if this is a systemic phenomenon, and find out who starts the chain reaction first.
Method No. 4. Promo codes
The price based on the promotional code is not displayed on trading platforms and price aggregators but can be offered to the client in newsletters. For example, all site visitors see the price within the MAP, however, if the user goes to the site from a promotional newsletter, he sees a lower price in the corresponding block of the product card.
Not all manufacturers consider such actions by a partner to be a deviation, but it can lead to a price war from the point of view of the retailer’s policy, who saw the price of a competitor using a promotional code.
The degree of criticality for the vendor: medium — not the entire market is falling, because not everyone monitors the prices of competitors by promotional codes.
It depends on the scale of the site – if it is large, others will match it, and therefore, the scenario described in method No. 1 (chain reaction on the market) is possible.
Solution: if our client-vendor considers the price in the promotional codes to be a deviation, we offer data expansion during parsing — so that, in addition to the prices on the site, the prices according to the promotional codes fall into it.
Method No. 5. Hiding goods from price aggregator listings
Some brands monitor only price aggregators due to the lack of data collection automation. Internet stores, knowing about this, do not display certain items on price aggregators, the price of which is lower than the MAP on their website.
The degree of criticality for the vendor: medium — a price lower than the MAP is seen only by those customers who go directly to the website of the online store. The market does not always react.
The solution is regular parsing of the entire market: both price aggregators and partner sites directly.
Method No. 6. Creation of product duplicates
A duplicate product card is created without an article number and additional data. The goal is that the client seems to understand what kind of product it is, but the parser may not find it or identify it (for example, if monitoring occurs only through links to products from previously defined bundles).
The degree of criticality for the vendor: low – the client will not always respond to an offer that contains very little information. Competitors can also ignore such product cards.
The solution is to constantly parse all product cards by brand and track new products in the retailer’s catalog for comparison.
For example, we parse not only the prices of goods but also the catalog of our client’s partner (new products, etc.).
Method No. 7. Protection against parsing
IT specialists of online stores put protection against “robots” primarily so that competitors cannot parse prices. And since not all vendors use high-quality parsing services that quickly adapt to these protective measures (changing price coding, converting prices to images, blocking IP addresses of “robots”, etc.), thus killing two birds with one stone: hiding prices from both competitors’ parsers and vendors’ parsers.
The degree of criticality for the vendor: depends on the data provider.
The optimal solution for a vendor is cooperation with a good data provider. For example, with Pricer24, we solve this problem by daily monitoring the work of parsers and promptly making adjustments.
The MAP should be designed in such a way as to give all parties involved the opportunity to profit from the final sale. Therefore, it should reflect not only the costs in the production process but also the average markup of retailers. To do this, the manufacturer must have a good understanding of the cost structure of the retail sector and build a pricing strategy so that retailers achieve their profit targets.
Really control the MAP
There are cases when manufacturers have suggested retail prices, but in practice, they are poorly controlled: they use outdated technical solutions, monitor only price aggregators or only market leaders, and check MAP according to the schedule (which, of course, partners know about), etc. A large array of information is not taken into account.
Pricer24 helps you control MAP:
see which of the partners has more / fewer deviations, how often and to what extent stores set the price below the MAP, in which categories and for which goods;
quickly determine which of the retailers was the first to deviate from the MAP;
in a few clicks, find out at what prices your goods were sold at night and on weekends;
find problem areas that should be dealt with in the first place;
determine which of the partners can be involved in compliance with the MAP based on the results of a certain period;
export lists of goods for which there are deviations from MAP to Excel;
set up automatic sending of letters to your email or retailer when deviations are detected by the service.
And all this — with minimal time spent by brand managers, because data collection is carried out automatically.
Stimulate partners to adhere to MAP
The MAP has a recommendatory nature, that is, the manufacturer has no legal grounds to force retailers to comply with it — it is illegal to introduce fines for non-compliance with the MAP.
In conditions where “tough measures” are not possible, various incentive practices are emerging from the vendor side for retailers who adhere to the MAP. It can be a discount for the next purchase or a bonus for the product sold for a certain period.
Important: the manufacturer must take care to convey to the partner information about the benefit of such a bonus program and compliance with the policy of suggested prices.
And of course, it is necessary to ensure transparent conditions for all partners. This task is easy to perform if the brand manager always has a report with the price history at hand, after analyzing which it is possible to determine to whom the bonus belongs according to the results of the quarter.
Our clients use the report on deviations mentioned above for these purposes.
In the diagram, you can see that the partner marked in lilac had the most deviations from the MAP for the week, and the partner marked in green had the least.
Switch to tabular view:
The same report can be made for any period of interest to you for all counterparties.
There are a lot of ways to bypass the MAP: some of them have big risks for the vendor, some less. But all of them can be minimized if your MAP policy implies a fair markup, effective automated control, and a transparent motivation system for partners. Based on the experience of our clients, it is these three conditions that make it possible for brands to enforce the suggested price policy even in the most highly competitive e-commerce niches.
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