What is Minimum Advertised Price (MAP) monitoring and how to automate it?
In this article we will cover:
- Define: Minimum Advertised Price (MAP)
- MAP use cases, and practical business applications
- How can you automate your data collection monitoring?
Define: Minimum Advertised Price (MAP)
MAP is all about monitoring eCommerce prices as far as third-party vendors are concerned. Many companies produce, and sell their branded goods online. But in order to grow their target audience, they allow others to retail their products. This is an amazing way to increase sales with minimal effort but it also raises many issues which need to be addressed:
- Pricing: Due to competitive pressure, third-party vendors are sometimes tempted to drop prices below the pre-stipulated price point, laid out in the vendor agreements by the brand in question. The latter is known as a product’s Minimum Advertised Price (or ‘MAP’) i.e. the lowest a company will allow their goods to be sold for. Some third-party vendors are even willing to take a loss on certain items in order to attract business and drive profit margins on other products. This however harms the brands that are being ‘discounted’.
- Branding: Savvy consumers today do not simply buy products, they compare pricing on multiple sites, and read peer-written reviews. When third-party vendors undercut the original brand’s pricing this dilutes the brand’s value. The third-party vendor of course does not care – they were able to drive up short-term profit margins and make a few quick/easy sales. But the perception of the brand that has been devalued takes a hit, which in the long term can lead consumers to opt for a competing brand that appears to have a stronger ‘value moat’.
- Authenticity: Then there is of course the issue of knock-offs. Many vendors produce product ‘lookalikes’, selling them as if they are the real thing. This can be accomplished at a much lower price, as much less money needs to be invested in advertising and brand-building efforts. Consumers may even be fooled into thinking that these items are the real deal.
- Quality Assurance(QA): This leads us to our last point, QA. This can be at the product level. For example, even a gullible shopper who purchases a knockoff will likely notice that the quality of the item they ordered is sub-par. This can lead to a chain of events that can negatively influence brand reputation and conversion rates by association (for example, undesirable Reddit discussions that discourage future positive purchase decisions).
But QA can also be in the form of reviewing messaging on advertising campaigns, as well as on product listings. Imagine a third-party vendor adds low-quality product images and writes false product attributes on a marketplace product listing. Or, imagine they launch an advertising campaign that exaggerates a product’s capabilities, effectively ‘overselling’ an item and setting up consumers for disappointment.
By collecting open-source web data, companies can keep a watchful eye on third-party vendor activities and ensure that all pricing, marketing, and production activities are kept in line with corporate guidelines.
MAP use cases, and practical business applications
Here are 4 ways in which businesses are currently leveraging web data collection, and monitoring in the context of enforcing MAP among third-party vendors:
First, and foremost brands are constantly collecting live data on how vendors are pricing their items. This data is fed into internal systems and algorithms that alert their legal teams when vendor agreements have been breached. The relevant party on the team then reaches out and requests that pricing be amended immediately or further action will be taken. After a pre-defined period of time, say a week, companies will run another data collection job to ensure that the vendor in question has complied. They may even add them to a ‘black list’ running periodical data collection jobs in order to validate compliance over the longer term. Vendors that do not keep their word may be banned from selling a brand’s items in some extreme case scenarios.
Advertising, and marketing
When using web data for adtech companies or when internal eCommerce product marketing departments are looking to review third-party campaigns, data monitoring can be a very useful tool. This can take many forms such as ensuring that:
- Pricing published on advertisements are in line with brand MAP guidelines
- Visuals are high quality/resolution and accurately representative of the real-life version of the product
- Advertisement messaging is in line with the company’s ‘brand book’, and approved ‘brand narrative’
Quality Assurance, and counterfeit prevention
By collecting open-source data using product description keywords, known/approved SKUs (Stock Keeping Units), product location information, and other ‘product identifiers’. Companies can work to cross-reference, and correlate their approved list of third-party vendors with non-approved sellers. They can also use specific product attributes in order to easily identify fakes, a good example of this is product size or color. Sometimes counterfeiters will offer an item in purple when the original brand only offers it in green, blue, and gray. This data will set off the alarm bells as to fraudulent activity.
Brand protection is an umbrella term that pertains to anything that can harm a company’s perceived value. When approaching this from a data monitoring perspective businesses will want to:
- Scan search engines for brand/relevant keyword mentions
- Collect data from marketplace product/search results/category pages
- Keep an eye on customer reviews that mention the company/products in question
The logic here is simple. Cybercriminals, no matter how advanced, must abide by many of the same ‘rules’, and play the same ‘games’ that legitimate businesses are bound by. This means that fraudsters also need to optimize their listings and stores for SEO and that their shops will be held accountable by consumers vis-a-vis public feedback. It is by collecting these user-generated ‘data footprints’ that these actors can be caught, and stopped in their tracks.
How can you automate your data collection monitoring?
For companies that are looking to scrape web data at scale, an automated data collection tool may very well be the right solution for your business.
Bright Data has created hundreds of ready-to-use collectors that can help companies protect their brands, and monitor the web for MAP adherence by following a few simple steps:
Step 1: Choose your target site, and data set
Step 2: Hit ‘Create Collector’, and choose how you want to receive your data. This includes choosing:
- Between ‘real-time’ output, and ‘job completion (batch)’
- Your desired file format (JSON/NDJSON/CSV/XLSX)
- The delivery method i.e. Email/Webhook/AWS/ GCP/Azure/API Download SFTP/FTP
Step 3: Run the collector and receive instant results.
Step 4: Take further action when necessary, such as having your legal department reach out to the offending parties.
Check out this video demonstration of how you can get a data collector up and running in under 5 minutes: