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A buyer's framework for evaluating MAP monitoring and enforcement vendors. Published by ShopVision. Free to use and adapt, no attribution required. A sister template for competitive pricing intelligence is available separately.
MAP violations compound. One reseller breaks price, the marketplace algorithms react, authorized partners follow to stay competitive, and within days a single violation has become channel-wide margin erosion that takes months to repair. The economics of MAP enforcement are therefore about speed and attribution: how fast you detect, how precisely you identify who moved first, and how quickly you can act with evidence that holds.
This template is built around one principle: detection is table stakes, enforcement is the product. Most vendors can show you a dashboard of violations. Far fewer can tell you which seller started the cascade, produce an evidence package your legal team can use, and run the notice-and-escalation workflow that actually changes reseller behavior. Evaluate the distance between "we found 4,000 violations" and "we resolved them."
Use this template three ways:
One rule we'd urge you to keep: require every vendor to monitor a sample of your catalog across five resellers you name, including at least one marketplace, before you sign anything. Section 15 shows how to structure that.
MAP enforcement crosses more functions than most software purchases: it is a sales relationship issue, a legal issue, and a data issue at once. Wholesale and channel sales own the reseller relationships (Sections 4, 7, 8, 9), legal owns evidence quality and enforcement risk (4, 8, 9), revenue ops owns workflow fit (5, 9, 10), ecommerce owns coverage (2, 3), data and analytics own delivery and the AI layer (10, 11), IT and security own the email integration (9, 12), and procurement owns the year-two cost case (1, 13, 14). Assign sections before you send the RFP.
A note for IT: if you want violation notices sent from your own domain (you do, see 9.6), your IT team has a small but real onboarding task. Involve them at RFP stage, not at implementation.
Score every question 0 to 5. Weight the sections that match your channel reality: a brand fighting marketplace chaos should weight Sections 6 and 7 heavily; a brand with a disciplined dealer network and a leakage problem should weight Section 8.
Scoring rules that keep vendors honest:
A suggested weighting appears in the scorecard at the end. Adjust it before sending, not after responses arrive.
Why this matters: MAP enforcement is a multi-year program, not a project. You are choosing a partner whose data your legal team may one day rely on. Stability, focus, and domain depth matter more here than in most software categories.
Describe your company: founding year, ownership structure, headcount, and headcount specifically dedicated to data operations and data quality.
What percentage of your revenue comes from MAP monitoring and brand protection specifically? Is this your core business or a module attached to a different one?
List three brand customers of similar size and channel structure to ours who have been live for more than 12 months, and confirm they are available for reference calls.
What is your gross customer retention rate over the past 24 months? If you will not disclose it, explain why.
Summarize your MAP and brand protection roadmap for the next 12 months. What are the two largest investments you are making, and why?
Watch for: vendors whose MAP capability is a reporting layer on a pricing tool built for retailers. The workflows are different: retailers compare prices, brands enforce policy against named accounts. Ask which use case the product was designed for first.
Why this matters: your violation picture is only as complete as your coverage. The violations that hurt most often come from sellers and channels you were not watching: a marketplace storefront, a regional dealer's site, a discounter three tiers down your distribution.
For the reseller list attached to this RFP, confirm which sites you already monitor today versus which you would need to add. For sites you would add, what is the lead time and is there an added cost?
Which marketplaces do you cover (Amazon, Walmart Marketplace, eBay, Target Plus, category-specific marketplaces), and to what depth: first-party offers, third-party offers, Buy Box tracking, offer-level detail per seller?
Describe how you collect data: your own collection infrastructure, third-party providers, or a mix. Describe your approach to collection compliance, including how you respect site terms of service and applicable law.
How do you handle resellers whose violating prices only appear in-cart, behind a login, after a coupon, or via "click to see price" mechanics? A MAP program that cannot see hidden pricing misses the most deliberate violations.
What geographic markets and currencies do you cover? If our MAP policy differs by region, can monitoring rules differ by region too?
What happens when a reseller redesigns their site? What is your average time to restore full monitoring after a site structure change, are rectification steps human based or fully automated, and how are we notified of data gaps?
Watch for: coverage counted in sites rather than offers. On marketplaces, one product page can hide forty sellers; a vendor that monitors "Amazon" but not the individual offers behind the Buy Box will miss most of your marketplace violations.
Why this matters: MAP compliance is enforced at the variant level. A reseller can be compliant on the black medium and violating on the pearl blue XXS, and a tool that matches at product level will average that violation away. Weak matching also produces false accusations, and one wrongly accused reseller costs you more channel trust than ten missed violations.
Describe your matching methodology end to end: what signals you use (GTIN/UPC, MPN, ASIN, title, description, images, attributes), how automated matching works, and where humans are involved.
Describe how you match at the variant level: size, color, pack count, model year. Can a violation be detected and evidenced on a specific variant, with that variant selected and visible?
What match rate do you typically achieve for brand catalogs in our category? State it as exact matches, close equivalents, and unmatched, and be specific about how you define each tier.
Will you run your matching engine on a 500-SKU sample of our catalog, across five resellers we name including one marketplace, before contract signature? If not, why not?
How do you handle the hard cases: multipacks and bundles, retailer-specific SKUs and exclusives, discontinued items still in reseller inventory, and refurbished or open-box listings that sit outside MAP policy?
Do matches carry a confidence score visible to us? Can we require human approval of matches before they become eligible for violation detection and notices?
When we find a wrong or missing match, what is the correction workflow and turnaround time? Do corrections persist, or can they be overwritten by your next matching run?
How are matches re-verified over time as products are added, discontinued, repackaged, or relisted? On what cadence do you re-verify (weekly, monthly, other)?
How does our catalog get into your system: direct feed from our PIM or ecommerce platform, CSV import, or scraping of our own site? How are MAP prices loaded and updated, including scheduled MAP changes?
Watch for: any vendor who resists 3.4, and any workflow where violation notices can fire on unapproved matches. Enforcement built on unverified matching sends angry emails to innocent resellers. The approval gate in 3.6 is not bureaucracy; it is what makes automation safe.
Why this matters: a violation you cannot prove is a phone call that goes badly. Evidence quality determines whether your enforcement escalates from friendly reminder to legal action without collapsing under "that's not what our site showed." Accuracy determines whether resellers take your notices seriously or learn to ignore them.
How is a violation verified before we are alerted? Describe the checks between "our system saw a low price" and "this is a confirmed violation worth acting on."
What evidence do you capture per violation: timestamped screenshots of the product page with the correct variant selected, the observed price, the MAP price, the URL, and the SKU, GTIN, and ASIN identifiers?
Is the evidence package exportable in a form our legal team can use: per-violation records, screenshot archives, and a violation history per seller over time?
What is your false positive rate on violation detection, how do you measure it, and what is the remedy when a notice is triggered by bad data?
How do you distinguish violation types that matter differently: advertised price versus in-cart price, temporary promotion versus permanent price drop, authorized reseller versus marketplace third party?
Do we have audit rights? If our team spot-checks 100 flagged violations against live sites and confirmation falls below your committed accuracy rate, what is the remedy?
Show us your data quality reporting: ongoing visibility into monitoring success rates, match health, and known coverage gaps.
Watch for: evidence that would not survive a dispute. Ask to see a real evidence package in the demo, then ask: if the reseller replies "prove it," is what's in this package enough? Screenshots without variant selection, timestamps, or URLs are decoration.
Why this matters: violation cascades move in hours, not days. Monitoring frequency sets the ceiling on everything downstream: how fast you detect, whether you can attribute the first mover (Section 7), and whether your notice arrives while the violation is live or after the damage is done.
State your standard monitoring frequency per site type (reseller sites, marketplaces), and the typical latency between a price changing and the violation appearing in our account.
What higher-frequency monitoring tiers exist (hourly, intraday), at what cost, and can frequency be raised selectively: on specific products, resellers, or during specific periods?
What are your monitoring commitments during peak trading periods (Black Friday through Cyber Monday, key category events), when violation pressure is highest? Have you sustained them in prior years, and can you show it?
What alerting do we get when monitoring fails and you are unable to retrieve reseller pricing within your stated SLAs?
How much violation history do we get at signing, and how far back does your archive go for the resellers we care about? Is history included or an add-on?
If monitoring frequency degrades below the committed level for more than 48 hours, how are we notified, and what is the contractual remedy?
Watch for: daily monitoring sold as sufficient for every use case. Daily detection is fine for a disciplined dealer network; it is too slow for marketplace categories where repricers react in minutes, and it limits first-mover attribution (Section 7). The honest vendor will tell you which of your channels need which frequency.
Why this matters: on marketplaces, the violation is only half the finding. "Someone on Amazon is at 40% off" is not actionable; "Storefront X, who also sells these six other SKUs of ours, is at 40% off and has held the Buy Box for three days" is. Enforcement requires a name.
For a violating marketplace offer, what seller details can you provide: storefront name, seller ID, business name and address where the marketplace discloses it, and their other listings of our products?
Can you track a seller's behavior across our catalog over time: which products they list, their pricing pattern, their violation history, and whether they appear and disappear (a common evasion pattern)?
Can you connect a marketplace storefront to a known authorized reseller where evidence supports it, so we know whether a violation is an authorized partner misbehaving or an unknown seller?
How do you track Buy Box dynamics: who holds it, at what price, and how a violating offer affects Buy Box rotation on our listings?
What is your coverage of seller-level data on marketplaces beyond Amazon?
Watch for: seller identification that stops at the storefront name. The valuable layer is the connective one: this storefront maps to this business, sells these twelve products of ours, and started violating on this date. That is the difference between a report and a case file.
Why this matters: when five resellers are all violating, they are not equally responsible. Usually one moved first and the rest followed in self-defense. Enforcement that treats followers like instigators burns channel relationships; enforcement aimed at the first mover fixes the cascade at its source. Attribution is the difference.
For a given violation, can we see a timeline view: when each reseller was compliant, who dropped below MAP first, and which resellers followed, in what order and at what interval?
What monitoring frequency does reliable first-mover attribution require? Be specific about the limits: if multiple resellers drop between two scans, what can and cannot be concluded, and how does the platform communicate that uncertainty rather than guessing?
Can attribution analysis be run across a product family or category, to identify resellers who are repeat first movers across our catalog?
How is forensic analysis surfaced: on-demand per violation, as a report, or as an alert when a cascade pattern is detected?
Is violation forensics included in the platform or priced as an add-on? If add-on, state the pricing model.
Watch for: attribution claims that outrun the data. A vendor scanning daily cannot honestly tell you who moved first within a same-day cascade, and the right answer to 7.2 acknowledges that and offers higher-frequency monitoring for the products where attribution matters. A vendor who claims perfect attribution at daily frequency is selling you a guess.
Why this matters: the resellers you know about are the easy part. Grey market sellers, retailers with no agreement with your sales team who obtain inventory through diversion, are where MAP erosion and brand damage hide. You cannot give a vendor a list of sellers you don't know exist; discovery has to be the vendor's job.
Beyond the reseller list we provide, can you proactively discover unknown sellers with our products in stock and available to buy? Describe how discovery works and how often it runs.
How does discovery separate signal from noise: transactional sites actively selling our products, versus blogs, affiliate pages, review sites, and referral content that merely mention them?
How are discovered grey market sellers identified and segmented in the platform, distinct from our authorized reseller list?
Since grey market sellers have no buyer contact and no agreement with us, the enforcement path differs: what reporting do you provide for our legal team to pursue delisting notices, marketplace takedowns, or cease-and-desist action?
How is discovery priced: is it included, and do discovered sellers count against a contracted reseller limit? What happens commercially when discovery succeeds and finds forty sellers we didn't know about?
Can discovered sellers be promoted into ongoing monitoring, so a grey market site we decide to watch gets the same violation detection as our authorized list?
Watch for: question 8.5 hides a commercial trap. If discovered sellers bill like contracted resellers, the feature's success inflates your invoice, and you will find yourself rationing which unknown sellers you can afford to know about. Get the pricing mechanics of discovery in writing.
Why this matters: this is where MAP programs live or die. Detection without a notice workflow is a dashboard your team screenshots into emails. The workflow questions below determine whether enforcement runs as a system, with escalation, evidence, and audit trail, or as a heroic manual effort that stops the week your wholesale manager goes on vacation.
Can we store enforcement contacts per reseller: the buyers, category managers, and vendor managers our notices should reach, with names, titles, and email addresses?
Describe your escalation framework. Can we configure staged triggers, for example: notice on detection, follow-up if unrectified at 7 days, escalation at 14 days, each with its own template and language our legal team has approved?
Can triggers be conditioned on materiality, such as only violations exceeding a percentage threshold below MAP, so minor mapping errors don't generate notices?
What does a notice contain? Can it attach a structured violation file (each SKU and variant with URL, observed price, MAP price, observation date, and product identifiers) and screenshot evidence with the correct variant shown?
Describe the review model: a queue where our team can review, edit, approve, or reject each notice before it sends, and a full auto-send mode for programs mature enough to run without review. Can review requirements differ by trigger stage?
Can notices send from our own domain rather than yours, so resellers see enforcement coming from us? Describe the options (connecting our Gmail or Microsoft 365, or sending via your infrastructure under our domain) and exactly what our IT team must configure, including email authentication (SPF, DKIM, DMARC).
Do follow-up notices thread onto the original email conversation, so the escalation history is visible to the recipient in one place?
What state does the system keep? For any current violation, can we see whether notices were sent, which trigger stage, when, and how many days have elapsed, directly in the match and violation views?
Can enforcement activity be reported by reseller over time: notices sent, time to rectification, repeat offenses, so we can distinguish resellers who fix things from resellers who wait us out?
Describe any AI-assisted or agentic capabilities in the enforcement workflow: can the system draft notices that adapt to context (a first-time violator versus a repeat offender, violation depth, the seller's rectification history), rather than filling a static template? What controls exist over what the AI can and cannot write in a notice that carries our brand and legal language?
If our own AI agents connect to your platform, what enforcement actions can they take versus only observe: can an agent queue a notice for human approval, and what actions are hard-gated behind human review regardless of configuration?
Watch for: notice workflows that send from the vendor's domain. A violation notice from "alerts@vendor-tool.com" reads as software spam and gets filtered or ignored; the same notice from your brand's domain reads as the channel relationship speaking. If a vendor cannot send from your domain, the workflow's authority is capped. Also confirm 9.5's review gate exists before you ever enable auto-send; automation of a broken or premature notice is worse than no automation. And on 9.10 and 9.11: an agentic notice that no human reviewed is your brand's legal voice on autopilot. Score agentic drafting and human-gated sending together, never one without the other.
Why this matters: MAP tools fail socially before they fail technically. If the wholesale team lives in email and the tool lives in a dashboard, the tool loses. Evaluate fit against how your team actually works today.
How configurable are alerts: by reseller, product set, violation depth, first-time versus repeat, and frequency? Show a real customer's alert configuration.
What noise controls exist: digests, materiality thresholds, deduplication when one reseller violates across many SKUs at once?
What channels do alerts reach: email, Slack, Microsoft Teams, mobile? Can the wholesale lead, legal, and an executive each subscribe to different slices?
Describe roles and permissions. Can we scope what a sales rep sees (their accounts only) versus the wholesale lead versus legal?
What does executive reporting look like: violation trends, resolution rates, recovered-margin estimates, by reseller and over time?
Watch for: ask for alert engagement stats on real accounts. Vendors who track whether alerts get acted on have thought about workflow; vendors who count alerts sent have not.
Why this matters: violation data belongs in the systems where channel decisions happen: your CRM, your BI stack, your planning tools. And as your team adopts AI assistants, whether this data is reachable by them determines if it joins the workflow or stays siloed.
Describe your API: coverage relative to the UI, rate limits, authentication, and documentation. Provide the docs link.
What scheduled export options exist: formats, destinations (SFTP, cloud storage, email), and granularity, down to per-violation records?
Can violation and seller data flow into our CRM, so account owners see the enforcement history of their accounts where they already work?
Describe your AI-assisted capabilities: can a non-analyst ask "which resellers went below MAP on the new collection this week" in plain language and get a correct, current, verifiable answer that cites underlying records?
Do you offer agent-ready access to your data, such as an MCP server or equivalent, so our own AI tools can query it directly? Under what authentication and permission model?
Is our data, or our usage, used to train models that serve other customers? State your policy plainly.
On contract termination, what do we keep? Confirm in writing that we can export our full violation history, evidence archives, match corrections, and configurations in a usable format.
Watch for: evidence archives that are viewable but not exportable. Your violation history is a legal asset that must outlive any vendor relationship; 11.7 belongs in the contract, not just the RFP response.
Why this matters: this platform will hold your MAP policy, your reseller contact lists, your enforcement history, and possibly a connection to your email. That is a sensitive combination. Your security team should own this section, with particular attention to the email-sending integration in 9.6.
Describe your security certifications and audit posture: which certifications you hold today (SOC 2, ISO 27001), which are in progress with dates, and whether recent audit reports or penetration test summaries are available under NDA.
How is our data isolated from other customers? Note that our resellers, or other brands they carry, may also be your customers. Be specific about the isolation model.
For the domain-sending capability in 9.6: describe the security model of the email integration, the scopes requested if connecting our Gmail or Microsoft 365, how credentials are stored, and how the integration is revoked.
Describe encryption at rest and in transit, secrets management, and internal access controls: who at your company can see our account data, and how is that logged?
What SSO and identity options do you support (SAML, OIDC)? Is SSO included or a paid tier?
List your subprocessors and hosting providers, with data residency locations. Describe your incident response commitments and your security incident track record over the past 36 months.
Watch for: treat certification as disclosure, not a pass/fail gate, especially with newer vendors whose engineering may be ahead of their paperwork. What is non-negotiable is a straight answer, and a careful one on 12.3: an email integration with overly broad scopes is a real risk, and a vendor who has thought about it will have a precise answer.
Why this matters: a MAP program has more moving parts at launch than a pricing tool: catalog load, MAP price load, reseller onboarding, contact collection, template approval with legal, and possibly an IT task for domain sending. Who owns each step determines whether you see value in weeks or quarters.
Provide a week-by-week implementation plan: catalog and MAP price ingestion, reseller onboarding, match approval, notice template setup with our legal review, email domain configuration, and user training. Who does each step, us or you?
What is your median time from contract to first violation notice sent, across recent customers of our size?
Describe ongoing support: channels, response time commitments by severity, and hours coverage. Is a named customer success contact included at our tier?
What does the ongoing cadence look like: business reviews, match quality reviews, enforcement outcome reviews? How do you flag when our account is underusing what we bought?
What training exists for new team members after launch, without paid services?
Watch for: implementation plans that leave notice template legal review to the end. Template approval is usually the long pole; a vendor who sequences it early has run real launches.
Why this matters: MAP tooling costs hide in the growth levers: resellers added, discovered sellers monitored, monitoring frequency upgrades, forensics add-ons. Model year-two cost at realistic growth, including the scenario where the tool works and you expand it.
State your pricing model precisely: what units drive cost (resellers monitored, SKUs, marketplaces, monitoring frequency, notices sent), and the price at each break point.
Using the scope attached to this RFP, provide year-one pricing, and then year-two pricing assuming we add ten resellers, upgrade five key resellers to hourly monitoring, and enable seller discovery.
Which capabilities in this RFP are included in the base platform and which are add-ons? Specifically state the pricing status of: violation forensics (Section 7), seller discovery (Section 8), the notice workflow (Section 9), higher-frequency monitoring, and API access.
What are your contract minimums: term length, minimum commitments, and payment terms? What discount applies to annual prepay or multi-year terms?
What are your renewal terms: is there a cap on annual price increases in writing? What is your average net price change at renewal across your customer base?
Are there additional or one-time implementation fees, or is implementation included? Do you have certified implementation partners or is implementation led exclusively by your own teams?
Watch for: per-notice or per-violation pricing. A pricing model that charges you more when resellers behave worse puts the vendor's revenue on the wrong side of your problem. The same logic applies to discovery (8.5): success should not be the expensive outcome.
Why this matters: MAP enforcement produces measurable outcomes: violations found, notices sent, prices rectified, margin recovered. A pilot should produce those numbers on your catalog and your resellers before you commit.
Propose a paid or free pilot structure: duration, scope (SKUs, resellers including at least one marketplace, users), and cost, with a clear conversion path to a full contract.
Agree to these acceptance criteria, or propose alternatives with reasoning:
Who staffs the pilot from your side, and what does a mid-pilot review look like?
If the pilot fails an acceptance criterion, what happens: do we walk away clean, does the pilot extend, or is there a remediation commitment?
Watch for: vendors who accept the pilot but resist the acceptance criteria. The criteria are the pilot. A pilot without pass/fail conditions is a long demo.
Total the weighted scores after all responses and demos are complete. Suggested starting weights: product and variant matching (Section 3), violation detection and evidence (Section 4), and the enforcement workflow (Section 9) at 12 percent each; coverage (Section 2) at 10 percent; monitoring frequency (Section 5) and seller identification (Section 6) at 8 percent each; violation forensics (Section 7), seller discovery (Section 8), and integrations (Section 11) at 6 percent each; alerts and reporting (Section 10) at 5 percent; company overview (Section 1), security (Section 12), and implementation (Section 13) at 4 percent each; commercial terms (Section 14) at 3 percent.
Adjust weights before sending, not after responses arrive. A brand fighting marketplace violations should raise Sections 6 and 7; a brand with a leakage problem should raise Section 8; a brand building its first formal program should raise Section 9.
Section 15 is not scored; it is pass/fail, and it happens with your finalist only.
Evaluating competitive pricing intelligence as well? A sister template covers that category: 14 sections, 85 questions, the same scoring system.
