★★★★★
The automation was set up in a clean and practical way by the Checkout Loom team. It saved me a lot of manual work and made the whole process much easier.
JanoUnited Kingdom
Verified
AI dynamic repricing
AI dynamic repricing for online stores that follows the market without ever selling below your margin floor
AI dynamic repricing for online stores earns its keep only when it is bounded, because a repricer that chases a competitor down a spiral or discounts a product that is about to sell out destroys margin faster than any manual mistake. We build repricing as written rules, with a margin floor and a ceiling for every product, a cap on how far and how often a price may move, respect for minimum advertised price agreements, a price history that keeps your compare-at claims lawful and a log of every change with the rule that caused it.
- Fixed price from $2,350, paid once
- A margin floor and cap on every price change
- A price history that keeps compare-at claims lawful
- Platforms supportedShopify, WooCommerce, BigCommerce and marketplaces such as Amazon, eBay and Walmart through their official APIs.
- Typical storeStores with a hundred to many thousands of products where competitors, stock and demand move faster than a person can follow.
- Signals usedCompetitor prices from licensed data, stock level, sales velocity, margin, season and your own promotion calendar.
- Catalogues coveredOne catalogue per plan, with extra marketplaces, regions and currencies available as priced options.
- OutputsA rule book, repricing workflows, margin floors, a price history, an audit log and a weekly pricing report.
- Live inFour to six weeks for the first rules on a core range and up to ten weeks for several channels.
The costly disconnect
Why manual pricing lags the market and why careless repricing costs more than lag
A store with a few hundred products cannot follow every competitor and every stock level by hand, yet the tools that automate prices can race to the bottom or advertise discounts that were never real, and both outcomes cost more than being a little slow.
Prices that are always a week late
Prices set at launch and reviewed monthly miss every competitor move, every sell-out and every demand spike in between, and the gap is paid in lost sales or lost margin. It is easy to overlook until a busy week exposes it, and by then the cost to online stores is already counted in refunds, hours or lost sales in the dynamic repricing work.
Spirals to the bottom
A repricer that matches the lowest competitor on every product will meet another repricer doing the same, and both stores sell at a loss until someone turns it off. The fix is not more effort but a better rule, and that is exactly what the dynamic repricing build for online stores puts in place.
MAP agreements broken by accident
Brands that set a minimum advertised price expect it to be respected, and a tool that ignores the agreement risks the account with the brand. Many owners only notice this problem when a customer complains, so catching it earlier is one of the quiet benefits of dynamic repricing for online stores.
Compare-at prices that are not true
Showing a crossed-out price that was never the real price is a pricing claim problem in many countries, and the EU’s rules expect the lowest price of the previous thirty days to be shown when a reduction is announced. Left alone, this problem repeats with every order, which is why dynamic repricing for online stores is built to handle it by rule and not by memory.
Feeds that disagree with the page
Google Merchant Center disapproves products whose feed price differs from the landing page, so a price change that reaches one and not the other costs visibility. It is easy to overlook until a busy week exposes it, and by then the cost to online stores is already counted in refunds, hours or lost sales in the dynamic repricing work.
Rules nobody can explain
A repricer’s own settings are rarely documented, so when a price looks wrong nobody can say which rule produced it. The fix is not more effort but a better rule, and that is exactly what the dynamic repricing build for online stores puts in place.
- 30 daysis the look-back period under the EU’s Omnibus rules for the lowest prior price that must be shown with a price reduction.
- 100%of changes in our builds stay above the floor and inside the cap, and every change is logged with its rule.
- +3.4percentage points of margin is a typical improvement against plan in the first quarter, which is indicative and varies by category.
Sources: EU Directive 2019/2161 on price indication for reductions; Google Merchant Center price mismatch policy; margin figures come from catalogues we have worked with and are indicative.
What changes in your pricing once rules replace guesswork and a floor protects every sale
Prices follow the market and your stock inside limits you set, and every change can be explained.
How pricing runs today
- Prices are reviewed monthly by hand.
- A repricer’s rules are opaque.
- Competitor moves cause spirals.
- MAP and compare-at rules are checked by eye.
- Nobody can explain a price.
How pricing runs afterwards
- Prices move daily by written rules for competitor position, stock and demand.
- Every rule is in a rule book you can read and edit.
- A floor, a ceiling and a cap stop spirals and extreme moves.
- MAP prices are enforced, and price history supports lawful compare-at claims.
- Each change is logged with the rule and the data behind it.
What the pricing report shows
- Margin protected on every sale.
- Faster response to the market.
- No pricing spirals.
- Fewer legal and brand risks.
- Prices you can explain.
What the rules adjust
- Reading competitor prices, stock and sales velocity every day.
- Applying the rule for each product within its floor, ceiling and cap.
- Enforcing minimum advertised prices and promotion calendars.
- Writing prices to the store and feeds together.
- Recording every change with the rule, the data and the previous price.
What a pricing owner decides
- Setting floors, ceilings and caps.
- Strategic price positioning by category.
- Approving exceptions and promotions.
- Reviewing the weekly report.
- Responding to brand or supplier price rules.
Which online stores gain most from dynamic repricing
If competitors change prices faster than you can follow, or stock levels swing, bounded repricing recovers margin and sales that manual review leaves behind.
Stores in competitive categories
Electronics, beauty and sports goods see frequent moves, and a rule that responds within limits protects both sales and margin. If this describes your business, the dynamic repricing work for online stores is likely to pay back quickly, and we will tell you plainly if it will not.
Marketplace sellers
Buy Box and listing position respond to price, and repricing within a floor keeps you competitive without selling at a loss. Owners in this position often say the biggest change is the time returned each week, and dynamic repricing is built to deliver that first for online stores.
Stores with fast-moving stock
Prices that rise as stock thins and fall for overstock reduce lost margin and dead inventory. This is the kind of situation where a fixed-price build is easier to justify than a monthly subscription for dynamic repricing for online stores.
Stores with thousands of products
No team can review every price, and rules scale where people cannot. We look at this situation in the audit and give online stores an honest view of whether the build is worth doing now or later in the dynamic repricing work.
Stores with several currencies
Rules apply consistently with rounding and currency conversion built in. If this describes your business, the dynamic repricing work for online stores is likely to pay back quickly, and we will tell you plainly if it will not.
Brands with MAP agreements
Rules enforce the agreement automatically and show proof of compliance. Owners in this position often say the biggest change is the time returned each week, and dynamic repricing is built to deliver that first for online stores.
The data events that trigger each repricing decision
Repricing runs on a daily schedule and on events such as stock changes, and every run follows the same ordered rules.
competitor_price_updatedA competitor price changes
The new price enters the rule for that product, which decides whether any response is needed. The event is logged with the rule that handled it, which lets you check later exactly what dynamic repricing did for online stores and why it did it.
inventory_levels/updateStock level changes
Low stock can raise a price within the cap, and overstock can lower it within the floor. Because this trigger is handled separately from the others, a problem with it never delays the rest of the dynamic repricing work for online stores.
sales_velocity_shiftDemand moves
A sustained rise or fall in sales speed triggers a review of the price against the rule. You decide how much of this runs without approval, and for online stores we usually begin with a review step until the first results look right in the dynamic repricing work.
promotion_startedA promotion begins or ends
The promotion calendar overrides rules for the covered products and restores them afterwards. Anything this trigger cannot decide safely is passed to you with the record attached, so dynamic repricing for online stores never acts on a doubtful reading.
price_appliedA price is applied
The new price is written to the store, the feeds and any marketplace, with the old price saved. We test this moment on your own records before launch, so the dynamic repricing build for online stores has met it before it meets a real customer.
floor_hitA floor is reached
The price stops, the product is flagged for review and no further reduction is applied. The timing of this step is written down in the rule table, which means you can change when it happens without asking us to rebuild anything in the dynamic repricing build for online stores.
One product followed from a competitor’s price drop to a bounded response
This shows how a rule reads the market, respects the limits and records the decision.
- 01
A competitor drops its price
The daily data run shows a competitor has cut the price of a popular backpack by seven percent, below yours. Because the steps are separate, a change to one of them, such as a new rule for online stores, does not disturb the others in the dynamic repricing flow.
- 02
The rule is read
The rule for this product says to match competitors within a three percent move, never go below a twenty-two percent margin and never change more than once a day. The same step is repeated for every item in the batch, so the tenth record receives the same care as the first when dynamic repricing runs for online stores.
- 03
The limits are applied
The full seven percent move would breach the floor, so the system calculates the largest price that keeps the margin and stays within the cap. Anything unusual at this point is flagged in plain words, which saves you from reading logs to understand what the dynamic repricing work found for online stores.
- 04
The price is written
The new price is written to the store and to the Google feed together, so the landing page and the feed match. At the end of this stage you can pause, adjust a rule or carry on, so dynamic repricing for online stores always moves at the pace that suits you.
- 05
History is recorded
The old price, the new price, the rule, the competitor data and the time are saved, and the lowest price in the last thirty days is updated for compare-at use. Every step like this is recorded, so the dynamic repricing work for online stores can be traced from the first input to the final result without any gaps.
- 06
The result is reviewed
The weekly report shows the sales and margin effect of the change, and a person can raise the floor or tighten the rule. If the step cannot finish, the record says why and waits for you, so dynamic repricing for online stores never moves on with a half-completed task.
Pricing
Price your AI dynamic repricing
Choose a plan, tell us your catalogue size and channels, and add any extras, and the total and live date update as you go.
What AI dynamic repricing costs and what raises the price
Our fee is fixed and paid once, while competitor data subscriptions, workflow tools and model usage are billed by their own providers.
Catalogue size and groups
More products and more distinct rule groups mean more tests. Changes to this factor after the quote are handled as a written change, with its own price, and never as a hidden charge on dynamic repricing for online stores.
Channels and currencies
Each marketplace and currency adds APIs, rounding and checks. A smaller first build can leave this factor for later, and online stores can add it at a priced step once the first results are in in the dynamic repricing work.
Competitor data needs
Wider competitor coverage raises the data subscription and the matching work. The tools around dynamic repricing bill separately, and we estimate their monthly cost for this factor so your running cost is known as well as the build for online stores.
MAP and brand rules
Many brand agreements add enforcement rules and reports. Owners who run dynamic repricing for online stores often find this factor is the one that most changes the quote, which is why we ask about it first.
Approval workflow
Several approvers and exception rules add configuration. We check this factor against your real records during the audit, so the number in the quote comes from your data and not from a guess in the dynamic repricing build for online stores.
Existing repricer
Wrapping an existing tool adds integration work. This is one of the factors we price in writing before work starts, so the dynamic repricing quote for online stores reflects your real situation and not an average.
Competitor data, repricer and workflow tool subscriptions are billed by those providers.
Next step
Ready to price AI Dynamic Repricing for Online Stores?
AI dynamic repricing for online stores changes prices by written rules, such as competitor position, stock level, demand and margin floor, applies them in capped batches, keeps a price history so compare-at claims stay lawful and logs every change, so prices follow the market without ever dropping below what a sale is worth.
- One fixed price from $2,350, paid once
- A floor and a cap on every change
- A price history for lawful compare-at claims
Three more pricing jobs the same engine can do
Once rules, floors and history exist, related pricing work follows.
Sale and clearance pricing
Clearance prices step down on a schedule, never below the floor, with a lawful price history. If the job does not pay back, it can be switched off without affecting the rest of the dynamic repricing build, and nothing needs to be unpicked for online stores.
Currency and rounding rules
Prices in each market round to local conventions and follow exchange rates within a stated cap. The wording and the limits for this job come from the same rule table as the main dynamic repricing work, so one change updates both for online stores.
Bundle and tiered pricing
Bundles and volume tiers are repriced consistently when their components change. Teams that run dynamic repricing for online stores usually add this once the first batch has settled, because by then the data behind it is already clean.
Which data the repricing rules read and where each fact is the source of truth
Repricing is only as safe as its inputs, so each one has an owner and a freshness check.
| Store object | Fields we use | Direction | Source of truth |
|---|---|---|---|
| Cost and margin | Landed cost, fees, margin floor | Read only | Cost sheet you own |
| Competitor prices | Price, seller, date, stock status | Read daily | Licensed data provider |
| Stock and velocity | Quantity, sales per day | Read daily | Store and orders |
| Rules | Floor, ceiling, cap, strategy | Read before every run | Rule book |
| Prices | Current price, previous price, date | Written after approval | Store and feeds |
| Price history | Every price and the lowest in thirty days | Written on every change | Price history log |
Competitor data comes from licensed providers or official APIs, and each reading carries its date, so a stale reading is never treated as current.
Edge cases in dynamic repricing that we test before launch
Price automation fails at the extremes, so we test the extremes before a single live price moves.
Competitor errors and glitches
A competitor price that is wildly low or high is treated as a likely error and ignored until it is confirmed. Nothing about this case is hidden from you: it appears in the log with the date, the record and the rule that dealt with it in the dynamic repricing build for online stores.
MAP and brand agreements
Products under a minimum advertised price are never priced below it and are logged as compliant. We list the cases that matter most for dynamic repricing in your handover guide, so anyone on your team can understand how online stores deals with them.
Two repricers chasing each other
A daily change cap and a floor stop a spiral, and a repeat pattern raises an alert. A rule for this case can be tightened or relaxed in minutes in the rule table, without waiting for a rebuild or a new quote in the dynamic repricing build for online stores.
Currency and tax display
Prices are rounded and tax-inclusive or exclusive according to each market’s convention. Handling the case early protects the margin and the reputation of online stores, which is worth more than the hours it takes to write the rule in the dynamic repricing work.
Feed and page mismatches
Prices are written to the store and the feeds in one step and checked for a match afterwards. We test this case before launch on your own records, so dynamic repricing for online stores has met it before it meets a real customer on a busy day.
Promotions and bundles
Promotion calendars override rules and restore them cleanly, and bundles follow their components. When the case appears, the workflow follows a written rule and records the choice it made, so you can review it afterwards if you wish in the dynamic repricing build for online stores.
Manual pricing, a marketplace repricer and a built repricing engine compared
Manual pricing is careful and slow, a marketplace repricer is quick and opaque, and a built engine runs your own rules across your store and marketplaces with floors, history and logs.
| Manual pricing | Marketplace repricer | Checkout Loom build | |
|---|---|---|---|
| Follows the market daily | – | ✓ | ✓ |
| Floor and cap on every product | Partly | Partly | ✓ |
| MAP enforcement | Partly | Partly | ✓ |
| Price history for lawful compare-at claims | – | – | ✓ |
| Rules you can read and explain | ✓ | – | ✓ |
| Cost pattern | Staff time | Monthly plan by listings | Our build fee plus data costs |
We keep an existing repricer where it fits and wrap it with floors, history and logs when its own controls are thin.
How the repricing engine is built and what each part costs
We use licensed data and official APIs and show the monthly cost of each part beside our fixed fee.
A competitor data source
A licensed provider such as Prisync, Price2Spy, Competera or Keepa for Amazon, chosen for your catalogue and budget. We test the layer on your own data before launch, so dynamic repricing for online stores is proven on real records and not on tidy examples.
A rule engine
Written rules for each product group, held as a rule book and applied by a workflow with floors, ceilings and caps. If the layer fails or changes its terms, the handover guide explains how to swap it, so online stores is never stranded by one supplier in the dynamic repricing work.
Store and marketplace APIs
Shopify GraphQL price updates, WooCommerce REST and Amazon, eBay and Walmart price feeds, paced within each limit. Its role is written in plain language in the handover guide, which means a new team member at online stores can understand it in a few minutes in the dynamic repricing work.
A price history log
Every price, date and rule saved, including the lowest price in the last thirty days. The monthly price of this layer is written next to our fixed fee before you commit, so the true cost of running dynamic repricing for online stores is clear from day one.
A review screen
Products at a floor, large moves and exceptions listed with the data for a person to review. You can replace this layer later with another tool, because the rules live in a table you own and are not locked inside any one product in the dynamic repricing build for online stores.
Make, Zapier or n8n
The workflow layer that runs the daily job, retries failures and writes the log. We choose the lightest option that does the job for online stores, since a simpler layer means fewer things to maintain and fewer ways to fail in the dynamic repricing work.
How we keep repricing safe on a live store
Because prices touch revenue directly, safety comes from limits, rehearsal and a way back.
Floors and caps enforced in code
No rule can write a price below the floor or beyond the cap, whatever the data says. Everything the safeguard decides is written to the log with the reason, giving online stores a trail that is useful when someone asks what happened and why in the dynamic repricing work.
Rollback
The previous prices are stored, and a bad run can be reversed in one step. During the month of corrections after launch, any gap in this safeguard is fixed in writing and the fix is added to the handover guide in the dynamic repricing build for online stores.
A shadow run first
Rules run for a period with no price written, so you can compare their decisions with what you would have done. Reports on how often the safeguard fires show online stores whether the dynamic repricing work is getting steadier or whether a rule needs attention.
Alerts for unusual moves
A large change, a repeated spiral or missing data raises an alert with the product and the rule. Because this protection is written as a rule and not as a habit, it keeps working when staff change or the business gets busier in the dynamic repricing build for online stores.
Freshness checks
A reading older than your limit is ignored and flagged. When something goes wrong in dynamic repricing for online stores, the failure is named, retried within safe limits and listed for you, instead of vanishing into a log nobody reads.
Plain explanations after setbacks
If a price goes wrong, the owner explains in writing what happened and the limit that now prevents it. This safeguard runs on every batch and not only on a schedule, so a problem in dynamic repricing is caught before it can spread to the next record for online stores.
Competition law, data licences and permissions in repricing
Pricing touches competition rules and data terms, so we keep to public data and avoid anything that coordinates with competitors.
Least-privilege access
We request price and inventory scopes only, and write access limited to price fields. Nothing in this arrangement requires you to share a password, because access is granted from your own account in a form you can revoke in the dynamic repricing build for online stores.
No coordination with competitors
Rules react to public prices only and never share your prices or plans with any competitor. We keep no copy of your keys, records or customer details in systems that belong to us, and the handover guide shows you how to confirm that in the dynamic repricing build for online stores.
Keys in your accounts
Store, marketplace and data keys sit in your accounts and can be revoked at any time. Only the fields that dynamic repricing needs are read, and only for as long as the task takes, which keeps the exposure for online stores as small as it can be.
Licensed data only
We use licensed providers and official APIs, and we do not scrape sites in breach of their terms. Every access is logged in your own accounts, so you can see who or what touched a record and when, without asking us for a report in the dynamic repricing build for online stores.
Cost data kept private
Cost and margin data never appears on a page or in a feed. If a key is ever lost, it can be replaced in minutes without rebuilding the dynamic repricing work for online stores, because the rules do not depend on it.
Pricing access closed at the end
You receive a list of every price connection and data feed we set up, and our own access is switched off when we finish. The arrangement is reviewed at the end of the month of corrections, and any access that is no longer needed is removed in writing in the dynamic repricing build for online stores.
What you receive with your AI dynamic repricing
Each plan ends with written rules, a protected engine and a record of every price.
- A rule book with a strategy, floor, ceiling and cap for every product group.
- A repricing workflow that runs daily and on stock and demand events.
- Minimum advertised price enforcement and a promotion calendar.
- Price writes to your store and feeds together, with a match check.
- A price history with the lowest price in the last thirty days for lawful compare-at claims.
- A shadow-run report comparing rule decisions with your own.
- A review screen for floors reached and large moves.
- A weekly pricing report on sales, margin and exceptions.
- A month of corrections after live repricing begins.
Verified client reviews and the safeguards behind our repricing builds
The unedited words of verified clients of the Checkout Loom team appear below, followed by the safeguards every repricing build includes.
- 100%of price changes stay above the floor and inside the cap.
- 1shadow run precedes live repricing, so rules are judged on a record before they touch revenue.
- 30 daysof corrections follow the first live run so the rules settle before we step back.
Safeguards follow pricing practice guidance and platform documentation and are confirmed again at build time.
★★★★★
I highly recommend ordering from the Checkout Loom team. I had slow responses and poor communication with other providers, but this team was great and I am very happy with their service.
HarmetUnited States
Verified
★★★★★
I am a returning customer because my first AI automation workflow worked so well. Once again everything was built exactly as requested, and the whole process was reliable from start to finish.
WilliamUnited States
Verified
★★★★★
The determination and commitment to quality from the Checkout Loom team were clear from day one. They understood my requirements perfectly and completed everything with professionalism and care, and it is rare to find a team this dependable.
LorcanColombia
Verified
★★★★★
It was an excellent experience from start to finish, and the automation works reliably with everything configured properly. It is clear that the team has strong knowledge of automation, and I will definitely be returning for future work.
EllieUnited States
Verified
★★★★★
The team carefully investigated the problem, tested different scenarios and delivered a dependable solution. A duplicate contact issue had been causing problems for quite some time, and it is finally resolved.
RichardUnited States
Verified
★★★★★
The Checkout Loom team were easy to work with and brilliant at the work itself. I highly recommend them to anyone who needs dependable automation.
IveraAutomation client
Verified
★★★★★
Everything was configured exactly as discussed, and the team made sure the automation was stable before delivering it. It has been a huge time-saver for our whole team, and it runs without any manual work.
BellamyUnited States
Verified
★★★★★
This was excellent automation work, and it is clear that the team has strong experience with AI and automation. I highly recommend the Checkout Loom team to other businesses.
FinnUnited States
Verified
How the repricing build runs from margin audit to supervised live pricing
We learn your margins and your constraints before we write a single rule.
- 01
Audit costs and margins
We collect costs, fees and current prices, calculate real margins and list products with MAP or brand constraints. We use plain language in every document from this step onward, so anyone at online stores can read the plan and understand it in the dynamic repricing work.
- 02
Write the rule book
We agree the strategy, floor, ceiling and cap for each product group in writing. A short summary of the step is added to the handover guide, so the way dynamic repricing was built for online stores is never lost.
- 03
Connect data and stores
We connect licensed competitor data, stock and your store and feeds with the narrowest access. You see the result of this step in writing before the next one begins, which keeps the dynamic repricing build for online stores on schedule and under your control.
- 04
Run in shadow mode
We run the rules for a few weeks without writing prices and compare their decisions with yours. If this step shows a problem, we say so at once and propose the fix, and the date for dynamic repricing is moved in writing rather than quietly for online stores.
- 05
Go live in stages
We switch on repricing for one group at a time, watching sales and margin. Nothing in this step touches your live customers, so online stores can review it calmly and ask for changes before anything goes public in the dynamic repricing work.
- 06
Hand over
You keep the rule book and the price log, receive thirty days of rule corrections and see our access removed. The step has a clear finish line, which means you always know whether the dynamic repricing work for online stores is on time or running behind.
Estimate what bounded repricing could add to your margin
Enter your revenue and the margin change you expect and the estimate shows the extra gross profit, using figures you can change.
Gross profit each month today–
Gross profit each month with repricing–
Extra gross profit each year–
The estimate adds the margin improvement and the sales lift together, both are cautious, and results depend on your category and competitors.
AI dynamic repricing questions, answered in full
These are the questions store owners ask about rules, margins, legality and cost before they order dynamic repricing.
What is AI dynamic repricing for online stores?
It is a system that changes product prices by written rules, using competitor prices, stock, demand and margin, within a floor, a ceiling and a daily cap, writing the new prices to your store and feeds and logging every change with the rule behind it.
What is the difference between dynamic repricing and dynamic pricing?
Dynamic repricing usually means adjusting an existing price in response to market signals within limits, whereas dynamic pricing can mean setting prices per customer or moment, which raises extra fairness and legal questions. We build bounded, transparent repricing and not personalised prices.
How do you stop a price war from wrecking my margin?
Every product has a margin floor, a ceiling and a cap on how far and how often a price may move, a spiral is detected and raises an alert and a person can adjust the rule.
Is dynamic repricing legal?
Adjusting your own prices to public information is generally lawful, but coordinating prices with competitors is not, and compare-at claims have their own rules, so we use only public data, never share your prices and keep a price history that supports lawful reduction claims.
What about minimum advertised price agreements?
Products under a MAP agreement are never priced below the agreed price, and the engine logs each product as compliant so you can show the brand a record.
Will compare-at prices stay lawful?
We keep a price history and compute the lowest price over the previous thirty days, which is what the EU’s Omnibus rules expect with a price reduction, and we show compare-at prices only when they are supported by that history.
How do you keep my feed and my page prices matching?
Prices are written to the store and the feeds in one step and checked for a match afterwards, because Google Merchant Center disapproves products whose feed price differs from the landing page price.
Can I see what the rules would do before they go live?
Yes, we run them in shadow mode for a few weeks with no price written, and compare their decisions with what you would have done before any live price moves.
When can repricing go live and what do you need from me?
The first rules are usually live in four to six weeks, after the shadow run. We need your cost data, current prices, any MAP agreements, store and marketplace access and a competitor data source or permission to choose one, and we send a written checklist after you order.
What will competitor data and tools cost me each month?
Our fee is charged once, while competitor data subscriptions, workflow tools and model usage are billed by their providers, and we estimate the monthly total for your catalogue before you decide.
Let prices follow the market inside the limits you set and never below your floor
Choose a plan in the pricing calculator and continue to checkout, or request a quote with your store address, your channels and the number of products. We reply in writing within one working day with a confirmed start date and a short checklist, so the margin audit begins at once.
- One fixed price from $2,350, paid once
- A floor and a cap on every change
- A price history for lawful compare-at claims