For Shopify eCommerce in Spain and the EU

Protect your brand with smarter discounts

A blanket coupon does not only cost you the margin of everyone who was going to buy anyway. It costs you something that shows up in no report: it teaches your whole customer base to wait for the next one.

The shopper who receives the adjustment sees it explained. The market never sees it at all.

Never above your catalogue price
No coupon, no banner, no code doing the rounds
Who sees the adjustment
Four visits to the same product, on the same day. Illustrative example.
Arrives at the home page and browses €129.00
Comes in from a generic search €129.00
Filtered “up to €120” and the product is overstocked €116.10
The collection listing, for everyone €129.00
Only the third one sees the adjustment, and she sees it with the reason written beside it. There is no code to forward, it appears in no campaign, and nobody else learns to wait for it.

Two engines that protect your margin and your brand from different angles

IBP installs as a Shopify app. It touches no product you have not configured, and you set the thresholds — we give you visibility over the information you need to set them.

Engine A

Inventory discount, behind an intent gate

It lives inside the shopper’s session and only goes down. It is a two-key lock, and both keys are required:

Stock is the condition. It decides whether there is a discount, and how much.
Intent is the trigger. It decides who gets through: only a shopper who declares a budget, by filtering on price or typing it into search.
Your stockDiscount
Last few units80% of your cap
Excess that needs to moveYour full cap
Inside its stable bandNone
Live in production
Engine B

Catalogue adjustment on scarcity

When a fast-moving product is running low, it raises the catalogue price by a bounded percentage that you set, and reverses it on its own when you restock.

It is an inventory rule. You set the threshold and the percentage; the engine checks a quantity and applies it when the rule is met.

Live in production, full cycle verified
They combine across a catalogue, SKU by SKU, and they never stack on the same product. A product on a scarcity strategy is excluded from the discount engine, so that nobody ever receives a catalogue adjustment and a session discount at once — that would produce a compound price nobody could explain. And the stable band, which in most catalogues is the bulk of it, is left alone: a pricing engine that acts all the time is a permanent coupon under another name.

The others help you lower your price. IBP helps you not lower it more than necessary.

The market is full of apps that hand out coupons and engines that chase a competitor’s price. Both push toward the same price war, and everybody sees both.

Discount apps Competitor-based pricing IBP
Looks atEvery shopperThe price next doorThis session’s demand and your warehouse
Who sees itThe whole marketThe whole marketOnly the person who gets it
Effect on your brandTrains it to waitNone directlyNone: it creates no expectation
Effect on your marginSpreads it aroundChases it downwardDefends it
Proof that it worksNoneNoneA measured control group

Five figures, and one of them is a limit

The dashboard is not a billing screen. It is where you see what is happening to your margin and what you can do about it. The figures are never added together: these are mechanisms with different logic, and a single total would hide where the value comes from.

How much have I stopped giving away?

Margin defended

The times the engine had calculated a discount and did not apply it, because the shopper had already declared a budget that covered the price — and the sale closed anyway.

How many sales would I not have had?

Sales recovered

Measured against a real control group: a share of sessions where the engine decides exactly as it would and withholds the discount. It is the only thing that legitimises our commission, and until the sample is large enough the dashboard says it is still measuring rather than handing you a number.

What did scarcity give me?

Additional margin captured

What the catalogue adjustment contributed on the products where you switched it on, kept separate from the figure above because its logic is different.

How many people left over price?

Unserved demand

Shoppers who declared a budget below your floor and walked away — and how far short of closing each one was.

Is this getting out of hand?

Shoppers who got a discount

A counter-metric, on the first screen on purpose: it should be low and it should not climb. If it climbs, IBP is starting to behave like a coupon — and we would rather you saw that before we did.

Only IBP sees this

The demand that appears in no report

Your Shopify reports tell you what sold. Nobody tells you how many people looked at your product, said what they were willing to pay, and left.

IBP is in the session before the purchase, so it does see them. And it tells you exactly by how much each one got away.

If you hold your price on purpose, this is your figure: it is the only way to know whether that decision is costing you more than it protects.

Aggregated and anonymous by construction: no category is ever shown with fewer than 25 sessions, budgets are grouped into bands, and the text the shopper typed is neither stored nor shown.
Illustrative example
Categoryhoodie
Sessions that left218
Declared budget, median€45.00
Your floor price€49.00
Distance to closing€4.00

We measure and propose. You decide.

We never touch your price on our own

We do not see your margins, so we cannot know whether losing a sale suits you better than closing it cheaply. Only you know that. We give you the figure and the proposal; you authorise it or you do not.

Every decision can be reconstructed

The same conditions always produce the same price, and the reason it did or did not act is recorded. If a shopper asks, there is an answer.

The shopper always knows

The adjustment is shown on the product page with its reason, in your store’s language. It is never a hidden discount nor a silent increase, and it never exceeds your catalogue price.

The test is not whether you discount today

It is whether you are under price pressure and do not want to become a discount brand. That is three different situations, and in all three the problem is the same.

1

You discount a lot and want to stop

Coupons, seasonal campaigns, welcome codes. You know what you give away and not who to. We start by measuring exactly that.

2

You discounted, and you pulled back

It worked on sales and it hurt the brand, so you put the lever away. You put it away because the only version you knew was a public one.

3

You refuse to discount, and lose sales holding the line

For you IBP is not a cheaper way to discount: it is the only way to do it without paying the brand price. And unserved demand finally tells you what holding that line costs you.

The requirement that really binds: inventory that leaves its range

Stock is the engine’s condition, so a merchant with no inventory problem — made to order, digital goods, pure dropshipping — has every product sitting in the stable band, and today IBP does nothing at all for them.

We would rather say so in the first meeting. It is awkward, and it is far cheaper than finding out in week three of a pilot where nothing is broken: nothing simply happens.

Fashion and footwear Consumer electronics Home and decor Sports
And the arithmetic that disqualifies, which we show you too
30% margin, 20% discount+200% conversion
55% margin, 10% discount+22% conversion
That is how much your conversion would have to rise just to break even. Two questions — your gross margin, and what discount it would take — tell us whether IBP can work in your case. If the arithmetic says no, we say so.

Two ways to start, depending on where you are coming from

If you discount: from your last ninety days of orders we tell you what share carried a discount, how deep it went, and what that is worth in margin. Nothing to install. If you do not discount: we install IBP in measure-only mode and show you the demand you are losing on price, before touching a single product.

Or just write to us at eus.vazquez@ibpintelligence.com