Growth / Built and operated

We build solutions that help your business grow.

We connect your data, take care of the manual work and give your team a clearer way forward. Built around how your business works.

Explore our projects
Connected data. Less manual work. More room to grow.Built around your business.

How we help

Good data.
Put to work.

When people spend their time gathering information, there is less time to act on it. We build a better way to get the work done.

01

Connect the data.

Bring the information from your existing systems together.

02

Do the work.

Use calculations, algorithms or AI to handle the checks and analysis your team repeats.

03

Make it useful.

A recommendation, one shared report, or an update straight into the tools you use.

Projects we’ve built

What that looks like
in practice.

Pricing and reporting are two examples. We start with the problem in your business and build the solution around it.

Pricing

Competitive prices. Protected margins. Across your store.

Your competitors change prices. Stock ages. Demand shifts. Keeping an entire store competitive while protecting margins takes more than manual price checks.

Pricing / Competitive prices. Protected margins. Across your store.Scripted example · Fictional data

Competitive prices. Protected margins.

Reprice the whole store as the market, stock and demand change.

Competitive prices and margin control across the store. Automatically updated, or ready for your team to approve.

Read the full example
  1. Reprice the whole store.

    A multi-brand retailer needs to stay competitive and protect margins across its catalog. Competitor sales, product costs, demand and stock keep changing. Checking and changing every price manually cannot keep pace.

  2. Connect the evidence.

    We connect competitor prices, product costs and margins, stock levels, marketing costs, product lifecycle and on-site behavior. Conversion rate, basket value and the order in which products enter a basket add context to the same product record.

  3. Apply the business’s own rules.

    The engine matches the evidence by product and applies the commercial team’s margin rules, price limits and exceptions before calculating a price. Missing or uncertain evidence can be sent for review. The following retail prices are fictional examples, not client results.

  4. Follow a competitor’s sale.

    The trail shoe currently sells for €120. A competitor starts a sale at €108. Within the agreed margin rules, the engine proposes €108 so the store remains competitive. Matching a competitor is a commercial choice, not a rule to cut every price.

  5. Test more margin on a basket add-on.

    The socks currently sell for €24 and are usually added second or third to the basket. That suggests they may be an add-on rather than the product that brings in the shopper. The engine proposes €27 as a price to test. Add-to-cart order alone does not establish price sensitivity; the team checks conversion, basket value and contribution before retaining the change.

  6. Help clear ageing stock.

    The seasonal jacket currently sells for €100, while a competitor sells it for €80. Lifecycle and stock data show remaining seasonal inventory. The engine proposes €76: €80 × 0.95, or 5% below the competitor, subject to the business’s margin rules. The aim is to move old stock; sell-through is not guaranteed.

  7. Choose how prices reach the store.

    Each product keeps its proposed price and reason. The business can automatically publish changes within approved rules, or send them to the commercial team for manual review and approval. People own the rules and exceptions. Competitive pricing and margin control become repeatable across the store.

Pricing

Competitive prices. Protected margins. Across your store.

Your competitors change prices. Stock ages. Demand shifts. Keeping an entire store competitive while protecting margins takes more than manual price checks.

Scripted example · Fictional dataScripted example · Fictional data
Pricing / Competitive prices. Protected margins. Across your store.
Store-wide goalStay competitive and protect margins
Connected evidenceCompetitors, costs, stock, marketing, lifecycle and basket behavior
Follow a saleTrail shoes: €120 → €108 · competitor €108
Test more marginSocks: €24 → €27 · usually added second or third
Clear ageing stockSeasonal jacket: €100 → €76 · 5% below competitor €80
Your delivery choiceAutomatic store updates or commercial-team review

Competitive prices and margin control across the store. Automatically updated, or ready for your team to approve.

Read the full example
  1. Reprice the whole store.

    A multi-brand retailer needs to stay competitive and protect margins across its catalog. Competitor sales, product costs, demand and stock keep changing. Checking and changing every price manually cannot keep pace.

  2. Connect the evidence.

    We connect competitor prices, product costs and margins, stock levels, marketing costs, product lifecycle and on-site behavior. Conversion rate, basket value and the order in which products enter a basket add context to the same product record.

  3. Apply the business’s own rules.

    The engine matches the evidence by product and applies the commercial team’s margin rules, price limits and exceptions before calculating a price. Missing or uncertain evidence can be sent for review. The following retail prices are fictional examples, not client results.

  4. Follow a competitor’s sale.

    The trail shoe currently sells for €120. A competitor starts a sale at €108. Within the agreed margin rules, the engine proposes €108 so the store remains competitive. Matching a competitor is a commercial choice, not a rule to cut every price.

  5. Test more margin on a basket add-on.

    The socks currently sell for €24 and are usually added second or third to the basket. That suggests they may be an add-on rather than the product that brings in the shopper. The engine proposes €27 as a price to test. Add-to-cart order alone does not establish price sensitivity; the team checks conversion, basket value and contribution before retaining the change.

  6. Help clear ageing stock.

    The seasonal jacket currently sells for €100, while a competitor sells it for €80. Lifecycle and stock data show remaining seasonal inventory. The engine proposes €76: €80 × 0.95, or 5% below the competitor, subject to the business’s margin rules. The aim is to move old stock; sell-through is not guaranteed.

  7. Choose how prices reach the store.

    Each product keeps its proposed price and reason. The business can automatically publish changes within approved rules, or send them to the commercial team for manual review and approval. People own the rules and exceptions. Competitive pricing and margin control become repeatable across the store.

A project we’ve delivered~30,000

active products, across five stores

A Nordic multi-brand e-commerce group

From manual price checks to an hourly update.

The situation

At a Nordic multi-brand e-commerce group, the team checked competitors manually. Keeping prices current across five stores meant repeating the same work.

What we built

We brought competitor prices, product costs, stock and sales data into one system. It applies the agreed pricing rules, including when to hold a price or move a product into outlet.

What changed

The catalog is now checked every hour. The team gets prices ready to use and a clear list of the products that need a commercial decision.

What it takes

We start with your team.

We start with the data you already have, the way your team sets prices and the rules that matter to your business.

What stays human

The judgment stays with people.

Your team sets the rules and approves changes that need judgment. We make the routine checks, explain the recommendation and bring exceptions back to people.

Commercial reporting

One business. One shared view.

Sales, finance and marketing each have part of the picture. We connect them so your team can see the whole business — and each product — in one place.

Scripted example · Fictional dataScripted example · Fictional data
Commercial reporting, brought together.
TodayExports and separate dashboards
What we buildConnected data + agreed calculations
What you getOne shared view of the business

See the business and each product in one place, without rebuilding the report every time.

Read the full example
  1. Today: the picture is scattered.

    Sales, finance, marketing, stock and returns sit in separate systems. The team exports data, compares dashboards and rebuilds the picture in a spreadsheet. That makes it hard to see the full profit-and-loss or understand a product’s performance.

  2. We bring the numbers together.

    We connect the sources, match the records and make the calculations. We agree the definitions with your team so the reporting reflects how the business works. The business view and product detail share the same source of truth.

  3. One place to see what is happening.

    At business level, the team sees sales, costs and the full profit-and-loss. At product level, channel clicks, impressions and advertising spend sit alongside sales, discounts, costs, returns and what is left. The team can follow trends without pulling together separate dashboards. People own the definitions and decisions.

A project we’ve deliveredOne view.

from the business P&L to each product

A Nordic multi-brand e-commerce group

The team stopped assembling the picture by hand.

The situation

At a Nordic multi-brand e-commerce group, reporting meant pulling exports from different systems. Teams calculated the same numbers in different ways.

What we built

We connected sales, marketing and finance data, agreed the calculations and built one daily reporting view. The business P&L and the product detail use the same numbers.

What changed

The team can see sales, costs and what is left in one place. Following the numbers down to individual products also exposed an error that had been hidden in the previous reporting.

What it takes

We start with your team.

We start with your existing reports, the questions they should answer and access to the systems behind them.

What stays human

The judgment stays with people.

People agree what each number means. We align the calculations with your business and make changes visible, so the team can trust the report and use its judgment.

Where we start

Start with the work
that gets in the way.

We should talk

A repeated task.
A clearer goal.

  • Your team spends time exporting, comparing or checking.
  • The information you need lives in several systems.
  • You know what a useful result would help you do.
Before we build

Make sure it will
help the team.

  • We understand how the work happens today.
  • We check which data we can connect and trust.
  • We agree what the system does and what people decide.

Book a call / 45 minutes

What is slowing
your team down?

We’ll look at how the work happens today, what data you have and where a useful first project could start.

  1. 01Walk us through the work today.
  2. 02Look at the systems and people involved.
  3. 03Find a practical next step together.

Europe-friendly · Remote-first · No pitch theatre

Let’s look at the work.Consultation

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Growth — solutions built around your business — BGA