[Value] / what the data says

What are data and algorithms actually worth?

I do not sell "AI-driven synergies". I sell modules with measurable results. So let the numbers speak: here is the strongest independent evidence of what the right algorithms create in value. Under each area you can see exactly which modules deliver it.

[01]  / run the numbers on your own potential

What could the numbers mean for you?

Enter a few key figures and get a conservative range for the annual potential. The details per area and every assumption sit openly under "Behind the numbers", and the numbers are typical effects, not a promise.

Average basket · calculated automatically ·
Annual potential · conservatively estimated ·

The estimate is based on typical, documented effects, not on your data, and it is not a promise. The actual potential is mapped in the free spot.

Behind the numbers
Churn & repeat purchases ·

0.5-1.5 percentage points lower customer loss (churn or no-shows), caught and followed up in time. Counted as retained annual revenue.

Recommendations & cross-sell ·

+2-5% on the average basket via recommendations and cross-sell, with the number of orders unchanged.

Dead stock & inventory ·

Typically frees 10-20% of the capital tied up in inventory. Inventory is valued at cost, not at sales price, so tied-up capital is estimated at 0.75-1.25× monthly revenue. One-off amount, not part of the annual total.

Returns ·

15-25% fewer returns once the problem items are found and fixed. Cost per return set conservatively at 10% of the average basket.

Document automation ·

60-85% of the manual data hours can be automated: invoices, reports, data entry. Valued at your hourly cost over 46 working weeks.

Freed-up time ·

The same hours in plain numbers: time your team gets back for what actually requires a human. Not counted in the kr total.

  • Annual revenue = 12 × the monthly revenue.
  • Churn & repeat purchases: 0.5-1.5 percentage points lower customer loss, converted 1:1 to retained annual revenue.
  • Recommendations & cross-sell: +2-5% on the average basket with the number of orders unchanged, equal to +2-5% of annual revenue. Shown only for webshop and B2B.
  • Dead stock & inventory: inventory is valued at cost, not at sales price. At a typical gross margin of about 50%, 1.5-2.5 months of stock corresponds to tied-up capital of roughly 0.75-1.25× monthly revenue, of which 10-20% can typically be freed. One-off amount, kept out of the annual total. Shown only for webshop and B2B.
  • Returns: number of returns = orders × return rate. Cost per return set at 10% of the average basket (shipping, handling, value loss), and 15-25% of returns are avoided. Shown only for webshops.
  • Document automation: 60-85% of the manual hours can be automated, counted over 46 working weeks per year at the stated hourly cost.
  • Freed-up time covers the same hours as the document card and is therefore not counted in the kr total.
  • All amounts are rounded. The total is the sum of the kr ranges for the areas shown, and no amount is counted twice.
[02]  / pays off, and fast

The investment pays for itself. Fast.

Data and AI is not a cost line. It is one of the investments with the shortest payback right now.

Return per euro invested
0.00
€1 in€3.50 out

back for every euro invested in AI. The best return €8+, and the average payback is just 14 months.

Source: IDC · 2024
[03]  / and Denmark is already ahead

Those who use their data pull away from the rest.

The gap between businesses that exploit their data and those that do not is widening fast.

Revenue growth · leaders vs laggards
0.0 ×
AI leaders
1.7× growth
Laggards
baseline

faster revenue growth at the most AI-mature businesses, with 40% larger cost savings.

Source: BCG · 2025
Share of businesses using AI · 2025
0%
Denmark
0%
EU average

Denmark is no. 1 in the EU. The train has left; the question is whether you are on it.

Source: Eurostat · 2025
[04]  / more from the ones you have

More from the customers you already have.

Selling more to an existing customer, and keeping her, is far cheaper than finding a new one. The algorithms do both.

Revenue uplift · personalisation
+0 %
Typical
+10-15%

revenue uplift from personalisation done right: the right customer sees the right product at the right time.

Source: McKinsey · 2021
Profit lift from 5% better retention
+0 %

profit can rise this much from just 5% higher customer retention (25-95%). Churn models step in before the customer is gone.

Source: Bain & Company
[05]  / you are already sitting on it

Your data knows more than you do.

The key point: you do not need to collect anything new. The value is already in the data you have. Untapped.

Share of business data that is never used
0 %
55% "dark data", stored, never used
0%untapped raw material100%

of business data is "dark data": stored away but never used for analysis or decisions. That is exactly the raw material a free demo is built on.

Source: Splunk / IBM

The numbers above are the industry's. The next ones are yours.

Book a 30-minute video call and we will find the numbers hiding in your data. You get concrete proposals with impact estimates, whether or not we work together afterwards.