– enabling the data driven decision process in retail

Build on ADI™ (Automated Decision Intelligence) answering:

Where, what, which, why, when, how


is now a part of can help increase ROI on online advertising with 20% – 400% using shop specific location data.

Using data on variations from where shoppers origin, and variations in for example Facebook online coverage in different locations, can increase expected ROI on advertising investments online from estimated 20-400%.
Gilling´s © can provide these accurate calculations and even automatically execute a complex advertising plan optimized with location data.

The largest data- and knowledge base of danish retail – EVER BUILD! gives fast access to updated locations and data about ALL danish retail shops and chains (app. 66.000 shops, including 550 chains with app. 17.000 chains shops), in this example the Matas chain. In half a minut you have access to all the data you need about every Matas shop, and you can export these data to your own excel template to make the calculations you need.

Get to know your market: Fast inspection of potential new locations or explanations of existing shop´s revenues and
competitive situation? gives fast access to visual hot spot inspection checks of many different variables like income, traffic, age groups, consumption, houses, appartments and in general every variable that can be measured.


Professional retail investment management: Estimating revenue and ROI for new shop locations using Big Data and algorithms?
How much revenue can we make at this new location? gives access to ADI™ (automated decision intelligence).
Using algorithms prepared by integrating chain data with Gilling data, we are able to estimate potential revenue for a NEW SHOP with great accuracy and precision. For the technically minded, R2 often is above 85% and average uncertainty around 10%. easily implements all kinds of algorithms using big data, ADI™ and AI, and outputs fast calculations and easy to understand graphics.

Efficent business development potential: Simulate new shops at EVERY potential location and prioritize for development!
If a retail chain has developed a usefull algorithm, can be used to ”massrun” say 50.000 potential locations (addresses). For each location calculates potential revenue if a shop in the chain is located at the address, delivering a list of total national covering potential. These locations and their values shows where to search for optimal new locations, and are efficient tools for business development.

Gilling Products:

Retail MasterPlan™

Retail MasterPlan™

The best alternative. How much revenue can/should we create from this retail location? Where should we locate retail chain stores? How many of our retail stores can the market accommodate?

The Human Decision System™

The Human Decision System™

The moment of truthHow do humans make decisions?  How can we create algorithms for behavioural predictions that reflect the human decision process?

Big Data for sale

Big Data for sale

Integrating datasources. What data is available to support our own ADI system? Consult the Gilling Universe of Big DECISION DATA for the answers.

Retail Ranking™

Retail Ranking™

Knowing who & why. Which retail chains are the optimal renters for this location?  Simulate which of the +500 Danish retail chains can create the best sustainable business from any retail location.

Office Ranking™

Office Ranking™

Knowing who & when. How do we direct our marketing to the most probable companies to rent our available office space?  Office Ranking™ predicts your most probable prospective tenants!

Center Ranking™

Center Ranking™

Knowing who & what. What is the optimal retail profile of the shops in our shopping centre from the shoppers’ perspective? Do we have the right mix of shops?  Who´s missing, who´s redundant?

MEDIA Ranking™

MEDIA Ranking™

Optimize!… Where and how can we maximize ROI and response to our marketing investments using advertising geolocation analysis and all social and psychological profiling and thus optimise all social media activity?

Software development

Software development

On time on price. Develop effective ADI solutions based on Gilling’s standard and bespoke components and Big Data.

The Profit Chain™

How to automate and optimize your sequence of business decisions with ADI and Big Data?

Finn Gilling presenting The Human Decision System™ at Symbion Science Park, August 2016

Teach yourself how to automate Business Decision making

Use 5 minutes:

How to develop a model for ADI and Big Data

The Profit Chain™ is a general model describing all the decisions, that any business management is confronted with. As these decisions are depending on each other, The Profit Chain™ also describes the optimal sequence in which to make them, maximizing your degrees of freedom as you are using them.

To design automated decision intelligence, translate these general decisions in The Profit Chain™ into “your reality” and add goals and targets as measurement points:

An example: The “location” decision in The Profit Chain™ model translated for ADI with Big data:

Retail chains need to find the best locations for their shops. The target is an unidentified address among millions of addresses. The goal is to maximize revenue at one of these addresses with a new shop.

To automate your business decisions with ADI, work systematically through all the business decisions in The Profit Chain™, and define goals and targets. When this is ready, you can identify your measurement points (ex…target = an address related to data like the number of consumers within 500 meters to the address, or shopping traffic around the address etc.)

If you have not seen The Profit Chain™ before, here is a short 5 minutes introduction – push left/right with the arrows at the screen below and start with no. 1.

Read moreand order the book on:

Gilling / The Human Decision ApS

Symbion Science Park

Fruebjergvej 3

2100 Copenhagen Ø

Finn Gilling


Tel.: +4560211704

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