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Executives · Data-driven retail
How to become a data-driven retailer without a multi-year build
A retailer becomes data-driven when the people making everyday decisions can get evidence in the moment they need it. 11Ants makes that possible without a multi-year build. It connects to your existing data, and every team gets Ant, an AI retail expert they can ask in plain English. Most customers are up and running within two weeks.

THE CHALLENGE
Why do data-driven programs take so long?
Most retailers already have the data. What they lack is a way for category managers, marketers and store teams to use it without waiting on a small analytics team.
Building that capability in-house means data engineering, new hires and custom models. It can take months and still leave most decisions resting on instinct.
THE SOLUTION
How does 11Ants make a retailer data-driven?
Ant, available to every team for plain-English answers, with Ant Reports for scheduled updates.
Alongside it, more than 40 research modules give analysts and power users ready-built, best-practice retail analysis, so nothing needs to be built in-house.
Connect existing data
11Ants works on top of your current warehouse and systems.
Give every team Ant
Merchandising, marketing, operations and leadership ask questions directly.
Apply proven methods
More than 40 research modules bring best-practice retail analysis to every team.
Build the habit
Ant Reports delivers the numbers each role needs, on schedule.
EXAMPLE QUESTION TO ASK ANT
QUESTION
How did sales and margin perform yesterday against budget, and what should I be concerned about?
WHAT ANT RETURNS
[Insert a real Ant answer from demo data: headline performance against budget, the two or three issues to watch, and who owns each.]
See Ant prepare a board ready trading update
Demonstration data; brand names are illustrative.
What does buy versus build look like?
Build in-house
TIME TO FIRST VALUE
Months of data engineering and hiring before first value
INFRASTRUCTURE
New data platform and tooling
PEOPLE
Data engineers, analysts, data scientists
RETAIL METHODS
Built from scratch
ONGOING COST
Salaries, maintenance and rebuilds
Buy 11Ants
TIME TO FIRST VALUE
Most customers live
within two weeks
INFRASTRUCTURE
Uses your existing data
PEOPLE
Existing teams, minimal training
RETAIL METHODS
40+ ready-built research modules
ONGOING COST
Subscription, which suppliers can help fund
What does buy versus build look like?
Time to first value
BUILD IN-HOUSE
Months of data engineering and hiring before first value
BUY 11ANTS
Most customers live within two weeks
Infrastructure
BUILD IN-HOUSE
New data platform and tooling
BUY 11ANTS
Uses your existing data
People
BUILD IN-HOUSE
Data engineers, analysts, data scientists
BUY 11ANTS
Existing teams, minimal training
Retail methods
BUILD IN-HOUSE
Built from scratch
BUY 11ANTS
40+ ready-built research modules
What results do retail leaders see?
Jobs that took the whole day now only take a few minutes and a few clicks in 11Ants.

Luka Jalšovec
BI Project Manager, Mercator
11Ants has increased my efficiency, I don’t have to contact business intelligence for every matter – I’m more independent.

Ambrož Rozman
Category Manager, Mercator
11Ants is used by retailers including Mercator, Farro, IDEA, Farm Source, Metcash, Konzum and Green Cross Health.
Data-driven retail FAQ
What does it mean to be a data-driven retailer?
A data-driven retailer makes range, pricing, promotion, store and customer decisions on evidence from its own data, at every level of the business. That means frontline decision-makers, not just analysts, can get answers quickly.
Do we need a data science team to use 11Ants?
No. 11Ants is built for business users. It brings ready-made retail methods and an AI expert, so teams can use the data without hiring specialists.
Should we build or buy retail intelligence?
Build if your needs are unique and you can wait years for value. Buy if you need proven retail analysis across the business quickly. For most retailers, buying 11Ants frees internal IT and data teams for genuinely bespoke projects.












