For retailers
Every decision-maker gets
their own analyst
Not a tool for the function — an analyst for the individual, equipped with the skills of your role. And your data & insights team is freed for value-added work, not production: we assemble, run and keep the platform fresh, daily.
What would yours do?
Leadership
Prioritise the key issues, by impact.
Category Manager
Diagnose performance drivers, and recommend actions.
Buyer
Build the negotiation plan, with scenarios.
Marketer
Evaluate campaign and promotion effectiveness, and recommend improvements.
Planner
Diagnose the cause of out-of-stocks and recommend solutions.
Monday morning
A meeting that decides, not reconciles
Every function arrives with the same version of the truth.
Sales vs plan
one number, ready before the room fills
Why we’re up — or down
drivers diagnosed, not debated
Range and promotions
proposals with the evidence attached
Availability
what the out-of-stocks actually cost, store by store
Actions
agreed in the room, not afterwards
Any number challenged?
iterate live — ask, and ask again
A worked answer, scope and all
A category manager, mid-conversation. Every answer states the basis it was calculated on.
The chilled ready meals category is up double digits. Is that real, and where is it coming from?
| Where the growth came from | Contribution | Customers | Spend / visit |
|---|---|---|---|
| New to the category | +6.8 pts | +214k | 2.10 |
| Existing, buying more often | +4.1 pts | — | 2.44 |
| Trade-up within range | +2.9 pts | — | 2.71 |
| Lost to competitors | −1.5 pts | −47k | — |
| Net | +12.3% | +167k | 2.37 |
It is real growth, not a price effect: three quarters of it comes from new category buyers and higher frequency, at a rising spend per visit. The offsetting loss is concentrated in salads and prepared vegetables — the same shopper missions, moving across.
Who are the new buyers?
Same view excluding promotions
What should I range next?
And everyone can ask
Where access has to be justified licence by licence, it goes to the few who can prove they need it — and everyone else works from extracts and last month’s deck. Every extract is another chance for two teams to calculate the same number differently.
1,300+
users at the reference deployment, with no licence to justify
3,000+
reports run daily, on 100% granular data
94%
user satisfaction — the case study →
And it pays for itself
Suppliers subscribe to permissioned insight on their own categories — a premium tier above the data they already buy. At our reference client, 69 manufacturers pay today. Enabling one is a permission, not a build: revenue starts with the first agreement.
Suppliers pay
A premium tier above the data they already buy.
Costs are clear
No seat tax — one price, everyone on board.
Self-funding
Supplier revenue covers the platform cost.
>100% ROI
per annum, at the reference deployment.
01
Live in weeks
Not a multi-year BI programme.
02
Your data team, unburdened
The request queue moves to Caisy.
03
Run for you, daily
Data operations included, kept fresh.
04
In your own cloud
Alongside your existing warehouse.
Level the retail playing field
The capability of the global leaders, for retailers without their scale. Bring the questions your business argues about — and ask them twice.