Can you serve the demand you are promoting?
Look beyond total stock. Compare the sizes, colours, shades and price points shoppers seek with the campaign exposure you have planned.
Decide what to push or suppress.
For ecommerce & digital trading teams
Your Black Friday
plan is fixed.Your shoppers
are not.
Which customer demand is your website failing to serve, and what can you still change before peak?
Data-Hat AI connects available demand signals, stock and planned campaign exposure to identify which products, variants and customer journeys deserve a different trading decision.
Book a 20-minute Demand Review
With KK, founder of Data-Hat AI. · No data access needed.
Kshitij Kumar (KK)
Founder, Data-Hat AI · Your review host
Farfetch
Former Chief Data Officer
Zalando
Former VP Data
The questions worth asking now
Challenge the plan.
Before the traffic arrives.
For fashion, beauty and luxury ecommerce teams that can still change campaigns, merchandising or customer journeys.
What happens when the first choice fails?
Distinguish alternatives shoppers have actually accepted from plausible recommendations. See where recovery has evidence and where it needs testing.
Decide what to redirect or test.
What should Friday change about Monday?
Use emerging demand and stock pressure to revisit traffic, product exposure, creative and CRM while the Cyber Week opportunity is still open.
Decide what to widen, reverse or hold.
What a demand finding looks like
One unavailable size.
A different trading decision.
Illustrative example.
Not a customer result or product screenshot.
01 / The plan
A hero jacket campaign.
Media and CRM are set to send shoppers to a featured jacket.
02 / The signal
The wanted size is missing.
Shoppers repeatedly select an unavailable size. A sales-only view misses that demand signal.
03 / The recovery evidence
Some shoppers switch.
Some affected shoppers buy another in-stock jacket. Others leave.
04 / The decision to test
Redirect the relevant journey.
Test the observed alternative. Compare conversion and contribution margin.
The evidence informs a test. It does not prove why every shopper left, or that every alternative will work.
From review to action
Before peak. Through Black Friday.
Into Cyber Week.
The first conversation identifies a useful problem. A scoped, paid engagement is the next step where there is a fit.
Before peak
The two-week sprint
Investigate demand gaps, challenge planned exposure and prepare recovery tests using the available data.
During Black Friday
The Demand Desk
A senior AI and retail team works alongside yours to interpret emerging demand and prioritise approved trading corrections.
After Black Friday
Cyber Week corrections
Carry Friday's unexpected demand, stock pressure and failed substitutions into the remaining promotional window.
Scope, data access, refresh cadence and feasible changes are agreed against your team's trading deadlines.
Your first step / 20 minutes
Bring one campaign.
Or one category.
A working conversation about your Black Friday plan. Not a generic platform presentation.
- Identify the demand question.
Where might shopper demand and your plan diverge? - Establish what can still change.
Campaigns, merchandising, recovery journeys or exposure. - Agree a useful next step.
What evidence is needed, and whether a sprint fits.
Kshitij Kumar
Founder, Data-Hat AI
Arrange your Demand Review
Tell KK a little about your retail website and request a time by email.
Contact details are for arranging this review, not a mailing-list signup. Privacy Policy.
Prefer a direct email?
kk@data-hat.com
Before we meet
A clear question.
A practical next step.
No data access is needed for the first conversation. The review establishes what is worth investigating.
Is this a generic website audit?
No. We start with a trading question, not a checklist of website fixes. The sprint connects available demand signals to stock, campaign exposure and a specific decision your team can make.
What data would a sprint need?
Depending on the question: onsite behaviour, product and variant availability, and campaign or CRM plans. We start with what you already collect. Tracking quality and access determine which analyses are feasible.
What if our Black Friday plan is already locked?
We first establish your change freeze and what is still in scope. The work follows your trading deadlines. We will not assume a change is feasible just because the analysis suggests it.
Will AI change our site or campaigns automatically?
Changes remain subject to your team's approval and agreed controls. The review and sprint establish what to investigate, what to test and who owns each decision.