Innermoon is an advisory practice for brand owners, retailers and analytics providers across Asian retail and travel retail. We work in the gap between what the data can now show and what an organisation is actually able to decide.
Most of the money was already being spent with the same retailer, under a different line item. It belongs inside the joint business plan, priced against everything else the retailer is asking for, and measured on incremental sales rather than impressions.
The highest-value shopper segmentation is usually derivable from transaction data the business already holds, joined to public data nobody has thought to join it to. Not more data. Better joins, and a hierarchy clean enough to make them possible.
The shelf moves on a slow cadence no amount of AI shortens. Price, promotion and feature space move weekly. Agility is available wherever a change is cheap to make and cheap to reverse — stop pretending the planogram is agile.
Tooling will surface a correlation faster than any analyst and will not tell you why it exists. The commercial value sits almost entirely in that second step. We hold a hard view on this because we enforce it inside our own production systems, where a wrong answer costs money.
Senior and small by design. Every engagement ends in a decision someone owns, or it has failed.
INNERMOON PTE LTD · SINGAPORE · UEN 202118442M
An advisory practice working with brand owners, retailers and analytics providers across Asian retail and travel retail. We work on the gap between what the data can now show and what an organisation is actually able to decide.
Most of the money funding retail media in this region was already being spent with the same retailer, under a different line item. Treating it as new media spend hands the retailer both sides of the negotiation. It belongs inside the joint business plan, priced against everything else the retailer is asking for, and measured on incremental sales rather than impressions.
The highest-value shopper segmentation is usually derivable from transaction data the business already holds, joined to public data nobody has thought to join it to. Not more data. Better joins, and a product attribute structure clean enough to make them possible.
The physical shelf changes on a slow cadence set by store labour, supplier lead times and the range review calendar. Price, promotion, feature space, signage and staffing change weekly. Agility is available wherever a change is cheap to make and cheap to reverse.
Current tooling will surface a correlation faster than any analyst and will not tell you why it exists. The useful question is what a machine has to prove before someone is entitled to act on its output, and how that line moves as the tools improve.
What you are paying for, what it actually answers, and which decisions it changes. The output is a single map of where the spend earns its keep, with a recommendation on what to cancel, renegotiate or join together.
For suppliers facing a retailer’s media proposition: what is genuinely being sold, what it is worth, what evidence to demand, and how to fold the commitment into trade terms.
Building the fast layer and defining what runs on it. Success criteria before the test, a weekly rhythm the store can sustain, and a clear line on what a machine must demonstrate before a recommendation is actioned.
Positioning, commercial model and route to market for transaction data and shopper analytics companies moving into Asian retail, from the perspective of people who have been the buyer in these markets.
INNERMOON PTE LTD · SINGAPORE · UEN 202118442M