01 / Customer question
The commercial context
Brand demand must connect to the correct product on the shelf.
AI may influence which brands a customer considers for a meal, household task or personal-care need. The manufacturer needs the right product, formulation and pack to be represented, with a route to a retailer that actually carries it.
That differs from the retailer's control of assortment, inventory and checkout. Brand teams may influence approved content and product syndication while the retailer owns availability and the purchase relationship. We assess category consideration and data consistency within those practical channel boundaries.
Customer journeys
Test category, occasion and substitution questions.
We agree the questions, audiences and markets to assess. The examples below show what we can investigate, with the final scope based on your priorities.
02 / Customer question
Does a comparison preserve the actual formulation, pack size, ingredients and allergens?
03 / Customer question
Can discovery connect the correct SKU to a retailer carrying it in the relevant market?
01
Category and brand benchmarking
We evaluate brand and SKU presence by occasion, need, market and agreed competitors. The findings identify category-discovery gaps, own-label substitution patterns and material product claims.
You receive: Category-consideration baseline and source/claim gaps.
02
Product and retailer syndication
We reconcile GTINs, pack formats, formulations, brand references and retailer listings. The priorities address inconsistent ingredients, allergens or market applicability and the process for syndicating correct data.
You receive: Digital-shelf consistency audit and syndication priorities.
03
Channel and internal pilots
We assess retailer and DTC routes alongside permissioned brand, content or insight workflows. The plan identifies channel owners, approved-information processes and measures that the available data can support.
You receive: Channel strategy options, approved-content process and pilot measures.
Internal AI readiness
Connect brand, category and product-data ownership.
Formulation changes, claims approvals and retailer updates need coordinated ownership. We assess how brand, category and product-data teams retrieve approved information and maintain consistency across markets and channels.
Public product attributes are separate from confidential formulations, shopper records and commercial agreements. Internal pilots use appropriate permissions and review. Sales evaluation also needs realistic boundaries: a manufacturer should not assume direct access to every retailer's checkout or customer data.
A practical first engagement
FMCG AI Category & Digital Shelf Assessment
We agree brands, categories, occasions, markets, representative SKUs and retailer channels. You receive category findings, product and listing inconsistencies, content and access priorities, and a roadmap with channel owners and suitable approved-content or discovery pilot options.
01
Agree the scope
We agree the business questions, reference sources, AI platforms and teams involved. Before the assessment begins, we confirm the access needed and any work it depends on.
02
Review the evidence together
We separate what the AI answer shows from the content, data or workflow issues behind it. Your teams help decide which changes matter and which are feasible.
03
Choose the next action
The plan identifies the priorities, who is responsible, what each change depends on and how it will be checked. If a pilot is worthwhile, we agree how to run and evaluate it with the teams involved.
Evaluation
Measure the changes that matter.
We agree how to evaluate results before making changes. Each answer is recorded with its question, market, AI platform and date. Repeat checks help identify patterns. We assess commercial results and improvements to internal workflows separately with your teams.
Category and occasion consideration
Correct SKU and formulation
Retailer data consistency
Distribution and measurable sell-through
Part of Ayima
Technical search expertise. Practical enterprise thinking.
SWLR combines AI visibility and readiness consulting with Ayima's experience in enterprise search. We investigate the content, data and technical issues behind your business question, including access permissions, then help your teams decide what to do next.
Common questions
Before we begin.
How is this different from retail AI consulting?
Retail work centres on assortment, inventory, fulfilment and checkout. Manufacturer work centres on brand/category consideration, product information and retailer syndication. The channel strategy follows who owns the systems and customer journey.
Can AI recommend the right regional formulation?
We assess explicit product identity, formulation and market references, then test relevant scenarios. Correct GTIN, pack and regional attributes help distinguish products. Evaluation is needed to identify remaining confusion or outdated retailer information.
How do we measure sales when retailers own checkout?
We use the retailer and channel data available within the agreed scope. Where order or sell-through evidence is unavailable, reporting separates observed discovery from sales outcomes. Attribution or incrementality cannot be inferred from a brand mention.
Retail & Omnichannel CommerceGive AI shopping experiences accurate product information and assess the route from recommendations to orders across your catalogue and markets.
Consumer Health, Wellness & NutritionAssess how AI describes your ingredients, benefits and intended use, then improve approved information across your products, markets and channels.
Signal → Evidence → Action
Start with the questions that matter.
Discuss your brands, categories, markets and the retailers carrying your products.
Discuss your AI strategy