Easier product decisions
Make product information easier to find, compare and maintain so customers and staff can choose with more confidence.
FROM POSSIBILITY TO PRACTICE
For your commerce and merchandising team, “Grocery and basket” can become a repeatable workflow rather than a separate task handled from scratch each time. AI can organise the relevant information, work through a question and prepare an explanation of the options or findings for your team. It fits into product discovery, catalogue operations and customer assistance, using your business information and the standards your team already works to.
These are the improvements to evaluate against your current process. We agree the scope and test the value with your team.
Make product information easier to find, compare and maintain so customers and staff can choose with more confidence.
Bring scattered information into a useful explanation so the team can focus on evaluating the result.
Make assumptions, evidence and trade-offs visible rather than leaving them buried in separate records.
EVIDENCE FROM OTHER BUSINESSES
These named businesses implemented related workflows. Their deployment results provide a reference for the opportunity; they are not appana projects or a promised return for your business.
Logile Fresh Inventory Management
1,070%Reported annual deployment ROI
Demand-led fresh production reduced excess stock and spoilage; the study attributes more than $10 million in profits to the deployment by year three.
A grocery-wide deployment combining production planning, recipe, grind and yield management. This is the suite’s return, not an isolated forecasting result.
Nucleus Research · Published 2025-12-17 · Source checked 2026-10-05
Read the published case study ↗Reported annual ROI uses Nucleus Research’s method: average annual net benefit across three years divided by initial investment. Assessments can include indirect benefits and projected years. Figures cover the named deployment, including software, integration and process changes; they do not isolate AI’s contribution or predict your return.
Nucleus Research’s calculation method ↗STEP 1
Select the relevant information from your commerce platform, product-information system and stock tools. Agree what a good result looks like with your commerce and merchandising team, including the rules, examples and permissions the workflow needs.
STEP 2
Substitutions, baskets and the weekly shop. Apply the agreed criteria, separate evidence from assumptions and make the reasoning available for someone to challenge or refine.
STEP 3
Provide an analysis or recommendation with supporting information, open questions and a clear decision for the owner to make. Staff verify stock, product claims and commercial terms before they are presented as confirmed.
AN EXAMPLE IN PRACTICE
A member of your commerce and merchandising team needs help with “Grocery and basket”. They supply product attributes, catalogue records and stock information, together with the relevant instructions and the result they need. The workflow prepares an initial result with its supporting context, flags missing information and returns it for review. The owner can correct it and use the accepted result in the team's commerce platform, product-information system and stock tools.
Choose one workflow, one team and a representative set of real tasks. We establish the current baseline, build the first version and review the results together before expanding it.
Depending on the scope, useful inputs include:
We agree access and integration with your commerce platform, product-information system and stock tools as part of the design.
Staff verify stock, product claims and commercial terms before they are presented as confirmed.
LET’S BUILD IT TOGETHER
Tell us how your team works today and what you would like to improve. We’ll explore the opportunity, shape a practical first step and build it with you.
Talk to us about this use case