A retailer can grow sales and still struggle with profitability. A product can sell out in one location while sitting untouched in another. Our work starts with those business questions, connects the evidence and identifies what needs to change.
Ten connected lenses.
- Business economics and segments
- Product development and the customer proposition
- Sourcing, procurement and production
- Demand planning and merchandising
- Fulfillment, delivery and product use
- Discovery, stores, online shopping and purchase
- Loyalty and retention
- Customer service and feedback
- Competition and market entry
- Implementation and investment
Start with how the business makes money
We examine products, customers, channels, markets and the operating model. Where available, annual reports, interim results, margins, cash flow and business segments help separate changes in price, volume and product mix.
Public research gives an outside view. It cannot reveal every internal cost, customer behavior or operating constraint. We show those gaps and explain what data would be needed to validate an opportunity.
Connect the operating decisions
We follow ten connected areas of the business. An apparent checkout problem can start with stock availability. Returns can reveal problems with fit, quality or product information. More marketing can expose service failures when operations cannot support demand.
Supply-chain analysis considers lead times, supplier dependence, minimum orders, landed costs and delivery reliability. Merchandising connects assortment, sizes, allocation, price and markdowns to customer demand. Customer-experience analysis follows discovery, purchase, delivery, use, returns and the next visit.
A forecast matters when it improves purchasing or replenishment. A loyalty program matters when it supports additional profitable visits. Reviews help surface questions, but voluntary reviews are a partial view of the customer base.
Make customer experience an operating opportunity
Every analysis examines a customer-experience opportunity alongside supply chain. Reviews, product complaints, support, refunds, returns, delivery and app feedback help identify questions to investigate. We connect recurring signals to a product, location or operating decision and assign a proposed owner. Public feedback is a partial view; it cannot establish company-wide prevalence or a root cause.
The test follows whether the underlying issue improves: complaint recurrence, resolution time, refunds or remakes, returned products and subsequent purchases. Faster automated replies alone do not establish lasting improvement. When AI does not fit, we recommend the data or process prerequisite. Campaigns can be considered separately later.
Use cases to understand the mechanism
Implementation cases help explain what another business changed, which workflow or technology was involved and what was reported. We distinguish a pilot from a rollout, attributed revenue from incremental revenue, and hours saved from cash savings.
A recognizable company name does not establish relevance. Category, operating model, geography, data needs and implementation constraints determine whether a lesson is worth testing. Another study’s reported improvement does not become a forecast of your benefit.
Make AI earn its place
AI can help organize research, compare implementations and develop hypotheses. The useful question is which decision or workflow needs improvement, and which approach fits it.
Provider research considers evidence, data readiness, integration, human oversight, costs and maturity. We compare buying software, building a solution and improving the process with existing tools. A new model must beat a sensible baseline on data it has not seen before it becomes a tested improvement.
Choose a provider on evidence
The $79 company report identifies relevant AI companies for the specific opportunity. We compare their data coverage, product and location detail, integrations, geographic and language support, operational workflows, human controls, privacy, implementation effort, total cost and customer evidence. Momos is a candidate where its restaurant focus fits; it is not the default winner. Unknown capability or cost stays unknown.
Discovery, data readiness, a bounded pilot and scaling are distinct phases. The plan depends on the actual systems, team and procurement process; a 90-day window is not a promise to complete an AI transformation. Direct implementation support is scoped separately with David.
Turn a hypothesis into a measurable decision
A useful recommendation identifies the evidence, missing information, proposed change, responsible team, credible comparison and measures for expanding, revising or stopping. A focused test helps determine whether the idea fits the company.
Financial scenarios make assumptions visible. We separate additional sales, profit, cash released from inventory and time saved. Costs, returns, discounts and overlapping benefits belong in the calculation. A modeled opportunity is a proposition to validate.
Give the team a clearer starting point
Depending on the report scope, our work provides company and market research, ranked opportunities, relevant cases, possible technology options, scenarios and practical next steps. A focused brief examines a narrower question; a deeper diagnosis connects more of the business.
The Retail Lab is currently in beta. Commercial judgment determines whether an idea fits. Internal data and real-world comparisons determine whether it works.