Aislemetry is AI-first retail audit software for designing store audits, preparing field teams, capturing evidence, and turning retail data into clear findings and recommended actions. Count SKUs, measure share of shelf, and see where store execution needs attention.
Why are competitors
gaining share in Atlanta?
Aislemetry is AI-first retail audit software that connects business questions, audit design, store evidence, and recommended actions. Its Visual Intelligence is designed to identify visible SKUs, count product facings, and measure facings-based share of shelf from photos. Retail teams review uncertain observations and use the evidence to investigate assortment and execution gaps.
Brands ask open questions about share, execution, pricing and growth. Traditional audits often begin with fixed questions and end with spreadsheets—leaving people to connect the evidence to a decision by hand.
Plan the work before a visit, guide consistent field execution, and connect what teams observe in stores to the question the business needs answered.
Use shelf photos to identify and count visible SKUs and product facings. Compare the observed assortment with the expected range to identify products not observed in the captured shelf area and prioritize store follow-ups.
Explore AI SKU counting ↗Measure your brand’s share of visible category facings: brand facings divided by total category facings, multiplied by 100. Compare shelf presence across stores, regions, and visits to identify gaps and guide merchandising decisions.
Explore share of shelf measurement ↗Design retail store audits around availability, assortment, pricing, shelf share, displays, and planogram execution. Keep questions and evidence tied to the measures your team wants to understand.
Explore the audit workflow ↗Structure retail and mystery audit programs with clear questions, required evidence, and consistent field capture. Give analysts a connected dataset to review across stores, channels, and locations.
See the Aislemetry capabilities ↗Prepare the audit before fieldwork begins: define store scope, organize sampling by zone and outlet type, set the questions and metrics, and specify the photos or observations teams need to collect.
See an audit plan example ↗Each stage passes structured context forward, so the evidence stays connected to the question that started the work.
Start in plain language with the question your team needs answered.
Generate the methodology, questions, evidence, metrics and sampling plan.
Capture answers, photos and store context in a consistent format.
Read visual evidence, compare dimensions and surface patterns and gaps.
Give teams clear next moves they can review, prioritize and decide on.
Aislemetry breaks the business question into dimensions field teams can measure and the analysis can compare.
See the capabilities ↓Purpose-built AI capabilities carry the audit from design through interpretation and action.
Turns the business problem into an audit methodology.
Structures and validates field data collection.
Reads shelf photos to identify visible SKUs, count facings, and measure share of shelf.
Finds patterns across large volumes of audit data.
Converts raw results into clear business findings.
Connects insights to recommended actions.
Findings arrive with the evidence behind them, giving teams a way to investigate before they act.
Aislemetry connects findings to the stores and evidence behind them. Your team reviews the options, sets priorities and makes the final call.
Back to the beginning ↑Increase display presence in priority clusters
↗Improve promotional execution
↗Address assortment gaps
↗Investigate competitor pricing
↗Aislemetry builds on years of operational experience, field work and retail data.
Retail checklists completed
Images processed
Experience across retail and facilities
Built from real-world retail execution
Aislemetry is AI-first retail audit software that connects business questions, audit design, store evidence, and recommended actions. AI supports audit methodology, visible product recognition, facing counts, and evidence-linked findings. Teams review uncertain observations and decide on follow-up actions.
Retail audit software helps brands and field teams plan store checks, capture structured observations and photos, and analyze retail execution across locations. Aislemetry adds AI-assisted audit design and evidence-linked insights to that workflow.
Aislemetry Visual Intelligence is designed to identify visible SKUs and count their facings from shelf photos. Teams can compare the observed assortment with the expected range and review the linked photos to investigate gaps. Shelf observations reflect visible products at the time of the visit.
Aislemetry is designed to support retail and mystery audit programs by structuring questions, field evidence, and analysis around the business problem. The specific methodology is reviewed by your team before launch.
A pre-journey plan can define the store scope and sampling, questions, metrics, required photos or other evidence, and the analysis approach before auditors visit stores.
Aislemetry Visual Intelligence is designed to read store and shelf photos and structure observations such as product presence, facings, share of shelf, displays, and planogram compliance. Examples on this page are illustrative.
Aislemetry brings business context into the audit—and intelligence back to the business.
Explore Aislemetry ↑Content reviewed · Aislemetry