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Fundle Agentic AI · Retail Analytics Agent

Store-level intelligence for multi-outlet retail.

Benchmarks every store, category and SKU across your network, explains why performance differs and tells each store manager exactly what to do next.

per-store

action plans

+12%

same-store sales

daily

benchmarking

Section 01

The business problem

Retail chains drown in POS reports but starve for direction. Head office sees averages; store managers see their own numbers; nobody sees which specific action lifts a specific store.

Why existing solutions fall short

  • Reporting shows what happened, never what to do about it.
  • Best practices from top stores never reach the laggards.
  • Analysis stops at the chain level and never reaches the shop floor.

Section 02

How Fundle solves it

The Retail Analytics Agent benchmarks every store against comparable peers, isolates the drivers of the gap and pushes a concrete, prioritised action plan to each store manager, then tracks whether it worked.

01

Like-for-like benchmarking

Compares stores against true peers by format, catchment and size.

02

Driver analysis

Explains why a store over- or under-performs (basket, footfall, conversion, mix).

03

Store action plans

Delivers a ranked to-do list to each manager, in their language.

04

SKU & category insight

Surfaces winning and dying SKUs and category opportunities per store.

How it works

From data to outcome — the agentic workflow.

01

Benchmark

Ranks each store against comparable peers daily.

02

Explain

Isolates the specific drivers of each performance gap.

03

Prescribe

Sends prioritised actions to each store manager.

04

Verify

Measures whether the action closed the gap.

Business impact & ROI

+12%

same-store sales growth

−35%

time on manual reporting

100%

stores with a plan

Integrations

POS systemsERPInventory systemsFundle CDPBI toolsREST API

FAQ

Retail Analytics Agent — questions buyers ask.

How is “comparable peer” defined?

By format, catchment demographics, floor area and footfall, so benchmarks are fair.

Can store managers actually use it?

Yes — output is a short, plain-language action list, not a dashboard to interpret.

Does it need clean master data?

It tolerates messy data and improves as SKU and store master data is connected.

Get started

See Retail Analytics Agent on your data.

A 30-minute working session with the Fundle team — mapped to your brand, mall or programme.

A

Abhinav · Fundle.ai

Loyalty & ADSR Expert · Online

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