Archived · v1.0 This is the January 2026 version of the Economic Impact Report. It remains accessible for traceability. The current version is v2.0 (May 2026) — supersedes this on five points (cumulative arithmetic, payback framing, ECR citation, supplier-CM scoping, WACC note).
View v2.0 (current)
Economic impact report · v1.0 · archived

Economic impact of R+Retail+ .

A finance-ready model of what Retail+ is worth in your business. Built from inputs you already know: revenue, gross margin, labour cost.

Per store, per year
A$32.5k A$221.4k
Extra profit per store year - driven by faster execution and stronger margin control. Based on a typical A$30m store at 27% gross margin, net of Retail+ subscription.
TL;DR

Three places the money comes from.

Protect & grow margin

Most of the impact comes from margin protection. Even small basis-point wins compound fast across A$30m of revenue per store.

+5 to +30 bps

Recover lost sales

Recover sales you'd otherwise miss through faster, smarter execution - spotting and fixing issues earlier in the day, not at quarter-end.

+0.2% to +1.0% revenue

Fewer mistakes, more time

Free up team time and reduce costly errors by turning every exception into a clear task and list - closed with proof.

4–12 hrs/wk returned
Why this works

Problem in. Fix out.

By the time you spot a problem - a promo that's not set up, stock that's missing, a category drifting - you've already lost sales and margin. Retail+ closes the loop in real time.

01
Late visibility
Issues land in weekly reports. By then, the damage is already in the P&L.
02
Lost sales & margin
Every hour without intervention costs incremental gross profit you'll never recover.
03
Retail+ closes the loop
See it, understand it, fix it, confirm it worked - in real time, with Hank assisting.
04
Confirmed recovery
Tasks close with photo-proof. Sales recover. The model gets sharper for next time.
Try your own numbers

What's Retail+ worth in your business?

Move the four sliders. The three scenarios update live, using the same model behind this report. Email yourself the result at the bottom.

1 · · · 500
A$2m · · · A$100m
15% · · · 45%
A$20 · · · A$80
Conservative
A$813k
A$32.5k per store · year
~1.6 month payback
Aggressive
A$5.54m
A$221.4k per store · year
~0.2 month payback
How this is calculated. Same model as the report above - margin gain + sales uplift + hours saved + compliance/risk avoided, with a 15% overlap haircut and per-store subscription of A$4.2k/yr. Move the sliders to see your range.
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How much Retail+ is worth in your stores.

Share your revenue, GM% and labour cost. We'll send back a finance-ready model with your numbers.

Apply for your ROI estimate
How to prove it

Indicative estimates. Prove them on your data.

Run a pilot in a small store set with matched controls. Keep scope tight. The math will speak for itself.

01

Run a pilot in a handful of stores

  • Use matched control stores
  • Keep scope tight: focus on repeatable issues and fast execution loops
  • Run 90 days minimum - enough to clear seasonality noise
02

Track the results

  • How fast you spot and fix issues
  • How many actions get closed (with proof)
  • How much performance you recover vs control stores
01

Executive summary

Retail+ concentrates value in five retailer levers:

  1. Sales recapture / uplift
  2. Gross-margin basis-point gains
  3. Hours returned (capacity unlocked)
  4. Execution & compliance risk avoidance
  5. Optional supplier contribution margin via data access / monetisation

Using an assumed A$30m revenue per store, the model estimates annual per-store value of ~A$32.5k (Conservative), ~A$100.7k (Moderate), ~A$221.4k (Aggressive) - net of subscription.

Retail+ matters because it compresses the loop from "spot" → "diagnose" → "act" → "confirm" using live analytics plus execution tooling (tasks & lists), with Hank enabling analyst-like Q&A against live performance patterns.

Scenario range, per store, annual
~A$32k to ~A$221k
Dominated by margin bps and execution-driven sales recapture.
02

Report metadata

RoleRetailer decision-makers (CEO/Owner, CFO, COO, Commercial/Category leaders)
Versionv1.0 - scenario model + substantiation-ready structure
Feature listFeatures Homepage + Retail+ feature descriptions
Date18 January 2026
Confidence score63 / 100

Confidence rationale

Upward drivers
  • Feature capability statements are explicit and verifiable.
  • Reputable benchmark sources triangulate the headroom: availability/OOS research, execution & inventory inaccuracy, analytics-performance evidence, shelf/space response.
  • Five role-specific models converge inside the same envelope.
Downward drivers
  • Only revenue/store is given as a baseline figure.
  • Baseline GM%, fully-loaded labour, supplier monetisation participation, and overlap between levers are assumptions.
  • Assumptions are exposed and sensitivity-tested below - not hidden.
03

Methodology overview

Feature → benefit → economics mapping

  1. Start with verifiable features from the Retail+ product surface.
  2. Convert each into an operational benefit with a measurable proxy.
  3. Convert each benefit into a P&L mechanism:
Sales uplift → incremental GP = ΔSales × GM%
Margin gain → incremental GP = Sales × ΔGM (bps)
Hours returned → hours × cost/hr × capture%
Compliance / risk avoided → expected-value reduction
Supplier contribution margin → supplier subscription / data access contribution

Scenario modelling

Three scenarios (Conservative / Moderate / Aggressive) representing differences in data readiness, adoption cadence, execution discipline, and (optionally) supplier participation.

Conservative bias

  • Overlap haircut: 15% reduction on combined sales-uplift + margin-gain GP to reduce double-counting.
  • Hours captured: hours returned are partially captured - not all time becomes cash.
  • Validation plan: outcome claims validated via store pilot using matched controls and difference-in-differences.
04

Role context - operational realities

Across retailers, the recurring constraints are remarkably consistent.

01

Decision latency cost

When insight arrives weekly or monthly, issues have already leaked sales and margin. Retail+ shortens that latency to hours.

02

Execution gap

Good decisions don't pay if store execution is inconsistent. Tasks + Lists explicitly target "nothing slips through the cracks".

03

Margin pressure

Small basis-point improvements applied to a large sales base become material profit. Margin bps is the dominant sensitivity.

04

Labour constraints

The opportunity is usually capacity unlock - better prioritisation, faster "truth checks", less ad-hoc reporting. Not headcount reduction.

05

Supplier relationships

Retailers want clearer, data-backed joint business planning - and optionally to convert reporting burden into governed supplier-paid access.

05

Feature → benefit → economic mechanism

5.1 Feature summary

Retail+ includes - at the time of writing:

Mobile, tablet & desktop Search & scan Home Real-time analytics Tasks Lists Spaces (Pro) Basket analytics Data trading Hank (Pro) Workflow recommendations Trend analysis Data marketplace Task collaboration (soon) Conversations (soon)

5.2 Benefits extracted

Feature Operational benefit Measurement type
Real-time analyticsFaster detection of drift; earlier correction of leakage; one version of truth.Time-to-insight; variance recovery rate
Search & scanTruth in seconds, in aisle and in supplier meetings. Less analyst dependency.Time per query; reporting hours avoided
Home screenPrioritisation and exception management - top / bottom / tasks / metrics.Daily review time; actions / insight
TasksConverts insight to accountable execution. Audit trail. Reduces slippage.Completion %; time-to-close
ListsStandardises workflows: delists, promos, stocktakes, gap checks.Promo readiness; rework rate
Basket analyticsImproves "profit per trip" - attach, bundles, promo profitability.Basket value / margin / profit
Spaces (Pro)Improves sales / GP density by reallocating space to higher-return bays.GP per sqm; endcap ROI
Data tradingOptional, governed supplier-paid access. New high-margin contribution line.Supplier uptake; contribution margin
Hank (bounded Q&A)Reduces friction to answer core trading questions. Increases decision cadence.Query cycle time; actions / answer
Hank scope constraint. This model assumes Hank reliably answers questions in the analyst-retrieval space - department declines, product margin queries, growth categories, top/bottom SKUs, rolling totals - not "open-ended magic". This aligns with the current Hank release.

5.3 Economic mechanisms

Benefit clusterPrimary leverHow value shows up
Faster exception detectionSales uplift, margin gain, hours returnedReduce time-to-correct leaks; expand review cadence; improve mix / promo decisions sooner.
Execution reliabilitySales protection, risk avoidance, hours returnedFewer missed promos, ticketing errors, delayed fixes; less rework.
Basket-quality optimisationSales uplift, margin gainImprove attach & bundles. Avoid "discount-only" promos. Lift GP per trip.
Space optimisationSales uplift, margin gainAllocate space to higher-return bays / endcaps. Improve profit density.
Supplier monetisationSupplier contribution marginSell governed insight access. Convert reporting burden into subscription-like contribution.
06

Financial & operational assumptions

6.1 Baseline assumptions

VariableValueConfidence
Revenue per storeA$30,000,000 / yearHigh
Retail+ subscriptionA$350 / store / month (A$4,200 / year)High
Baseline GM%27% (sensitivity 25–30%)Medium
Labour cost / hr (fully loaded)A$35 / hr (sensitivity A$32–A$40)Medium
Overlap haircut15% of (GP sales uplift + GP margin gain)Medium
Discount rate (NPV)8% (replace with your WACC)Medium
Adoption ramp (10 yrs)Y1 40%, Y2 70%, Y3 90%, Y4–10 100%Med–Low

6.2 Scenario input ranges

Driver Conservative Moderate Aggressive
Sales uplift (% of revenue)0.20%0.50%1.00%
Margin gain (bps on total sales)+5 bps+15 bps+30 bps
Hours saved weekly4 hrs8 hrs12 hrs
Hours capture factor30%50%70%
Compliance / risk avoided (EV)A$3k/yrA$10k/yrA$25k/yr
Supplier contribution margin (optional)A$5k/yrA$15k/yrA$40k/yr
07

Economic impact modelling

7.1 Impact areas

We quantify five impact areas (annual, per store):

  1. Sales uplift → incremental GP from incremental sales
  2. Margin gain → incremental GP from basis-point improvement
  3. Hours returned → monetised at labour cost × capture%
  4. Compliance / risk avoided → expected-value reduction
  5. Supplier contribution margin → optional, from governed access

7.2 Per-store annual impact

R = A$30,000,000; GM = 27%; labour = A$35/hr; overlap haircut = 15%.

Impact area Conservative Moderate Aggressive
Incremental sales (revenue)60,000150,000300,000
GP from sales uplift16,20040,50081,000
GP from margin gain15,00045,00090,000
Less: overlap haircut (15%)(4,680)(12,825)(25,650)
Captured hours returned value2,1847,28015,288
Compliance / risk avoided (EV)3,00010,00025,000
Supplier contribution margin (optional)5,00015,00040,000
Subtotal - gross value36,704104,955225,638
Less: Retail+ subscription(4,200)(4,200)(4,200)
Total - net annual value / store32,504100,755221,438
Interpretation. Even the Moderate case is only ~0.35% of annual sales in profit-equivalent value - consistent with Retail+ primarily reducing leakage and improving decision cadence, not creating a one-off transformation event.

7.3 Sensitivity - value per unit change

Using R = 30m, GM = 27%, overlap haircut k = 15%.

+10 bps margin gain → A$30,000 gross · A$25,500 net of overlap
+10 bps sales uplift → A$8,100 gross GP · A$6,885 net
+1 hour / week saved → A$1,820 gross · A$910 at 50% capture
+A$1,000 / year risk avoided → +A$1,000
+A$1,000 / year supplier CM → +A$1,000

Key takeaway: the model is most sensitive to margin basis points, then sales uplift, then supplier CM, then hours returned.

7.4 Moderate-scenario sensitivity (one-at-a-time)

Base Moderate total = A$104,955 / store / year.

ChangeNew totalDelta
Margin gain 15 bps → 20 bps117,705+12,750
Sales uplift 0.50% → 0.60%111,840+6,885
Hours saved 8 → 10 hrs/wk106,775+1,820
Hours saved 8 → 6 hrs/wk103,135−1,820
Capture 50% → 30%102,043−2,912
Overlap haircut 15% → 20%100,680−4,275
Sales uplift 0.50% → 0.40%98,070−6,885
Risk avoided 10k → 094,955−10,000
Margin gain 15 bps → 10 bps92,205−12,750
Supplier CM 15k → 089,955−15,000
08

Multi-store & long-term value

8.1 Annual impact at scale

Net of Retail+ subscription. Linear scaling shown for transparency.

StoresConservativeModerateAggressive
1A$32,504A$100,755A$221,438
5A$162,520A$503,775A$1.11m
10A$325,040A$1.01mA$2.21m
100A$3.25mA$10.08mA$22.14m
1,000A$32.50mA$100.76mA$221.44m

8.2 10-year cumulative impact

Adoption ramp: Y1 40%, Y2 70%, Y3 90%, Y4–10 100% (sum factor 9.0×).

Conservative
A$288k
10-yr undiscounted · per store
NPV @ 8%: A$185k
Moderate
A$903k
10-yr undiscounted · per store
NPV @ 8%: A$582k
Aggressive
A$1.99m
10-yr undiscounted · per store
NPV @ 8%: A$1.28m

8.3 Payback & ROI profile

Retail+ subscription is A$350 per store per month (A$4,200 per year per store).

ConservativeModerateAggressive
Annual benefit / storeA$32.5kA$100.7kA$221.4k
Payback period~1.6 months~0.5 months~0.2 months
Benefit-to-cost multiple~7.7×~24.0×~52.7×
09

Dependencies, risks & conditions

Preconditions to realise value

  1. Data readiness. Clean POS ingestion. Stable product hierarchy. Supplier mapping. Consistent promo identifiers.
  2. Operating cadence. Weekly exceptions review + monthly commercial review using the same views. Decisions must be routinised.
  3. Execution loop. Tasks & lists must be used and closed with evidence - not just created.
  4. Governance for supplier access. Permissions, aggregation rules, contracts, audit trails - before activation.

Risks & mitigations

Double-counting

Sales uplift and margin gain can overlap (mix, availability, promo effects).

Mitigation - overlap haircut + benefits ledger + pilot attribution.
Adoption

Dashboards without behaviour change yield little.

Mitigation - embed into rituals; make "Home → drilldown → task → closure" the operating rhythm.
Labour capture

Hours returned may not convert directly to cash.

Mitigation - track capacity unlocked separately from cash released; redeploy to higher-value work.
Supplier monetisation

Commercial upside depends on supplier appetite and governance.

Mitigation - treat supplier CM as optional; stage-gate with legal / privacy and clear packaging.
Feature delivery

Some features are explicitly marked "coming soon".

Mitigation - base ROI on the surface available today; treat the rest as upside.
10

Citations & evidence library

Benchmarks are used as plausibility bounds - headroom and mechanism support - not as guarantees.

2011

"Strength in Numbers"

Brynjolfsson, Hitt & Kim · 179 large firms · US

Supports "faster insight → higher productivity / output" directionality.

2003

ECR "Blue Book" on OOS

ECR Europe · Large observational base · Europe

Anchors that on-shelf availability is material and process-driven; supports sales-recapture plausibility.

Early 2000s

Out-of-stocks consumer response

Corsten & Gruen research stream · Global / meta

Supports that some OOS becomes truly lost sales; informs conservative recapture assumptions.

2000s

Execution & inventory accuracy

Raman, DeHoratius, Ton

Execution failures are common and profit-damaging; justifies tooling that closes the loop.

Multiple

Shelf / space response

Eisend meta-analysis; Drèze, Hoch, Purk field experiments

Space and layout interventions can move sales - informing the "Spaces" mechanism.

Public

AU grocery GM% context

Coles / Woolworths public reporting

Calibrates GM% for scaling uplift to GP$.

Public

AU wages & on-costs

Award wage references + statutory super

Informs labour value of hours returned.

Industry

Data monetisation margin proxies

Reuters / Deloitte-style ranges

Supplier-paid data access can be structurally high-contribution - governance-dependent.

11

Appendices

Appendix A · Raw formula spec

GP_sales = R × su × GM
GP_margin = R × mg
Overlap = k × (GP_sales + GP_margin)
Hours_value = h × 52 × w × cap
Total_annual = GP_sales + GP_margin − Overlap + Hours_value + risk + scm
Total_10y = Total_annual × Σ Adoption_t
NPV = Σ (Total_annual × Adoption_t / (1+r)^t)

Appendix B · Feature mapping matrix

FeatureSales upliftMargin gainHours returnedRisk avoidedSupplier CM
Real-time analyticsindirect
Search & scanindirect
Home screen-
Tasks-
Lists-
Basket analytics---
Spaces (Pro)---
Data trading--
Hank (bounded Q&A)-

Appendix C · Role-model cross-check

The role reports produce the following per-store annual ranges. This consolidated model sits within the envelope and uses an explicit overlap haircut + hours-capture factor for conservatism.

Role report Conservative Moderate Aggressive
CEO / Owner24,82059,050119,100
CFO40,780109,685227,090
COO27,83092,950201,820
Buying Manager39,440117,500242,400
Category Manager58,600169,340342,040
This consolidated retailer model32,504100,755221,438

Prove these numbers on your own data.

Apply for your personalised ROI estimate - finance-ready, with your inputs.