📐 Methodology

How We Calculate Your Revenue Gap

Every number in our simulator is sourced, documented, and deliberately conservative. Here’s exactly how we built it, and why you can trust the results.

Last updated: February 2026 · 24 sourced references

01What the simulator measures

The Revenue Gap Simulator estimates the annual financial impact of deploying Samareo Shopping Guide on your e-commerce store. It computes two value drivers:

Value driver 1
Revenue Recovered
Additional sales from improved conversion rates through guided product discovery.
Value driver 2
Savings on Returns
Reduced return costs when customers find the right product the first time.

02Your inputs

The simulator uses four inputs. Two are entered by you, two are pre-filled from industry benchmarks and can be customized:

InputRangeDefaultSource
Monthly visitors1,000 – 2,000,000Industry-specificYou
Average order value€10 – €2,000Industry-specificYou
Conversion rate0.3% – 8.0%BenchmarkPre-filled
Return rate1.0% – 40.0%BenchmarkPre-filled

03The formulas

Current state: without Samareo

Current monthly sales    = Monthly visitors × (CR / 100)
Current monthly revenue  = Current monthly sales × AOV
Current annual revenue   = Current monthly revenue × 12
Current annual returns   = Current monthly sales × 12 × (RR / 100) × AOV

Projected state: with Samareo Shopping Guide

Guided CR                = CR × (1 + Guided Lift% / 100)
Guided monthly sales     = Monthly visitors × (Guided CR / 100)
Guided monthly revenue   = Guided monthly sales × AOV

Impact calculations

Annual revenue gain      = (Guided monthly revenue − Current monthly revenue) × 12
Return savings           = Current annual returns × (Return Reduction% / 100)

Total annual impact      = Annual revenue gain + Return savings

Worked example: Electronics & Appliances

StepFormulaValue
Monthly visitorsinput50,000
Average order valueinput€200
Conversion ratebenchmark1.8%
Return ratebenchmark9.0%
Guided Liftbenchmark+35%
Return Reductionbenchmark25%
Current monthly sales50,000 × 0.018900 orders
Current monthly revenue900 × €200€180,000
Current annual revenue€180,000 × 12€2,160,000
Guided CR1.8% × 1.352.43%
Guided monthly sales50,000 × 0.02431,215 orders
Annual revenue gain(€243K − €180K) × 12€756,000 /year
Current annual returns900 × 12 × 0.09 × €200€194,400
Return savings€194,400 × 0.25€48,600 /year
Total annual impact€756,000 + €48,600€804,600 /year

04Industry benchmarks

Each industry has its own conversion rate, return rate, guided lift, and return reduction values. All are set at the conservative end of documented ranges.

IndustryCRReturnGuided LiftReturn Reduction
Electronics & Appliances1.8%9.0%+35%−25%
Home & Garden1.8%14.0%+30%−22%
Fashion & Apparel2.2%26.0%+28%−30%
Sports & Outdoors1.8%12.0%+32%−22%
Beauty & Health2.5%7.0%+25%−18%
Automotive Parts1.4%12.0%+38%−30%
Toys & Games2.2%10.0%+30%−20%
DIY & Hardware1.5%9.0%+35%−25%
Lingerie & Intimate Wellness2.6%22.0%+38%−28%
Other (cross-industry)1.9%12.0%+28%−22%

05Why +25% to +38% conversion lift is conservative

Our guided lift values represent the relative increase in conversion rate when visitors use a Shopping Guide. Here’s what the research says, and why we use the bottom of the range:

SourceFinding
Forrester & GartnerProduct recommendations: up to +150% conversion
McKinseyPersonalization: +10-15% revenue, up to +25%
ShopifyRecommendations grow conversions up to +35%
Amazon35% of total revenue ($150B) from recommendations
Preezie (case study)Guided conversion: +246% CR increase
SalesforceRecommendation clickers: 4.5× more likely to buy

Our approach: Documented lifts range from +10% (McKinsey) to +246% (Preezie case study). We use +25% to +38%, consistently at or below the floor of published research. The simulator shows the minimum, not the maximum.

06Why −18% to −30% return reduction is conservative

When customers find the right product, they keep it. Returns overwhelmingly stem from product mismatch, not defects:

SourceFinding
McKinsey70% of online apparel returns from poor fit
CoreSight ResearchReturn reasons: 53% size/fit, 16% color, 10% damage
Rocket Returns (2025)AI fit tools: −27% size-related returns
Rocket Returns (2025)Virtual try-on: −34% fit-related returns
Rocket Returns (2025)Sizing guides + reviews: −31% returns
Rocket Returns (case study)Major retailer: 28.7% → 18.9% = −34% reduction

Our approach: Documented return reductions range from −27% to −34%. We use −18% to −30%. Beauty gets the lowest reduction (−18%) because its returns are already low. Fashion and Automotive get the highest (−30%) because fit and compatibility mismatches, which guided selling directly solves, drive the majority of returns in those categories.

07What we deliberately exclude

The simulator shows the floor, not the ceiling. These documented benefits are real but not included in the calculation:

📈
Increased AOV
Guided selling typically increases average order value by 5-30% through better cross-selling (McKinsey, Salesforce).
🛒
Reduced cart abandonment
70%+ of carts are abandoned (Baymard). Guided selling reduces purchase uncertainty, a top driver.
🔄
Customer lifetime value
Customers who find the right product come back. CLV improvement is documented but excluded here.
🎧
Support cost savings
Fewer “which product should I choose?” tickets when visitors can self-serve through a guide.
📦
Return processing costs
Each return costs €5-15+ in logistics, restocking, and depreciation, beyond the lost sale itself.
🔍
SEO & NPS value
Shopping guides create indexable content pages and improve satisfaction scores (+23% in case studies).

08Sources

Conversion rate benchmarks

  1. Statista – Online shopping conversion rate by industry, Q3 2024 (Salesforce Research) – statista.com
  2. IRP Commerce – All-industry average e-commerce CR 1.65% (2024) – cited in amasty.com
  3. SpeedCommerce – 2025 eCommerce Benchmarks by Industry – speedcommerce.com
  4. Smart Insights – E-commerce conversion rate benchmarks 2025 – smartinsights.com
  5. Blend Commerce – Shopify conversion rate benchmarks 2025–2026 – blendcommerce.com
  6. weDevs – eCommerce Conversion Rate Statistics 2026 – wedevs.com

Return rate benchmarks

  1. National Retail Federation (NRF) – 2024 Consumer Returns: 16.9% overall, ~20.4% e-commerce – nrf.com
  2. Statista – Most returned product categories – statista.com
  3. Opensend – Return rates by category (electronics 8–10%, home 15–20%) – opensend.com
  4. Rocket Returns – 2025 Complete Industry Analysis – rocketreturns.io
  5. Synctrack – 2025 Return Data by Category & Country – synctrack.io
  6. Upcounting – Average eCommerce Return Rate 2025 – upcounting.com

Guided selling & conversion lift

  1. Forrester & Gartner – Product recommendations: up to +150% CR – cited in threekit.com
  2. McKinsey – Personalization: +10-15% revenue, up to +25% – cited in threekit.com
  3. Shopify – Recommendations grow conversions up to +35% – cloudways.com
  4. Preezie – Guided conversion case studies (+246% CR) – preezie.com
  5. Salesforce – Recommendation clickers: 4.5× more likely to purchase – barilliance.com
  6. Envive – 52 Conversion Lift Statistics 2026 – envive.ai

Return reduction from guided selling

  1. McKinsey – 70% of apparel returns from poor fit – cited in threekit.com
  2. CoreSight Research – Return reasons: 53% size/fit – cited in trackingmore.com
  3. Rocket Returns – AI fit tools −27%, virtual try-on −34%, sizing guides −31% – rocketreturns.io

Market context

  1. Forrester – Commerce Search & Product Discovery Wave Q3 2023 – forrester.com
  2. Forrester – Agentic Commerce & Guided Selling (2025) – forrester.com
  3. Baymard Institute – Cart abandonment rate 70.19% – cited in multiple sources above

09Disclaimer

All benchmarks are industry averages. Individual store performance varies based on catalog depth, UX quality, traffic quality, and implementation. The simulator assumes the guided lift applies to all site visitors as a blended impact. Return savings reflect merchandise value only, not logistics costs. Results are projections based on published third-party research, not guarantees.