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Sample audit

This is what a Product Audit looks like

Data Octopus together with Echo (AI assistant) analysed the last 90 days of Google Ads product campaigns for a premium fashion store. The goal: stop guessing, start earning through product segmentation, product feed optimisation and ad account structure.

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  • Industry

    Fashion / Premium Fashion: clothing, footwear, luxury accessories and jewellery.

  • Customer profile

    Aspiring and affluent shoppers looking for premium brands and limited sneakers.

  • Competition

    Farfetch, Mytheresa and, in Poland, Moliera2 and Gomez.

  • Seasonality

    SS/AW collections, sales, Black Friday and the pre-Christmas peak.

Stage 01

Performance summary – last 90 days

Based on the data provided, here is the full picture of your business over the last 90 days. The store operates in the premium segment, which means high basket values and a selective customer profile. Key operating metrics show a strong market position, although — as the next stages show — some areas need immediate budget action.

Total revenue: PLN 6,796,937.74 of total revenue in the period analysed
0M
Budget spent: PLN 398,255.46 invested in ad campaigns
0K
Profit After Cost: PLN 1,640,790.20 net profit after ad costs
0M
Total SKUs: products in the catalogue, 35 unique brands, 5 categories
0
Average ROAS: return on ad spend — above the industry average
0
Average COS: Cost of Sale — ad cost as a share of revenue
0%
Stage 02

No Revenue segment

This is where your biggest “dormant” costs sit. As many as 4,381 products — 77% of the whole catalogue — earned not a single złoty of revenue. You invested PLN 121,269.08 in them, which is 30% of the total ad budget. That is pure operating loss that can and must be stopped.

77%of the catalogue with no revenue
30%of the budget spent on them
MetricNO REVENUELOWMID
Impression Rate1,612.674,453.006,047.72
Click Rate19.8163.3390.66
Budget Rate27.68 PLN88.43 PLN128.24 PLN

NO REVENUE products get almost 10 times less exposure (Impression Rate: 1,612 vs 15,026 for HIGH) than bestsellers. You pay for clicks that do not convert — probably because Google's algorithm “tests” them with too little budget per product, so it cannot gather enough data to optimise.

Framework #5Isolate zero-revenue products in a test campaign to see whether exposure or price is the issue.
Stage 03

Low, Mid and High segments

The segment data reveals a dramatic gap in efficiency between product groups. The HIGH segment far outclasses the rest, driving 89% of the store's revenue. The LOW segment, meanwhile, is currently unprofitable — its Profit After Cost is PLN -9,025.05, so every złoty spent advertising it loses money.

ROAS

  • HIGH33.81
  • MID10.66
  • LOW2.57

COS

  • HIGH3%
  • MID9.4%
  • LOW38.9%

Exposure

  • HIGH15,026
  • MID6,047
  • LOW4,453

MID – hidden potential

ROAS 10.66 but 2.5x less exposure than HIGH. Moving budget from LOW grows revenue without extra spend.

Framework #7Automatic labels: MID products above ROAS 15 move straight to the HIGH campaign.
Stage 04

Margin and Profit After Cost

Profitability after ad costs (Profit After Cost) shows a clear segment hierarchy. HIGH is the undisputed engine of the whole business, generating over PLN 1.6M in net profit. MID has real potential to scale with the right budget support. LOW and NO REVENUE together consume PLN 130,294.13 without an adequate return.

  • +PLN 1,644,894

    HIGH – the engine

    Protect exposure and budget from erosion.

  • +PLN 126,278

    MID – ready to scale

    Grow exposure with budget from LOW.

  • −PLN 9,025

    LOW – rescue or switch off

    Cut spend or run a price test.

  • −PLN 121,269

    NO REVENUE – loss

    Isolate in a test campaign.

Framework #12Import purchase costs, create a Real_Profit field and exclude negative-profit products regardless of ROAS.
Stage 05

Brands – top 10 by ROAS

The brand analysis reveals several key insights. VERSACE achieves an astronomical ROAS of 364.54 on a relatively low budget — a brand that needs scaling right away. SAINT LAURENT and GIVENCHY are revenue pillars generating over PLN 3.9M combined. The real “Rising Star”, though, is RALPH LAUREN, with ROAS 60.64 and an extremely low Impression Rate of just 551 — a classic case of underfunded potential.

BrandRevenue (PLN)Budget (PLN)ROASProfit After Cost (PLN)Impression Rate
VERSACE37,066.93101.68364.54+11,018.411,730
ARMANI85,614.371,144.8674.78+24,539.452,811.5
RALPH LAUREN68,289.661,126.1660.64+19,360.74551.93
DR. MARTENS160,788.886,056.0326.55+42,180.634,980.89
GIVENCHY1,654,505.7472,973.2922.67+423,378.438,444.54
SAINT LAURENT2,303,508.38105,896.0821.75+585,156.435,967.8
VALENTINO783,023.646,366.4716.89+188,540.612,222.33
BURBERRY665,674.8344,396.8514.99+155,305.64,409.95
BALENCIAGA871.5467.5112.91+193.95812.85
HERMES5,579.64436.5412.78+1,237.354,652.86

Revenue pillars

Saint Laurent

PLN 2.30M · ROAS 21.75 · +PLN 585K profit

Givenchy

PLN 1.65M · ROAS 22.67 · +PLN 423K profit

Valentino

PLN 783K · ROAS 16.89 · +PLN 189K profit

Framework #3Ralph Lauren: ROAS 60.64 with exposure of 551 is a rising star to scale.
Stage 06

Categories

Revenue by category is highly concentrated. Textiles dominate with an 85% share of revenue (PLN 5,806,099.89) and the highest ROAS at 19.21 — the undisputed foundation of the business. At the opposite end is Jewellery, with the lowest ROAS (8.24) and the highest CPC (PLN 1.99) in the catalogue, which calls for strict margin control and product-level profitability checks.

Revenue (PLN) by category

  • Textiles5,806,099.89
  • Jewellery412,286.04
  • Accessories313,012.45
  • Outerwear139,065.51
  • Footwear126,488.15
CategoryRevenue (PLN)Budget (PLN)ROASProfit After Cost (PLN)Impression Rate
TEXTILES5,806,099.89302,296.1219.21+1,439,533.854,697.71
ACCESSORIES313,012.4522,448.113.97+71,474.982,431.18
OUTERWEAR139,065.5111,114.1112.51+30,605.54862.8
FOOTWEAR126,488.1512,395.210.24+25,584.331,741.83
JEWELLERY412,286.0450,006.758.24+73,679.061,789.79

Budget vs. ROAS by category

Comparing ad spend with efficiency (ROAS) reveals a key imbalance: Jewellery absorbs PLN 50,006.75 of budget at a ROAS of just 8.24 — the worst input-to-output ratio in the catalogue. Textiles, by contrast, generate ROAS 19.21 on a budget of PLN 302,296.12, confirming their position as the most efficient investment category.

ROAS

  • Textiles · Budget 302,296 PLN19.21
  • Accessories · Budget 22,448 PLN13.97
  • Outerwear · Budget 11,114 PLN12.51
  • Footwear · Budget 12,395 PLN10.24
  • Jewellery · Budget 50,007 PLN8.24

COS (%)

  • Textiles5.21%
  • Accessories7.17%
  • Outerwear7.99%
  • Footwear9.8%
  • Jewellery12.13%
Stage 07

Summary and checklist

Your store has huge potential in premium brands but carries the “ballast” of NO REVENUE products, which eat 30% of the budget with no effect at all. Four key frameworks to roll out first will unlock hidden profitability and send budget where it earns a real return. Below is the complete priority checklist.

Action priorities

  1. 1ImmediatelyFramework #5: isolate No Revenue products.
  2. 2UrgentFramework #12: margin and negative Real_Profit exclusion.
  3. 3ImportantFramework #7: reallocate from LOW to MID.
  4. 4StrategicFramework #1: Meta Ads for bestsellers.

Stop the losses first (#5, #12), then scale what works (#7, #1).

Stage 08

Growth questions

To prepare a precise scaling strategy matched to your business goals, I need answers to a few key questions. Each one lets me calibrate the recommendations so they are not only effective but also safe for your cash flow. Answer any of the questions below and I will turn it into a concrete action plan straight away.

  • Target ROAS

    Which ROAS lets you scale budget safely?

  • Revenue goal

    What monthly revenue do you want this quarter?

  • Market expansion

    Planning new markets, e.g. Czechia or Germany?

  • Win back VIPs

    Recover customers from the RFM “Slipping Champions” segment?

Echo

What next with Echo?

Echo can map out the next steps right away:

  • Framework #5 setup

    The Zombie_Trial label and test campaign step by step.

  • Margin integration

    Import margin and auto-exclude negative Real_Profit.

  • Scaling Ralph Lauren

    How to lift exposure from 551 to top-brand level.

Ask Echo a questionSee all frameworks
Return on investment

An investment that pays back fast

A monthly cost of PLN 2,500 is only a fraction of the potential profit Data Octopus can unlock. The platform works like a skilled surgeon, precisely removing losses and maximising the return on every złoty spent. See how quickly the investment pays for itself.

  • Stop losses

    Over PLN 121,000 saved from the No Revenue segment.

  • Revenue growth

    Budget moved to premium brands such as Ralph Lauren and Versace.

  • Automation

    Auto-excluding negative Real_Profit saves time.

See pricing