Real campaign case studies. Anonymized.
Six studies built only from what the source reports document: numbers, what they demonstrate and where they stop being reliable.
Clothing e-commerce: purchase campaigns at scale
Clothing e-commerce · Account D
- ₹45.83 LAd spend (purchase entries)
- 16,399Attributed purchases
- ₹279Cost per purchase
Clothing e-commerce: comparing creative formats with reported purchase value
Clothing e-commerce · Account E
- ₹9.39 LAd spend
- 2,510Attributed purchases
- ₹374Cost per purchase
Watch e-commerce: video-led purchase campaigns
Watch e-commerce · Account I
- ₹6.07 LAd spend (purchase entries)
- 1,907Attributed purchases
- ₹318Cost per purchase
Perfume e-commerce: catalogue carousel and video purchases
Perfume e-commerce · Account K
- ₹4.83 LAd spend (purchase entries)
- 1,526Attributed purchases
- ₹316Cost per purchase
Promo banners: near-identical spend, very different purchase costs
E-commerce (category not specified) · Account N
- ₹18,264–₹18,594Spend per entry
- 265–425Purchases per entry
- ₹44–₹70Cost per purchase
Where the budget actually went: concentration and dormant entries
Across all analysed exports · Account All
- 923Entries analysed
- 574Entries that spent
- 65%Top 10% of spending entries
About this data
What it is, how it was prepared and what it cannot tell you.
What the data is
Selected historical Meta Ads Manager reports from 14 different client accounts handled by AWEBZONE, 923 campaign, ad set or ad rows, of which 574 recorded spend. Reporting windows run from 7 Oct 2023 to 7 Nov 2026. This is a snapshot, not a live Meta Ads Manager connection.
How it was prepared
Rows were normalised, account summary rows were separated from campaign rows and never added to them, cost per result was re-calculated and matched the exports, and objectives were never combined. Client names, ad names, account identifiers and creative details were removed; entries carry only a random code, a business-category label, an inferred creative format and numbers.
How headline figures are calculated
Cost per purchase = total spend ÷ total attributed purchases in purchase-objective entries. ROAS = purchase conversion value ÷ spend, using only entries where value could be validated (359 entries, 65% of purchase spend). Value comes from three sources: reported directly, taken from the exported ROAS field, or derived from average order value × purchases where that relationship was proven in another export. Implausible values were excluded. Reach is never added across entries.
What it cannot tell you
Results are attributed by the platform, not independently verified sales. Attribution settings differ between exports and some do not state them. Creative format labels are inferred from ad names. The reports contain no lead-generation or traffic campaigns, so none are shown. The data does not represent every AWEBZONE client or every category, is not typical of any industry, and does not predict future results.
The ₹5 Crore+ figure
AWEBZONE’s ₹5 Crore+ cumulative advertising budget managed is a business-provided figure. The analysed reports (14 client accounts) total ₹1.51 Cr in spend and do not independently verify the full amount.
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