Release #10 - Product Analytics & more

Release Notes for: Sep 15 – Oct 31, 2025

These past few weeks we were focussed on making your analytics faster and more accesible, attribution smarter, and integrations more seamless.

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1. Product Analytics

You can now analyse performance at a product and SKU level. This includes data on channel attribution, discounted revenue and return rate. This should helps identify top-performing SKUs, optimise pricing, and evaluate marketing impact per product.

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2. UTM-Driven Manual Attribution

We have introduced a manual layer of attribution on top of our Algorithmic attribution. Users can now attribute unidentified UTM parameters to campaigns, ad groups, or channels.

The combined logic of Algorithmic (96%) + Manual (4%) ensures 100% attribution for all Orders.

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3. Ads Manager Updates

The Ads Manager now includes two new performance metrics - New Customer ROAS and Returning Customer Share - available across Campaign, Ad Set, and Ad levels. These metrics help you understand how effectively each campaign is driving first-time customers versus repeat buyers.

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4. Export Functionality across the Platform

You can now export your complete analytics data from BooleanMaths with a single click.

You can find these options on every chart/table in your Dashboards.

You can also find Export option for the data in Orders/Products features.

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5. CAPI Enhancements

We have migrated to event-based processing to ensure significantly faster syncs and improved Meta EMQ scores and Google CAPI reliability.

We have also added event filters for finer control on which events are sent via CAPI.

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6. Shopify App & Integrations

We have expanded Shopify Integration coverage to include for orders, products, collections, and inventory. we also added a daily sync that matches Shopify and BooleanMaths data automatically.

We have also added new Integrations with Google Analytics, Klaviyo, Bitespeed, BIK & more

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⚙️ Minor Updates

⚡ Influencer & Link Builder were optimised with loading times reduced by 95%.

💾 Visitor Tables have been optimised by decoupling dependent features and introducing a cache layer for recent visitors.

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