Release #13 - Ads Agent, CXO Dashboard, Geo Segments, Post Purchase Survey

Release Notes for: Jan 23, 2026 – Mar 16, 2026

In Q1 2026, we rapidly scaled our Analytics & Attribution capabilities. Our focus was on making profitability an integral part of the platform, while giving marketing teams more impactful and actionable data.

New Features

1. Post Purchase Survey

We have added a Post Purchase Survey module to capture customer self-reported attribution signals on the Thank-you page.

2. CXO Dashboard

We have launched a Home Dashboard for CXOs to customise a personal dashboard with key metrics across Ads, Attribution, Orders, and Profitability.

This dashboard enables comparisons across two time periods and allows users to show/hide and drag/drop metrics, choosing from 50+ available metrics.

3. Geography Analysis

Based on client requests, we have deployed Geo-level Analytics that analyses performance by country, state, city, and pincode, and enables quick-compare.

4. Ad Fatigue Agent

We have launched an Ads Fatigue Monitoring Agent that scans 20+ signals to highlight ads showing Early, Moderate, or Severe fatigue, along with recommendations.

5. Shopify App & Integrations

• New data integrations with shipping providers Clickpost and WareIQ

• Shopify Hydrogen now supported on BooleanMaths

• Added capability to read historical orders to improve New vs Returning accuracy, cohort retention, and data modelling

Major Updates

1. Navigation

A downside of adding new features was that the navigation was becoming cluttered. We have deployed a new and improved sidebar, with a clear feature hierarchy and quick search capability.

2. Channel Attribution Improvements

• Added download functionality for both order-level and summary-level data.

• Also introduced NC ROAS, NC-CPA, and additional New Customer metrics.

3. Profitability Analytics (P&L)

We have added CM1, CM2, and POAS metrics across Channels, Campaigns, Ad Sets, and Ads, making profitability measurement a default mode in BooleanMaths.

🔮 What’s Next

• Integrating profitability analysis across Product analytics

• Enhancing Product Analytics with collection-level summaries and comparative trend analysis.

• Proprietary Boolean Attribution, blending click data with customer survey responses, enabling brands to move from heuristic to factual attribution

• Audiences to power better targeting on ad platforms

• AI-driven insights layered on top of channel performance

• A Marketing Copilot, allowing users to ask natural-language questions about ad performance