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You can now view New Customer Revenue and Returning Customer Revenue in Attribution-All.

These metrics are optional and hidden by default. You can turn them on from the “Edit columns" selector.

The API documentation has also been updated accordingly.

AllyClaw now works across Claude, ChatGPT, and the Attribuly interface, so teams can analyze Shopify and ad account performance in the workflow that fits them best.

Connect your Shopify and ad accounts, add Attribuly API, install skills, and ask anything in your preferred workflow.

Try AllyClaw in Attribuly：https://app.attribuly.com/cherry/#/ally-claw

See how to connect Claude/ChatGPT to Shopify, Google Ads, and Meta：https://attribuly.com/how-to-connect-claude-to-shopify-google-meta/

Meet AllyClaw, an AI marketing operator for DTC brands powered by OpenClaw and built-in skills.

AllyClaw connects with your attribution data and helps analyze performance across channels, creatives, funnels, and customer behavior. It can surface profit-focused insights, identify wasted spend, and recommend next actions based on your marketing goals.

With AllyClaw, you can:

AllyClaw is built for modern e-commerce teams and works with attribution data from your existing stack.

You can now see how different channels contribute across the full customer journey, not just the final conversion step.

Touchpoints Analysis breaks each conversion path into three stages:

This helps you understand which channels introduce demand, which ones nurture it, and which ones close it.

The report is available in Attribution > Conversion Path, with a visual breakdown at the top of the page. Hover over each stage to view total value, active channels, top contributors, and calculation logic.

You can also switch the analysis between Channel and Campaign using the Dimension filter.

You can now identify traffic from AI assistants and AI search platforms such as ChatGPT, Claude, Perplexity, Gemini, Copilot, Grok, Kimi, and more.

When shoppers discover your brand, compare products, or get recommendations inside AI tools and then click through to your store, Attribuly can classify that visit as Agentic Shopping. This helps you separate AI-driven traffic from organic search, paid ads, social, email, and other channels.

How it works:

Attribuly detects Agentic Shopping mainly through:

For the most reliable reporting, we recommend using full UTM parameters, such as:

utm_source=chatgpt&utm_medium=agentic_shopping&utm_campaign=spring-launch&utm_platform=chatgpt

Once set up, you can validate it in real-time events or reporting and confirm the visit is classified as Agentic Shopping.

You can switch to Chinese or English by clicking on the language tab.

After selecting the Full Impact model, you can see which touchpoints in the customer journey are predicted by AI.

Google Analytics may lose some key data, so we have launched this feature.

Full-stack web analytics module for Acquisition, Behavior, and Conversion analysis, enabling end-to-end user behavior tracking from traffic source click to purchase completion

Cause & Effect core analysis model that categorizes user events into traffic source actions (Cause) and conversion results (Effect), with User ID-based correlation for accurate conversion attribution

Session & Engaged Session mechanism with 30-minute inactivity-based new session determination and multi-condition high-quality access identification (10s+ duration, >1 page depth, or critical cart/checkout events)

Comprehensive Traffic & Spend metrics including multi-channel cost aggregation (spend), unique session counting (total sessions), deduplicated user stats (unique users), and returning user tracking (returning users)

Unassigned is the value Analytics uses when there are no other channel rules that match the event data.