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.

What it means: You can now manage access to specific tool pages (e.g., the full Attribution module vs. only its Billing sub-page) instead of all-or-nothing access.

- Navigate to Team Settings → select a team member → click the Access Control (shield) button to open a module tree view.

- Use "Select All Pages" for quick full access grants/revokes, or expand categories (via arrow) to toggle sub-permissions (e.g., let analysts access Attribution data but restrict them from billing settings).

- Changes take effect immediately (users may need a page refresh/logout for full UI updates).

What it means: Selecting a parent module (e.g., Retargeting) auto-selects its sub-features; deselecting a sub-feature marks the parent as "partially accessible." This prevents accidental over-granting of access.

What it means: Every team member can check their own access rights in read-only mode to avoid 403 errors or missing menu items.

We have added a critical template to address iOS 26’s privacy mode changes that remove Google’s gclid, wbraid, and gbraid parameters—plus Bing’s msclkid parameter—from ad tracking data.

Here’s what this means for you (no deep tech jargon required):

Why this matters: iOS 26’s privacy shifts risked blurring ad performance visibility for eCommerce brands. Our template ensures you keep leveraging actionable ad data without compromising compliance—so you can keep optimizing campaigns and growing revenue with confidence.

All Channel Attribution (our tool that maps which ads actually lead to orders, so you can avoid wasted spend on low-impact campaigns) now lets you select a "Compare to" filter with three new options: