> ## Documentation Index
> Fetch the complete documentation index at: https://docs.hibonsai.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Analytics

> Use Sales, Performance, and Behavior to understand outcomes, improve experiences, and discover shopper needs.

Analytics gives your team three complementary views of the shopping experience.

* **Sales** shows commercial outcomes.
* **Performance** highlights how shoppers engage with results.
* **Behavior** helps you understand what people are trying to do.

Use them together: a change in sales is easier to interpret when you can also see changes in activity, intent, and engagement.

## Sales

Understand the orders and revenue associated with your Bonsai experiences, then explore the products, markets, and visitor groups behind them.

![Clean Shot 2026 10 21 At 2 55 51 Pm@2x](https://mintcdn.com/bonsai-fa04a9b1/Vm-GQMes7woeY2aC/images/CleanShot-2026-10-21-at-2.55.51-PM@2x.png?fit=max\&auto=format\&n=Vm-GQMes7woeY2aC\&q=85\&s=08ef42cea24811611557f33e9dd77e5c)

### Questions you can answer

* **Did revenue change because of more orders or larger baskets?** Read order count alongside average order value.
* **Which products and markets account for the change?** Explore the product and location breakdowns to find where the movement is concentrated.
* **How does revenue differ between new and returning visitors?** Use the visitor split to understand the mix, remembering that visitor history is different from purchase history.

![Clean Shot 2026 10 21 At 2 58 22 Pm@2x](https://mintcdn.com/bonsai-fa04a9b1/Vm-GQMes7woeY2aC/images/CleanShot-2026-10-21-at-2.58.22-PM@2x-2.png?fit=max\&auto=format\&n=Vm-GQMes7woeY2aC\&q=85\&s=bac848a46043a5416c2287a397ec9c05)

**Put it to work:** if revenue rises while order count stays similar, investigate product mix and average order value before assuming more people are buying. Use what you find to choose products or markets for closer review.

Sales reports use credited orders. Revenue is gross, including tax and shipping, without deducting refunds. These reports describe attributed outcomes rather than proving sales lift. [Review the definitions](/project/docs/bonsai-analytics/definitions.md).

## Performance

Find opportunities to improve how shoppers discover products and move toward a purchase. Review result engagement, weak-answer signals, and conversion trends for the experience you want to assess.

![Clean Shot 2026 10 21 At 2 56 18 Pm@2x](https://mintcdn.com/bonsai-fa04a9b1/Vm-GQMes7woeY2aC/images/CleanShot-2026-10-21-at-2.56.18-PM@2x.png?fit=max\&auto=format\&n=Vm-GQMes7woeY2aC\&q=85\&s=da4313902c945bc733031a9aa0a336b6)

### Questions you can answer

* **Are shoppers engaging with the products they are shown?** Review click-through alongside the volume of eligible sessions or conversations.
* **Where might product discovery be falling short?** Use weak-answer and no-result signals to identify areas for catalog, content, or query review.
* **Is the experience improving over time?** Compare the same experience and metric across comparable periods, then inspect examples behind a change.

![Clean Shot 2026 10 21 At 2 58 22 Pm@2x](https://mintcdn.com/bonsai-fa04a9b1/Vm-GQMes7woeY2aC/images/CleanShot-2026-10-21-at-2.58.22-PM@2x-1.png?fit=max\&auto=format\&n=Vm-GQMes7woeY2aC\&q=85\&s=df5283769f6c9a77163a85f6807ee4f1)

**Put it to work:** if engagement falls while activity stays steady, investigate whether the results and product information still meet shopper needs. A no-click outcome is a reason to investigate, not proof that the answer failed.

Compare each experience with its own history. Search and Concierge conversion use different denominators and windows.

## Behavior

Learn how shoppers express their needs and engage with Search and Concierge. Activity, intent, query types, and conversations provide context for what your customers want from the experience.

![Clean Shot 2026 10 21 At 2 56 41 Pm@2x](https://mintcdn.com/bonsai-fa04a9b1/Vm-GQMes7woeY2aC/images/CleanShot-2026-10-21-at-2.56.41-PM@2x.png?fit=max\&auto=format\&n=Vm-GQMes7woeY2aC\&q=85\&s=96dcdd26115107ed9d00f2f786809e24)

### Questions you can answer

* **Are shoppers naming products or describing a need?** Use query types and intent categories to understand how they approach discovery.
* **Are conversations developing into useful exchanges?** Review replies, message activity, and handoff demand alongside the underlying interactions.
* **When is activity highest?** Use peak hours to inform campaign timing or support planning, converting UTC into your operating timezone.

**Put it to work:** if shoppers increasingly describe needs such as “a bonsai tree for a small apartment,” review whether product descriptions explain size, placement, and care requirements clearly. Use engagement signals to evaluate the response rather than assuming longer queries mean greater trust.

## Take the next step

> **[Identity Mesh](/project/docs/bonsai-analytics/identity-mesh.md)**
>
> Explore the connected journey behind an AI referral or repeat visit.

> **[Journeys](/project/docs/bonsai-analytics/funnels.md)**
>
> Investigate where sessions stop progressing toward a purchase.


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