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

# BigCommerce

> Integrate Mavera with BigCommerce — product review sentiment, customer attribute personas, and multi-channel content strategy

## Overview

Pull data from **BigCommerce** (Product Reviews, Customers with Custom Attributes, Multi-Channel Orders) → analyze with **Mavera** (Chat with structured output, Personas, Mave Agent) → get actionable brand health metrics, real-customer personas, and channel-specific content strategies.

<Info>
  **BigCommerce API** — Base URL: `https://api.bigcommerce.com/stores/{store_hash}/v3/`. Auth: OAuth via `X-Auth-Token` header. Rate limits: **150–450+ req/30 sec** (scales with plan tier; Standard 150, Plus 250, Pro/Enterprise 450+).
</Info>

***

## Prerequisites

<Steps>
  <Step title="BigCommerce API account">Create an [API Account](https://developer.bigcommerce.com/docs/start/authentication/api-accounts) in your BigCommerce control panel. Required scopes: `store_v2_products_read_only`, `store_v2_customers_read_only`, `store_v2_orders_read_only`. Save the generated Store Hash, Client ID, and Access Token.</Step>
  <Step title="Mavera API key">Get your key from [Mavera dashboard](https://app.mavera.io/settings/api-keys).</Step>

  <Step title="Environment variables">
    ```bash theme={"dark"}
    export BIGCOMMERCE_STORE_HASH="your-store-hash"
    export BIGCOMMERCE_ACCESS_TOKEN="your-access-token"
    export MAVERA_API_KEY="mvra_live_xxxxx"
    ```
  </Step>
</Steps>

***

## Jobs

| # | Job                                                                        | BigCommerce Data     | Mavera Surface           | Output                     |
| - | -------------------------------------------------------------------------- | -------------------- | ------------------------ | -------------------------- |
| 1 | [Product Review Sentiment → Brand Health](review-sentiment-brand-health)   | Product reviews      | Chat (structured output) | Sentiment dashboard data   |
| 2 | [Customer Custom Attributes → Persona Source](customer-attribute-personas) | Customer attributes  | Personas                 | Segment-based personas     |
| 3 | [Multi-Channel Performance → Content Strategy](multi-channel-content)      | Channel-level orders | Mave Agent               | Channel content strategies |

***

***

## Storefront ($284,500 | 1,240 orders | AOV $229)

* Content: Long-form product pages, comparison guides, video demos
* Messaging: Brand story + premium quality — highest AOV, buyers trust the brand
* Budget: 40% — owned channel with best margins
* Campaign: "Behind the Build" video series with loyalty program upsell

## Amazon ($192,300 | 2,100 orders | AOV $91)

* Content: A+ bullet-point content, infographic inserts, review solicitation
* Messaging: Social proof + competitive differentiation — price-sensitive shoppers
* Budget: 25% — listing optimization over external ads
* Campaign: Review campaign targeting 3-star reviewers with follow-up support

## Facebook Shop ($67,200 | 580 orders | AOV $115)

* Content: Carousel ads, short-form video, UGC reposts
* Messaging: Lifestyle-driven — products in context, not white backgrounds
* Budget: 20% — high growth potential, test aggressively
* Campaign: UGC contest "Show us your setup" with product credit prizes

## eBay ($31,800 | 410 orders | AOV $77)

* Content: Condition descriptions, competitive pricing tables
* Messaging: Value and reliability — eBay buyers expect deals
* Budget: 15% — maintain presence, clearance bundles for end-of-season

```

### Error Handling

<AccordionGroup>
  <Accordion title="Channel IDs vary by store">The channel IDs (1, 2, 3, 4) are examples. Fetch your actual channels with `GET /v3/channels` to get the correct IDs and names for your store configuration.</Accordion>
  <Accordion title="Order products sub-request volume">Each order triggers a sub-request for line items. For 10,000+ orders, pre-filter by date range (`min_date_created`) and sample. Use `X-Rate-Limit-Requests-Left` header to throttle dynamically.</Accordion>
</AccordionGroup>

---

## Rate Limits & Production Notes

| BigCommerce Plan | Rate Limit | Window |
|---|---|---|
| Standard | 150 requests | 30 seconds |
| Plus | 250 requests | 30 seconds |
| Pro | 450 requests | 30 seconds |
| Enterprise | 450+ requests | 30 seconds (negotiable) |

<Warning>
BigCommerce rate limits are **per-store**, not per-endpoint. All three jobs share the same quota. Use `X-Rate-Limit-Requests-Left` and `X-Rate-Limit-Time-Reset-Ms` response headers for dynamic throttling.
</Warning>

<Tip>
**Webhook-driven updates:** Configure BigCommerce [webhooks](https://developer.bigcommerce.com/docs/integrations/webhooks) for `store/product/review/created` and `store/order/completed` to trigger Mavera analysis in real time instead of polling.
</Tip>

**Production checklist:** Store credentials in a secrets manager. Paginate all list endpoints using `page` and `limit` params (max 250 per page). Retry on 429 using `X-Rate-Limit-Time-Reset-Ms` header. Cache catalog data locally. Monitor Mavera credits at [Dashboard → Usage](https://app.mavera.io/settings/usage). Run batch jobs off-peak to avoid competing with storefront API traffic.

---

<CardGroup cols={3}>
  <Card title="All Integrations" icon="plug" href="/integrations" />
  <Card title="BigCommerce API" icon="cart-shopping" href="https://developer.bigcommerce.com/docs/rest-catalog" />
  <Card title="Personas" icon="user" href="/features/personas" />
  <Card title="Brand Voice" icon="microphone" href="/features/brand-voice" />
  <Card title="Mave Agent" icon="brain" href="/features/mave-agent" />
  <Card title="Responses API" icon="comments" href="/features/chat" />
</CardGroup>
```