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StavBenShlomoBrowsiStav Ben Shlomo
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browsi rtd provider updates (prebid#6004)
* browsi rtd provider updates * browsi rtd provider updates * browsi rtd provider updates --------- Co-authored-by: Stav Ben Shlomo <stavbe@gobrowsi.com>
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dev-docs/analytics/browsi.md

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---
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layout: analytics
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title: Browsi
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description: Browsi Analytics Adapter
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modulecode: browsiAnalyticsAdapter
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gvl_id: 329
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prebid_member: true
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---
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#### Registration
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For more information about [Browsi](https://www.browsi.com), please contact [support@browsi.com](support@browsi.com).
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#### Example Configuration
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```js
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pbjs.que.push(function () {
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pbjs.enableAnalytics({
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provider: 'browsi',
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options: {}
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});
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});
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```
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---
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layout: page_v2
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title: Browsi Viewability Module
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display_name: Browsi Viewability
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description: Browsi Real Time Viewability
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title: Browsi RTD Module
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display_name: Browsi RTD Module
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description: Browsi Real Time Module
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page_type: module
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module_type: rtd
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module_code : browsiRtdProvider
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enable_download : true
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module_code: browsiRtdProvider
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enable_download: true
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vendor_specific: true
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sidebarType : 1
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---
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# Browsi Viewability Module
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# Browsi RTD Module
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{:.no_toc}
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* TOC
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{:toc}
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## Overview
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The Browsi Viewability module provides viewability predictions for ad slots on the page.
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To use this module, you'll need to work with [Browsi](https://gobrowsi.com) to get
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an account and receive instructions on how to set up your pages and ad server.
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Browsi’s RTD module for Prebid.js provides real-time insights and predictive signals to optimize bid requests and ad delivery.
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This module leverages Browsi's AI models to give publishers access to:
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-**Real-time predictions for GAM:** Enhance ad placements and maximize revenue by leveraging viewability and revenue predictions as key values in GAM ad requests.
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-**Enhanced bid request signals**: Augment bid requests with additional contextual, behavioral, and engagement signals to improve demand partner performance.
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-**Dynamic ad serving optimization**: Enable smarter ad delivery strategies based on predicted user behavior and page context.
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## Integration
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Implementation works like this:
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1. Build the Browsi module into the Prebid.js package with:
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1. Build the Browsi modules into the Prebid.js package with:
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```bash
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gulp build --modules=browsiRtdProvider&...
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gulp build --modules=browsiRtdProvider,browsiAnalyticsAdapter
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```
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2. Use `setConfig` to instruct the browser to obtain the viewability data in parallel with the header bidding auction
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2. Use `setConfig` to instruct the browser to obtain Browsi’s predictive signals in parallel with the header bidding auction
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## Configuration
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This module is configured as part of the `realTimeData.dataProviders` object:
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```javascript
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pbjs.setConfig({
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"realTimeData": {
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dataProviders:[{
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"name": "browsi",
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"params": {
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"url": "testUrl.com", // get params values
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"siteKey": "testKey", // from Browsi
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"pubKey": "testPub", //
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"keyName":"bv" //
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}
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}]
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realTimeData: {
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auctionDelay : 3000,
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dataProviders: [{
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name: "browsi",
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params: {
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url: "domain.com",
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siteKey: "SITE",
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pubKey: "PUB",
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waitForIt: true
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}
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}]
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}
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});
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```
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| params.siteKey |String |Site key| |
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| params.pubKey |String |Publisher key| |
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| params.url |String |Server URL| |
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| params.keyName |String |Key value name| Optional. Defaults to 'bv'. |
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| params.keyName |String |GAM key value name for the viewability prediction| Optional. Defaults to ‘browsiViewability’. |
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| params.waitForIt |boolean |Allow waiting for data| true |
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## Output
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For each ad slot, the module returns expected viewability prediction in a JSON format.
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When the data is received, it calls `pbjs.setTargetingForGPT` to set the defined `keyName` for each adunit.
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Example:
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```json
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{
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"slotA":{
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"p":0.56, // ad server targeting variable (e.g. bv) for slotA is 0.56
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},
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"slotB":{
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"p":0.824, // ad server targeting variable (e.g. bv) for slotB is 0.824
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}
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}
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```
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For each ad slot, the module generates predictive signals in JSON format, assigns key-value pairs for viewability and revenue predictions via `pbjs.setTargetingForGPT`, and embeds the full JSON in the bid request under `<bidder>.ortb2Imp.ext.data.browsi`.

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