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layout page_v2
title Browsi RTD Module
display_name Browsi RTD Module
description Browsi Real Time Module
page_type module
module_type rtd
module_code browsiRtdProvider
enable_download true
vendor_specific true
sidebarType 1

Browsi RTD Module

{:.no_toc}

  • TOC {:toc}

Overview

Browsi’s RTD module for Prebid.js provides real-time insights and predictive signals to optimize bid requests and ad delivery. This module leverages Browsi's AI models to give publishers access to:

  • Real-time predictions for GAM: Enhance ad placements and maximize revenue by leveraging viewability and revenue predictions as key values in GAM ad requests.
  • Enhanced bid request signals: Augment bid requests with additional contextual, behavioral, and engagement signals to improve demand partner performance.
  • Dynamic ad serving optimization: Enable smarter ad delivery strategies based on predicted user behavior and page context.

Integration

Implementation works like this:

  1. Build the Browsi modules into the Prebid.js package with:

    gulp build --modules=browsiRtdProvider,browsiAnalyticsAdapter

  2. Use setConfig to instruct the browser to obtain Browsi’s predictive signals in parallel with the header bidding auction

Configuration

This module is configured as part of the realTimeData.dataProviders object:

pbjs.setConfig({
   realTimeData: {
       auctionDelay : 3000,
       dataProviders: [{
           name: "browsi",
           params: {
               url: "domain.com",
               siteKey: "SITE",
               pubKey: "PUB",
               waitForIt: true
           }
       }]
    }
});

Syntax details:

{: .table .table-bordered .table-striped }

Name Type Description Notes
name String Real time data module name Always 'browsi'
params Object
params.siteKey String Site key
params.pubKey String Publisher key
params.url String Server URL
params.keyName String GAM key value name for the viewability prediction Optional. Defaults to ‘browsiViewability’.
params.waitForIt boolean Allow waiting for data true

Output

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.