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@financial-times/ads-permutive
Advanced tools
A library to easily integrate Permutive functionality with FT-owned webpages.
This component will integrate Permutive's Data Management Platform functionality onto a website. Specifically the component will do the following:
FT.com specific documentation from Permutive
This package is available on npm.
npm install --save @financial-times/ads-permutive
We're currently investigating the possibility to setup Permutive via GTM across FT.com.
ads-permutive
would still expose the setup()
method for certain use cases.
import adsPermutive from '@financial-times/ads-permutive'
adsPermutive.identifyUser({ uuid })
Configure and initialise the permutive instance (see above for details).
Example:
adsPermutive.setup()
setup()
takes an argument configOptions
, where the only supported option is currently eventsCacheLimitBytes
.
Example: limit the events cache to 12 kB.
adsPermutive.setup({
eventsCacheLimitBytes: 12e3
}
See Limiting the events cache storage
It loads the Permutive script. This needs to be executed by any app that needs to be load the Permutive script programmatically. It can be run after setup has been executed.
Example:
adsPermutive.setup()
adsPermutive.loadPermutiveScript()
Use if you wish to make use of Permutive's User Identity Matching features whereby Permutive's unique user ID can be mapped to first-party User IDs. This would be needed for cross-device User matching for example. See UserIdentityV2 in adsapiv2_schema.
Name | Data-structure | Required? | Notes |
---|---|---|---|
uuid | Object | yes, see notes | Required if cross device user matching is required |
Example:
adsPermutive.identifyUser({
uuid,
})
Send metadata about the current request to permutive. All data-points are optional; however the schema is fixed, meaning that any data passed that is not in the format specified below will be rejected.
Any data-point below may be omitted if it is not available or not relevant for the page request. See Schemas.
Example:
adsPermutive.trackPageView(targeting, options)
Example: transform data from n-ads Data Manager format. See n-ads Data Manager schema here
import { fetchAdsData } from '@financial-times/n-ads'
const adsData = await fetchAdsData({ user = true, page = true })
if (adsData && adsData.metadata) {
adsPermutive.identifyUser(adsData.metadata.user)
}
where targeting
accepts targeting data in the Permutive's PageView schema specified here.
and options
accepts the following optional parameters.
mappingFunc
, a function used to map the input targeting metadata to data matching the PageView's schema.Alternatively the data can be formatted into a PageView event by using one of the exposed formatters: fromAdsApiV1ToPageView()
, fromAdsApiV2ToPageView()
, fromAdsDataToPageView()
,
Example: transform data from n-ads Data Manager format. See n-ads Data Manager schema here
import { fetchAdsData } from '@financial-times/n-ads'
const adsData = await fetchData({ user = true, page = true })
if (adsData && adsData.metadata) {
const pageViewData = adsPermutive.fromAdsDataToPageView({
...adsData.metadata,
rootId: getRootID(),
type: appContext.get('appName')
})
adsPermutive.trackPageView(pageViewData)
}
Example: transform data from Ads API V1 format. See Ads API V1 schema here
const pageView = adsPermutive.fromAdsApiV1ToPageView(adsApiV1Data)
adsPermutive.trackPageView(pageView)
Example: transform data from Ads API V2 format. See Ads API V2 schema here
const pageView = adsPermutive.fromAdsApiV2ToPageView(adsApiV2Data)
adsPermutive.trackPageView(pageView)
The mapping functions can be used as follows.
Example: transform data from custom format
adsPermutive.trackPageView(targeting, {
mappingFunc: myMappingFunction
})
Track an event in Permutive.
Example:
adsPermutive.trackEvent(eventName, trackingInfo)
Send metadata about the video play progress to permutive. All data-points are optional; however the schema is fixed, meaning that any data passed that is not in the format specified below will be rejected. Any data-point below may be omitted if it is not available or not relevant for the page request.
where videoTracking
currently accepts the following VideoEngagement
schema.
Name | Data-structure | Required? | Notes |
---|---|---|---|
campaign | String | no | ad campaign |
createdAt | String | no | created time |
duration | Integer | no | video duration in seconds |
title | String | no | video title |
videoId | String | no | video id |
progress | Float | no | video progress |
and client
data points are added automatically by the Permutive SDK.
Example: tracking the VideoEngagement event
adsPermutive.trackEvent('VideoEngagement', {
campaign: 'FT Rethink',
createdAt: '2019-05-22T11:00:00+00:00',
duration: 200,
title: 'DYSFUNCTIONAL: exploring sustainability through design',
videoId: 'WBtgMM3qLhg',
progress: 0.5,
})
The PageView
events sent by ads-permutive to Permutive are conformant to the schema defined in Permutive Event Schemas - see the Events section on the Permutive Dashboard.
ads-permutive stores locally the PageView schema.
Every time trackPageView(eventData, options)
is called, ads-permutive checks the input eventData against the PageView
schema stored locally and filters the data that conforms to the schema.
ads-permutive offers utilities to convert data from n-ads Data Manager, Ads API V1 User and Content or Ads API V2 User and Content into PageView events. See Using a formatter.
Please be aware that limiting the size will decrease the lookback window on the data we can use for segmentation, i.e. how much historical data is available to determine the result for new segments.
How the events storage size gets used is by writing all events into the available space. As soon as this cache is filled it will push out the oldest events to replace with new events.
This will happen exactly the same in any deployments.
The default eventsCacheLimitBytes
is 2.5MB, therefore by reducing the eventsCacheLimitBytes
to 1MB, the amount of available lookback window will be 3/5 smaller.
On average we store on average about 1000 events per 1 MB (1kB per event)
Example On average FT users over March 2020 saw this behavior:
Assumptions:
Pageview
So with limiting the localStorage to 1MB, we will be limiting the history to about 1000 events, or 90 pageviews. Given your last March 2020 history, on average a user has viewed 20 pageviews in a month.
So on average, your effective lookback will be 90/20 = 4.5 months.
Looking into this some more, we can see that the average is skewed by some highly engaged users so the lookback window on average should be even greater.
Given this, it shouldn't have a strong effect lowering the Permutive events cache limit.
FAQs
ads-permutive =================
We found that @financial-times/ads-permutive demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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