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Getting Started with Measurement

LiveRamp’s measurement enablement solutions allow you to achieve a large variety of measurement goals, including the common goals listed below:

  • Develop a unified view of consumer activity

  • Gain insight into which combination of display ads, email marketing, and TV ad views led to the most in-store sales growth

  • Determine what types of consumers tend to purchase online after visiting your stores in person

  • Determine which ad platforms would be best to launch a new campaign to drive increased customer interactions

LiveRamp’s measurement enablement solutions allow you to join together previously-isolated sets of data (such as consumer attribute data, impression data, and conversion data) and disparate identities (such as PII, cookies, and mobile device IDs). LiveRamp measurement links all of the various data to RampIDs so that your company can confidently tie those datasets back to the same consumer identity.

By combining this data in one place, your company (or your measurement partner) can start the process of analyzing data. This might entail identifying purchasing trends and putting together a complete picture of audience behavior and media engagement. It might entail comparing ad exposures with a third-party dataset. This enables you to create a fully-realized and accurate portrait of consumer identity, which in turn allows for a more mature and comprehensive analysis of consumer purchasing and engagement.

Measurement Environment Options

Depending on your situation, combining this data and performing other measurement activities might happen in one or more environments:

  • Your environment: This process typically involves you creating and uploading files that we process using our File-Based Recognition workflow. Once the files have been transformed to include the associated RampIDs, we deliver them back to you.

  • Your measurement partner’s environment: This process involves you creating and uploading files that we process using our File-Based Recognition workflow. Once the files have been transformed to include the associated RampIDs, we deliver them back to your measurement partner.

  • A platform that participates in our Attribution Program: Certain platforms don’t allow impression data outside of their environment, but have attribution programs and integrations with LiveRamp that allow you to send us your conversion data, which we then match and then send to the platform. The platform then is able to tie together their impression data with your conversion data. Typically the platform either has an attribution dashboard in their platform or generates an attribution report. For more information, see “Conversions API Programs”.

  • Ads Data Hub: LiveRamp’s integration with Google’s Ads Data Hub enables you to leverage RampIDs as the join key between your data and the exposure data present in Ads Data Hub. For more information, see “Measurement Enablement for Ads Data Hub with LiveRamp”.

Creating a Measurement Audience

Before you start a measurement workflow, LiveRamp will typically need to create an audience for your data in Connect. Customers cannot create measurement audiences themselves in Connect.

To have LiveRamp create this audience, use the Set Up a New File-Based Recognition Workflow quick case to create a support case that includes the information listed in “Set Up a New File-Based Recognition Data Feed”.

Overall Measurement Processing Steps

Files that LiveRamp processes and then delivers back to you (or a measurement partner) through our File-Based Recognition workflow typically go through the following steps:

  1. Create the file: You make any necessary formatting adjustments to meet our file-formatting guidelines.

  2. Data upload: After you create the file, you upload your data (typically consumer data or transaction data) to LiveRamp.

  3. Matching: During processing, LiveRamp matches any personally identifiable information (PII) in your file to the offline data in the AbiliTec (offline) Identity Graph to link each record to an AbiliTec ID, and then converts this AbiliTec ID into a pseudonymous, universal identifier called a RampID. For files containing online identifiers, we match these identifiers to the corresponding RampIDs in our online graph.

  4. Anonymization: The data is pseudonymized by removing any PII. The data in certain columns might be hashed, encrypted, truncated or removed, to reduce the risk or re-identification or depending on your needs. The row order is randomized and (when we’re returning multiple RampIDs per record) a grouping indicator is added to each row.

  5. Delivery: The file is delivered to the location(s) you’ve specified.

This process typically takes 1-3 business days. Once the files have been uploaded, you can view the file’s progress on the Files page in Connect (for more information, see “View FBR File Info”).

Once you’ve retrieved the file, you can tie the data in the file to other files containing RampIDs.

Measurement Use Case Example

See the information below for an example of how a hypothetical company might use LiveRamp measurement enablement.

Acme Parka Company has just completed an ad campaign at The Trade Desk to promote sales of the company’s new line of winter gloves where they targeted a segment of their customers who previously made a purchase from them within a specified time frame. Now that the ad campaign has completed, Acme wants to see how much more likely someone was to make an online purchase after seeing their digital ad.

Acme has obtained an exposure file from The Trade Desk which includes mobile device IDs linked to the consumers who viewed their ad. They also have a transaction data file that contains records of purchases of winter gloves within a specific time frame linked to email addresses. The information provided in these files will help Acme gauge their digital ad campaign’s effectiveness. However, because each set of data includes a different set of identifiers (online identifiers with the mobile device IDs and offline email identifiers) Acme is struggling to find the overlap of their consumer identities between the files - they can’t see if any of the user devices targeted by their digital ad are the same users who made instore glove purchases.

To get their measurement enablement workflow started, Acme needs to create a LiveRamp support case requesting the creation of two new LiveRamp measurement audiences, one for each identifier type. These audiences need to be created before Acme can upload their measurement files to LiveRamp. Acme uses this link to utilize a Quick Case template with most fields pre-populated and with a template in the description field for them to fill in the required information. Acme enters the information in the template and then submits the case.

LiveRamp support provides Acme with the SFTP folder locations to use to upload their files. Acme ensures that they upload their exposure files (containing Mobile IDs) from The Trade Desk and the transaction data files (containing email addresses) to the exact folder locations provided.

Now that Acme has uploaded their files, they must wait up to three business days for the files to finish processing through the measurement workflow. Acme checks the My Files page in their Connect account to keep up-to-date on the status of the completed measurement files. Acme can review the date each file was received, the status of the file, the number of rows in the input file, and the recognition rate, or the percentage of rows in Acme’s inbound measurement file LiveRamp was able to match to specific RampIDs.

After three days, a member of the LiveRamp support team follows up on Acme’s new measurement audience ticket, and provides them with an SFTP location to pick up their completed measurement files. The SFTP location provided by the LiveRamp representative matches the SFTP location Acme initially provided when they first opened this support ticket with LiveRamp.

Acme retrieves their completed measurement files. The files have been stripped of their identifiers and those identifiers have been replaced with RampIDs.

Acme can now analyze the RampIDs that overlap in the exposure data file and transaction data file to gauge what percentage of their users who were successfully targeted by their digital ads made an instore purchase of their new winter gloves. Based on data provided in the outbound measurement files, Acme finds that the same users who viewed the digital ad made a purchase of winter gloves. Thanks to engaging this measurement enablement workflow, Acme has concrete evidence that consumer engagement with their ad drove sales for their new line of gloves.

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