Data onboarding is the process of taking an offline data set and translating it into a data set that can be used in digital environments
Data onboarding is the process of taking an offline data set and translating it into a data set that can be used in digital environments. Onboarded data is typically used for marketing use cases.
How does it work?
Data onboarding connects offline customer data to online identifiers by taking pseudo-anonymous personally identifiable information (PII) from offline customer records and matching it to online identifiers such as mobile ad IDs and cookies to find the same customers online.
Data onboarding involves ingesting an offline data set, pseudo-anonymizing the offline data, matching the offline data to online data, and distributing the matched online data.
1. Upload & anonymize offline customer data
Data onboarding begins with an offline data set.
The offline data set is stripped of PII and assigned secure identifiers. Offline customer data is anonymized before matching to online identity data so that first-party customer PII is never exposed to other parties.
2. Connect to online identity data
Anonymized customer data is matched to online identifiers, such as mobile ad IDs and cookies, supplied by data providers.
3. Send onboarded IDs to destinations for activation
Online identifiers mapping back to the offline customer data set can be delivered to ad platforms and other business systems for targeting.
Using Onboarded Data
Boost media reach
By appending new identifiers to companies' first-party data, companies gain additional touch points to reach their customers and prospects across devices and channels.
By bringing offline data online, companies can ensure that they are delivering the most relevant messages to their audiences, boosting conversion rates and lowering acquisition costs.
Measure omni-channel performance
Combining offline and online data offers a complete view of customers and prospects across offline and online channels.
Translating offline data sets to offline data sets allow for omni-channel analytics. Instead of looking at touch points with customers as happening either offline or online, companies can now understand how offline and online interact and influence each other.
Challenges in Data Onboarding
Offline customer records often are keyed on personally identifiable information. Sharing those records creates some risk that the information might represent a breach of various privacy statutes. This risk is mitigated by cryptographically hashing records before onboarding them.
Data onboarding services are looking across billions of records to match the offline identifiers with their online counterparts. This has often led to a multi-day turnaround time, making it hard to do any just in time onboarding.
Data onboarding services are often expensive and require long term commitments, making them unfeasible for programs that aren't always on or for performance advertisers who have strict ROI goals. Further, some onboarding services charge for records even if they were unable to match them, creating a situation where users of the service struggle to estimate cost and/or ROI.
Most onboarding services act like a black box. Customer records go in and matches come out, but the underlying matching techniques, supply sources, and quality controls are completely opaque to the end user.
Data onboarding is an important tool for any digital marketer whose company also has offline relationships with their customer. Onboarding allows to bridge the offline and online identities, empowering the marketer to talk to their customer independent of where they are.