This is the  second part (2.3) of three part series on ‘Omnichannel Attribution Modelling’.  The series will cover:

  1. Attribution – Definitions / User Journeys
  2. Implementation – Type of Attributions / How they are tracked – 1. Multi Channel Tracking / 2. Cross Device Tracking / 3. Offline – Online Tracking
  3. Attribution and Attribution Roadmap – Industry Examples

We can only get deeper into attribution modelling after a complete omni-channel implementation is done for data collection.

Corresponding to these three models, firstly we have to implement viz:

  1. Multi channel tracking
  2. Cross device user tracking
  3. Offline tracking with Online

Omnichannel Tracking

In the last post we studied the Cross Device implementation, let’s begin now with the tracking of offline data collected along with the online.

In Offline-Online Attribution, we determine the impact of digital marketing channels on offline marketing channels and vice versa. We try to understand how online & offline campaigns work together to create conversions and how credit  for conversions should distribute  among different online & offline marketing channels. but to be able to have this capability first we have to take a complete view of your user journey online and offline.

User ids can be set for all of these authentication systems with the help of measurement protocol but the implementation is not going to be easy.

For all digital touchpoints covered until now, we have used ’login’ for the user authentication. However, in the real world a lot of transactions and interactions happen without the capturing the user data or atleast before capturing it. Other users’ authentication systems widely used for offline tracking are:

  1. Biometric identification (like retinal scan, fingerprint scan, iris recognition, voice recognition, Digital Signatures or Digital Signage, etc)
  2. Punching cards to record attendance (like attendance of employees)
  3. Wrist bands (like the one used by Disney)
  4. Retail loyalty cards (used by many supermarket chains)
  5. Online and offline Coupons

Depending on the businesses, the implementation model also has to be built and an accordingly custom reporting structure has to be setup and then combined.

If you use a variety of systems and tools to run your business, you can use Analytics to join and analyze that data in one place. For example, you can turn separate CRM data, ecommerce data, and Analytics data into a single comprehensive view of your business.

Data Import functionality by Google joins the offline data you’ve uploaded with the default hit data being collected by Analytics from your websites, mobile apps or other devices. The users’ on- and offline activity can be uploaded into GA interface by two methods:

  1. From the Analytics user interface, using the Admin > (Property) > Data Import option
  2. Using the Analytics Management API

Imported data can be used in reports, remarketing audiences alongside standard data collected by the website

Combining the data

ATMs, RFID tags, in-store traffic, kiosks, call centres, interactive voice response (IVR) systems, all generate a lot of offline data in non standard formats. The one basic challenge that occurs while doing this offline data mapping exercise is to unify the data. How would you combine the data together and make sense of the same user in online and offline activities? If you thought the answer to e a ‘primary key’ between two data sets, then you are right but it is the trickiest piece of the puzzle. The offline channels are multiple and there has to be one single way of making them coherent in one reporting structure.

How are you solving the problem of tracking online to offline tracking? What has worked for you? What did not? Comment on this and we shall discuss all the use cases that we can collect to offer a solution.


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