How to enable your marketing team

A customer 360 includes every interaction a customer has with your business right from the lead stage to post becoming a paid member.
Last updated:
May 17, 2023
Tarush Aggarwal

Tarush Aggarwal

Founder and CEO

A customer 360 includes every interaction a customer has with your business right from the lead stage to post-becoming a paid member. This is fundamental in allowing your marketing team to track user behavior during the customer journey. The majority of marketing teams fail because they do not have the correct feedback loop to help them measure the impact of the decisions they make. Today, we are going to go over the different steps needed to create a customer 360.

Define a list of all the activities

What are all the different steps in the customer journey?(even if they sound trivial). Do this across the entire journey – from an anonymous visitor all the way to a paid member.

How you will track each activity

Figure out the ones you are tracking today. For the ones not tracked, create a plan on how you can track them. Tracking them in your backend database or a frontend tracking tool are usually the best options.

Ingest the data

Ingest this data into your data warehouse. Pro tip: Use a fully automated data pipeline tool to do this instead of building your own pipelines.

Structure into a usable data model

Once you have the raw data inside your warehouse, you can now combine it into a well-structured data model.

Build out your customer journey

Work with the marketing team on understanding the different user flows and build out the right reporting for each different user flow.

Consider a tool or service

If you don’t have the technical expertise to do this, consider using a service like 5X which can set up and maintain this for you.

Remove the frustration of setting up a data platform!

Building a data platform doesn’t have to be hectic. Spending over four months and 20% dev time just to set up your data platform is ridiculous. Make 5X your data partner with faster setups, lower upfront costs, and 0% dev time. Let your data engineering team focus on actioning insights, not building infrastructure ;)

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