Skip to main content
Log in


Customer 360 - What Is It And Why Is It Important?

Learn why companies are adopting Customer 360 and how you can use this framework to create personalized customer experiences across your business.

Luke Kline.

Luke Kline

November 18, 2022

12 minutes

Image of Customer 360 Framework.

Today there’s more data in the world than ever before. The level of sophistication and the rate at which companies are collecting data is astronomical, and it’s only just getting started. In fact, according to a recent survey by Matillion, the average company has 400 external data sources and 20 percent of all companies have more than 1,000 data sources. With so many disparate systems it’s no wonder why every industry vertical is trying to adopt a Customer 360 motion.

What is Customer 360?

Customer 360 is a framework that seeks to consolidate all of your customer insights across all of your data sources and integrate them into one centralized location, thus giving you an all-encompassing 360-degree view of your customer, and creating a competitive advantage for your company.

The ultimate goal of Customer 360 is to eliminate fragmented and siloed data and create a single customer data hub so you can build personalized and connected customer experiences and optimize your business processes.

At its core, Customer 360 ensures that every person in your company is working off of the same unified customer view. Customer 360 is all about integrating your various datasets together and giving your business teams access to that data in the tools they rely on every day.

Why Are Companies Adopting Customer 360?

Companies have been trying to build a 360-degree customer view for years, but making this a reality is challenging for many reasons.

Multiple Data Silos

Your sales team lives in your customer relationship management (CRM) platform, your product team lives in your production database, your marketing team lives in your lifecycle/email marketing tool, and your success team lives in your customer support tool.

Each one of these platforms shows a slightly different view of your customer. Your CRM houses key historical and demographic data on your prospects, customers, and deals; your production databases have critical behavioral data from your app/website; your marketing tools have all of your audience cohorts and campaign data; and your support tools have critical customer service and ticketing data.

None of these data sources have insight into the other, and any time one of your business teams wants to ask a key question or access any of this data, they’re forced to hop back and forth between siloed systems. In many cases, a large portion of the data they need is inaccessible and locked behind a tool they can’t even access. Customer 360 eliminates data silos and ensures your business teams have access to the data they need.

No Single Source of Truth

When every data source in your technology stack has a slightly different view of your customer it creates misalignment because each of your business teams are actively looking at your customers through a different lens.

To be specific, there’s no standardized definition for your customer. And while each of your teams should be using a different subset of your data, all of them should have access to the same data. Without a single source of truth, you can never fully trust that your data is accurate or up-to-date, and this can lead to negative implications.

Analytics and Metrics

“Having all of your customer data accessible in one place gives you the ability to draw correlations between previously inaccessible datasets and define a core set of metrics for your customers,” explains Lourenço Mello, Product Marketing at Snowflake. When all of your customer data is in a centralized location your data team can splice and dice it to build relevant data models (e.g., lifetime value, churn rate, likelihood to purchase, etc.), identify new business opportunities, and answer key questions like:

  • Which customers have used X feature in the last week
  • When did user X last login?
  • How many active users does company ABC have?

All of this allows you to make predictions about your customers, so you can not only better understand their behavior but also use that data to inform your decision making.

Personalized Experiences

When all of your business teams have access to the same data, they can build personalized customer experiences for the entire customer journey, whether that’s sending an automated onboarding email every time a new user signs up, sending a promotional email once an account has exceeded its product usage threshold, or giving your sales team access to critical product usage data so they can personalize their outreach to generate more pipeline. Without a 360-degree view of your customer, all of this is impossible.

Challenges with Customer 360

The reason building out a 360-degree view of your customer is so hard largely comes down to two key factors, data centralization, and data activation.

Data Centralization

Today most companies are actively migrating all of their customer data to a centralized data platform like Snowflake, Databricks, or Google BigQuery for advanced analytics, artificial intelligence, and machine learning workloads. These analytics tools have become the standard for data engineers and analysts when it comes to storing, transforming, and modeling huge quantities of data at insanely fast speeds.

Aggregating and consolidating all of your customer data into a single centralized platform is no easy task. Depending on the number of data sources in your company, it can quickly become very time-consuming and expensive for your data team, as every data source in your stack requires a custom pipeline directly to your warehouse.

This is exactly why fully managed data ingestion platforms like Fivetran which offer hundreds of data connectors have risen to such prominence. They remove the burden of building and maintaining pipelines so your data team can focus on what matters most.

On a similar note, dedicated transformation and modeling tools like dbt have made it easier than ever before to automate and schedule your transformation jobs as soon as your data arrives in your warehouse–thus ensuring all of the data models powering dashboards are constantly being refreshed with clean and relevant data.

In fact, it’s probably safe to say that most companies today either have either consolidated all of their customer data into a centralized data platform or they're actively in the process of doing so.

Data Activation

Getting all of your data into the warehouse is only the first half of the problem. Having a comprehensive customer profile is only useful if you’re able to activate that data in your downstream business tools and that means you’ll inevitably need a way to sync your data to your various business applications and this is only possible through Data Activation.

If you’re not able to move data out of your warehouse, you’ve simply just created one big data silo rather than many individual silos. The problem is, moving data out of your warehouse introduces many of the same complexities that come with building and maintaining ELT pipelines.

In addition to this, you’re forced to integrate with various third-party APIs every time you want to send data to an end destination. Sending data to a CRM solution like Salesforce is not nearly as simple as using ELT to load data into your warehouse. If you make a mistake you can’t simply wipe away your database and re-ingest your data. Most tools used by sales, marketing, and support teams don’t have a time-travel feature, and that means there’s no undo button if you accidentally override critical fields.

Many companies try to solve this problem by downloading/uploading manual ad-hoc CSVs every time a business team makes a request. The problem with this method is that it’s a manual process that has to be done on a consistent basis and this often eats into the valuable time that your engineers and analysts could spend optimizing your infrastructure or uncovering new insights. To make matters worse, it can sometimes take days or weeks to get a CSV, which means the data is often already stale by the time it gets into the hands of your business teams.

To fully take advantage of your warehouse and the 360-degree view of your customer, you need to be able to democratize that data to your business teams in real-time, otherwise, you’re missing out on the huge impact each division could be having on your business.

Customer 360 Use Cases

It’s relatively easy to see the implications of a Customer 360 motion, but what does that actually look like in practice? Here are a few examples of some real-life examples:

  • Your sales team wants to automate and optimize their outbound motion with product usage data from your website/app (e.g., pages viewed, last login date, active workspaces, new users, etc.) and prioritize leads/accounts using a scoring system.
  • Your marketing team wants to lower your customer acquisition costs (CAC), by retargeting shopping cart abandoners and identifying potential lookalike audiences in Google Ads.
  • Your customer success team wants to know what customers are at risk of churning so they can take preventive measures and improve the ticket prioritization of your customer accounts.
  • Your product team wants to build hyper-personalized customer experiences for different industries (e.g., retail, healthcare, software, etc.) in your app and website.

It’s not possible to do any of this without a complete customer view. None of these questions can be answered unless your data is available in one place. Your data analysts can answer all of these questions and build the necessary audiences relatively quickly, but making this data available to your business teams is not so straightforward. At the end of the day, your business teams don’t want to be beholden to your data team; they want to self-serve and that means answering their own questions and building/defining their own custom audiences.

Customer 360 Tools

Plenty of options have risen up to tackle the concept of Customer 360, but few of them have been able to successfully address the entire problem because the core challenge with Customer 360 lies with data integration and figuring out how to sync data to your downstream systems.

Integration Platforms as a Service (iPaaS)

iPaaS tools automatically integrate directly with most third-party applications. They give you the ability to build point-to-point integrations between your various SaaS applications and systems (e.g., sending data from Salesforce to Hubspot.) However, iPaaS tools only let you send data once a key event that you define has been triggered (e.g., creating a contact in Hubspot after a deal has been created in Salesforce.)

All iPaaS tools are based on workflows. For every point-to-point integration between your systems, you have to build a complex workflow with multiple if/then statements with layers of complex steps and dependencies in between. These tools can work great for simple use cases, but for anything complex, they quickly become a nightmare to maintain.

A diagram showing point-to-point iPaaS connections

Point-to-Point iPaaS Integrations

Customer Data Platforms (CDPs)

CDPs are probably the most well-known technology when it comes to Customer 360. These platforms allow you to aggregate and transform all of your customer data in a central platform and sync that data to the destination of your choosing. Although CDPs have an assortment of audience-building features, they’re more commonly used for event tracking. That is to say most CDPs offer snippets of code you can run on your website/app to capture critical behavioral data.

One of the core problems with CDPs is that the platforms are relatively rigid and you’re limited to the features of the platform. You’re not able to attain a complete view of your customer unless your pair your CDP data with data from your warehouse and this means you’ve inevitably forced to pay for an additional layer of storage even though all of the data you need is likely already available in your warehouses. In addition to this, implementing a CDP can take upwards of six months.

A diagram showing a CDP

CDP Architecture

Reverse ETL

Reverse ETL is the underlying technology that powers Data Activation and it solves both of the problems with the previous two platforms. Rather than forcing you to manage numerous point-to-point integrations or pay for another layer of storage, Reverse ETL runs on top of your warehouse and syncs that data directly to your end destination.

Since Reverse ETL simply queries against your data warehouse, you can leverage all of the existing data models and metrics that your data team has defined and map that data directly to the specified fields in your end destination. Reverse ETL gives you the full flexibility to leverage your data exactly how it appears in your warehouse and it un-encumbers you from potential vendor lock-in.

A diagram showing reverse etl

Reverse ETL Architecture

How Do You Implement Customer 360?

Unfortunately, there’s no all-in-one solution that you can implement immediately to create a 360-degree view of your customer. Creating a seamless customer experience requires you to adopt a modern data stack and fully automate your data flow between acquisition, integration, and activation.

The reality is that for most companies all of the data they need is already available within their data warehouse and that means all of the customer attributes you need are already readily available in your warehouse. The problem is, most of the time this data is only ever used from an analytics perspective to power dashboards and static reports, which means it’s only ever being used to drive high-level decisions.

The truth is your sales team wants to know which leads they should be prioritizing, your marketing team wants to lower their customer acquisition costs (CAC), and your support team wants to know which customers are at risk of churning. The answers to all of these questions are already available in your warehouse, you just need a way to activate your data and that’s exactly the problem Hightouch solves.

More on the blog

  • What is Data Activation?.

    What is Data Activation?

    Learn everything to know about Data Activation, what it is, why it matters, and how you can get started activating your data today.

  • What is Reverse ETL? The Definitive Guide .

    What is Reverse ETL? The Definitive Guide

    Learn everything there is to know about Reverse ETL, how it fits into the modern data stack, and why it's different than ETL.

  • The CDP As We Know It Is Dead: Introducing the Composable CDP.

    The CDP As We Know It Is Dead: Introducing the Composable CDP

    Learn why CDPs are dead and how you can take advantage of the data warehouse.


Sign up for our newsletter

Ready to activate your data?

Get startedBook a demoBook a demo

Recognized as an industry leader
by industry leaders

We are proud to be recognized as a leader in Reverse ETL and Marketing & Analytics by customers, technology partners, and industry analysts.

Gartner 'Cool Vendor', 2022..
Snowflake 'Marketplace Partner of the Year', 2022..
G2 'Leader', Fall 2022.
G2 'Leader', Winter 2023.
Snowflake 'One to Watch for Activation and Measurement', 2022.
Fivetran 'Ecosystem Partner of the Year', 2022.