What is Customer 360? (And how can you make sure you get it right?)

Leveraging data is easier said than done—especially when your data is compartmentalized. This is where a customer 360 model comes in and provides a more complete profile of the consumer. Nevertheless, as a standalone model, this still doesn’t depict the full picture. Learn how to truly utilize customer 360 data to create accurate single-customer views.

Customer 360 defined

What is customer 360 and why is it relevant in today’s business sphere? 

Under this model, you have all of a customer’s data integrated into a single location that’s accessible and viewable by authorized staff. All of the data is in front of you via a single dashboard.

The data comes from multiple sources, such as:

• Website analytics, including visits, visit duration, pages navigated, etc.
• Email open rates
• Purchase history
• Items browsed on the recommended list
• Engagement with company social media channels

Under legacy CRM systems, these data sets would be in their own silos. A customer 360 model unites these data points to create a graph database that reveals a customer’s behavior, predicted behavior, and pain points. 

Why a customer 360 view matters

A customer 360 view ensures all members have access to the same set of data. When data is compartmentalized, the marketing team may only view the social media data, while HR views the website analytics. This is akin to the parable of the seven blind men each feeling a different part of the elephant. Each department has a different and segmented perspective that only portrays a fragment of the customer journey.

The advantages of customer 360 include:

• A better understanding of customer behavior based on superior predictive analysis
• More strategic sale campaigns based on past actions and predicted actions
• Customized customer experiences that lead to better conversions, retention, and loyalty

Why you might get Customer 360 analytics wrong

Customer 360 is a necessary model for accurately mapping the customer journey. However, the data in front of you still doesn’t quite paint an accurate picture. Data alone—even when neatly plotted in a graph database—doesn’t precisely equal customer insight. 

Data may not paint a fully accurate picture due to the following variables.

Outdated data

Data can get old really quickly. For example, let’s say a customer purchased a set of ear pods from Amazon six months ago but has not purchased or viewed similar products since. Is the data still reliable and reflective of the customer’s current behavioral profile?

Insufficient IT tools

Does your current CRM system have the capability to integrate data silos? Even if does, is it capable of filtering outdated or duplicate data? Can it create single customer views using incoming, real-time data? A customer data platform (CDP) may be more up to the task than conventional CRM software.

Insufficient data consolidation

Data integration doesn’t equal data consolidation. What’s the difference? Let’s say Sam Smith is a customer. He’s active on your company’s website and social media channels. However, his website profile account has him listed as Sam Smith, while his social media profile uses his full name, Samuel Smith. Meanwhile, he is listed as Sammy Smith under your email subscriber list. 

When you integrate data from these data silos, will the system recognize Sam, Samuel, and Sammy Smith as one and the same person? If not, then it’ll create multiple profiles from a single customer. Data consolidation addresses this issue while data integration merely brings data silos together.

How to address Customer 360 shortcomings

For customer 360 to be a truly effective customer-mapping tool, your team needs to address the following elements.

Maintain data freshness

When does data become outdated? That’s for your team to determine, and it differs with each data set. It may also differ on a case-to-case basis. For example, a purchase made six months ago may not necessarily be considered outdated if the customer has consistently made similar purchases and viewed similar products since then. Establish parameters that determine the cut-off point when data is stale and no longer viable.

Update your IT tools

Your CRM software may not be adequate to handle modern data streams. A customer data platform service is more adept at integrating data for cohesive analytics. The CDP should:

• Update data in real time, 24/7
• Identify outdated and duplicate data based on your input
• Reside in the cloud, be accessible via personal devices, and have strong encryption in place
• Provide training modules to integrate new users

Consolidate data in a meaningful way

The CDP should have customizable data consolidation features. Users should have a way to configure the system to identify customers across different platforms. Once it identifies customers and brings their data together to form a single customer view, it should have a system in place to filter out duplicate data. If two data sets for the same customer reveal a different phone number, for example, can it identify the one that’s up to date?

Get an accurate Customer 360 view with Lytics

Does your current CRM system have a way to consolidate data? Can it keep pace with real-time data? Can it create detailed customer profiles? Our flagship services Cloud Connect and Decision Engine make this an intuitive process. Get started with a free trial today!