Services

Marketing Automation & Segmentation
Data Science & Machine Learning
Data Integration & Architecture
Data Warehouse Modernisation
Data Visualisation & Reporting
July 24, 2018 1:11 pm

How to bring a 360° Customer View to life


Understanding your customer via a 360° view is pivotal to becoming customer-centric and remaining competitive in today’s digital era. However, achieving a true 360° view that drives business value remains elusive… This article proposes a different way to implement a 360° view, helping you in your initiatives towards building a robust 360° view of your customers, in turn impacting your business profitability.

It’s based on the white paper How to bring a 360° Customer View to life, which you can download on our site.

 

A different point of view

Traditionally, we have understood a 360° customer view to be a data and information collection initiative. It is the ability to know and understand everything about our customers, taking all the data you can gather about them across all their life stages with you, and unifying it to create one single view. 

Organisations have seen some successes in collating data, but mostly it turns out to be a big challenge. The truth is – it’s extremely difficult, if not impossible, to keep collecting new types of data from myriad sources and unify it to take you to 360°.

We believe it’s not just about data, or more data, or even all the data. It’s about the insights you can derive out of the data you have to drive business value: insights that are not visible to the human eye; hidden in the customer data; in customer behaviours; insights that can be unearthed by asking questions from the data; and insights that can help you increase what really matters for business value – revenues from your customers and profitability across each stage of your customer journey.

There’s a few steps you can follow to achieve this.

 

STEP 1: UNDERSTAND CUSTOMERS THROUGH MACRO-SEGMENTATION BASED ON CLTV

This step helps you understand that in the context of profitability not all customers are right. Only the high value customers are right.

 

STEP 2: STRATEGISE THROUGH MICRO-SEGMENTS BASED ON LIFECYCLE STAGE AND LTV-CHARACTERISTICS

This step helps you devise customer centric strategies and actions along the customer journey stages for the micro-segments with growth potential to generate more revenue. At the same time, you can understand what data you need to gather and process to generate behavioural and actionable insights about them.

 

STEP 3: PRIORITISE ACTIONS BASED ON THE BUSINESS OBJECTIVES AND LOW HANGING FRUITS

This step helps you take an informed and prioritised next action so you can collect and process only relevant data to start with, then develop and deploy only the relevant data science models to get the right insights, and finally start demonstrating the business impact on revenues and profitability.

 

CLOSING THE LOOP

When you measure your CLTV and profitability after going through each customer stage at least once, you should be able to clearly articulate the impact value generated. The CLTV macro-segments would have migrated and the average CLTV itself should have increased. You should also be able to see the increase in profitability.

 

CONCLUSION

Acrotrend’s 3-step approach to achieving a 360° customer view revolves around customer LTV and is based on the data science led insights required at each stage of the customer journey. This approach helps you:

• Reveal customer micro-segments where the maximum LTV is being leaked or generated

• Drive customer centric strategies to grow the CLTV

• Start based on priorities to demonstrate the impact on business revenues and profitability faster, and build the customer 360° view as you go through this initiative, one that really works!

DOWNLOAD THE WHITE PAPER HERE

Healthcare and Pharma
February 13, 2019

5 Testing Best Practices to Error-Proof Your Pharma Sales KPIs

How a solid KPI testing strategy underpins the success of your pharma sales team's digital transformation.

Fitness Industry
February 7, 2019

Getting from Insight to Action with Marketing Automation

Getting from Insight to Action with Marketing Automation: Applying the results of data science driven churn analysis to drive retention marketing efforts.

Customer Analytics
January 29, 2019

Applying Data Science to Predict Customer Churn

A practical guide for getting your data science churn analysis project up and running.