Making Sense of Customer Experience Data

Lots of pink question marks scattered on a blue background

Filed under - Industry Insights,

Stuart Dorman of Sabio explores how we can drive more value from the Customer Experience (CX) data stored within contact centres.

At Sabio’s recent Executive Forum, there was a discussion over how organisations could start to derive more value from the multiple datasets already available across their customer journeys.

With contributions from C-level executives representing the insurance, retail, travel, IT services and outsourcing sectors, there was a clear recognition of the untapped value just sitting there waiting to be exploited.

Many felt that initial enthusiasm to embrace discrete Machine Learning or AI-led projects to make use of these large but discrete data sets showed some real promise, but there was a consensus that the real value lies in linking together data siloes that exist across the entire customer journey.

That’s why it’s essential that we understand not just where we’re starting from when it comes to CX insight management, but also where we’re heading.

While most customer contact operations already collect data from digital, self-service and human-assisted call centre interactions, very few are linking this data to the actual ‘outcomes’ identified from web chat, virtual assistants, speech analytics or customer feedback.

Linking these siloes together unlocks the opportunity for predictive analytics (What will happen?) and even prescriptive analytics (What should I do?), which can then be applied to optimise the customer journey across areas such as proactive contact, targeting, routing, forecasting and coaching.

What’s clear is that current customer journey initiatives still have some way to go to move beyond simply collecting data and optimising single touch points.

Often referred to as Customer Journey Analytics, the focus needs to be on linking multiple datasets – coupled with in-depth insights and predictions – to achieve more valuable outcomes.

Stuart Dorman

Better outcomes include reducing bad demand by identifying process and experience improvements, improving sales performance or tracking and predicting the business impact of CSAT.

To stay ahead of the game it is good to use technology to link and extract value from CX data siloes to create a clear, end to end view of customer behaviour. This is the next step in unlocking the next wave of benefits from your digital transformation initiatives.

This blog post has been re-published by kind permission of Sabio

To find out more about Sabio, visit their website.

About Sabio

Sabio Sabio, is a customer contact technology specialist focused on delivering exceptional customer service strategies and solutions, partnering with leading organisations such as Avaya, Nuance and Verint. Sabio offers business consulting, systems integration and managed services working with many major organisations across the world including DHL, The AA, Liverpool Victoria, Homeserve, Saga, DX, P&O, Home Retail Group, SSE, Think Money, Office Depot, Unibet, Eurostar, Leeds City Council, Yorkshire Building Society and multi-award winning Lebara Mobile.

Read other posts by Sabio

Call Centre Helper is not responsible for the content of these guest blog posts. The opinions expressed in this article are those of the author, and do not necessarily reflect those of Call Centre Helper.

Published On: 15th Apr 2019 - Last modified: 19th Jul 2022
Read more about - Industry Insights,

Recommended Articles

A picture of data analysis
Customer Data Analysis – How to Analyse Data in 7 Steps
A collection of animated smiley faces
How to Improve the Emotive Customer Experience Using Scorecard Data
Traveler with backpack checks map to find directions in wilderness area
Customer Journey Map Examples With Expert Analysis
Get the latest exciting call centre reports, specialist whitepapers and interesting case-studies.

Choose the content that you want to receive.