As a business partner, Webhelp helps you to collect, aggregate and analyse customer data. With a team of experienced data champions and the use of advanced analytics methodology, aided by cutting-edge technologies, we manage change and enhance data-driven decisions.
Our mission is to enable our clients and partners to go beyond traditional contact centre metrics and transform their customer experience through the intelligent use of data. At Webhelp we use analytics to power performance, inform transformation and ultimately deliver financial gain.
The Webhelp Data and Analytics Approach
Understand and Optimise Every Customer Interaction
We examine the key performance indicators (KPIs) around customer service in your organisation – your customer satisfaction score (CSAT) and net promoter score (NPS). From there, we isolate the problematic elements and start mapping areas that require improvement.
A key part of our customer contact understanding and optimisation process is finding ways to
We analyse the entire spectrum of customer contact to find the sticking points – the areas where your contacts are either failing to find resolution or getting caught in a feedback loop of trying and failing to find resolution. By reducing demand, we optimise every contact.
Optimise the Customer Journey
Using proprietary customer journey mapping tools, we identify the problem journeys – the areas where contacts are going wrong and generating dissatisfaction. Once we have found the issues, we work with you to develop the most effective changes for your people, processes and systems. Often, a small adjustment in policy or procedure is all it takes to transform the customer journey from a cross-channel odyssey into a short and pleasant trip. When this is achieved, satisfaction and advocacy go up, and your contact expenditure goes down.
Optimise Customer Value
We maximise the value of every customer on every contact by using the unstructured data that is often overlooked – everything from social media dialogue to webchat transcripts can play a role in analysis and customer segmentation.
First, we build predictive models to identify those likely to respond to cross- or upselling, or who are likely to complain or leave. Then we use our acquired insight to build targeted interventions into the CRM. Advisors are offered prompts during every customer interaction – even service calls or quick webchats. These tailored suggestions maximise the value of every customer contact, without turning every interaction into a sales call.