UK CX Forum (voice of customer priorities and text analytics best practice)

UK CX Forum (voice of customer priorities and text analytics best practice)

By SandSIV UK

Date and time

Thu, 26 Jan 2017 08:15 - 11:00 GMT

Location

Simpson's-in-the-Strand

100 Strand London WC2R 0EW United Kingdom

Description

UK CX Forum
voice of customer priorities for 2017 & text analytics best practice

8.15am - Registration & Breakfast

9.00am - Welcome & Introduction

9.10am - 2017 Voice of Customer Priorities Christopher Brooks - Director Lexden Group

9.45am - Text and Sentiment Analytics Best Practice. Dr. Federico Cesconi - Founder & CEO SandSIV Group

10.15am - Closing Remarks

10.25am - Coffee & Networking

11.00am - Close


2017 VoC Priorities - Christopher Brooks, Lexden (Independent Customer Experience Specialists)

Voice of the Customer has taken off significantly in the last five years and is now a widespread practice amongst ‘leaders’ and ‘lagers’ alike in Customer Experience. With a critical eye on customer performance now coming from the boardroom, the expectations of conventional customer feedback programmes to provide enhanced quality and quantity of customer insight indictors has increased. In 2016 Lexden worked with several organisations reassessing their VoC capabilities to meet this growing demand. With this in mind, Lexden reached out to a broader community of VoC practitioners to better understand what they believe the VoC priorities for 2017 will be. This presentation will unveil the findings of their study.

Text Analytics Best Practice - Dr Federico Cesconi, Founder and CEO, SandSIV

The importance of accurate text analysis has grown significantly as the number and variety of sources available for the collection of voice of customer data has expanded. Multiple languages, sector specific terminology, text talk and sarcasm have all caused problems for the early text analytics systems. This presentation will describe the pros and cons of the different approaches to text analysis and focus on natural language processing and how machine learning can be used to ensure that multiple languages and unusual terminology can be correctly interpreted.

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