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ALM Media, LLC

Josh Gazes, Senior Vice President – Operations

British Gas

Jess Johnson, Head of Operational Excellence

Mosaic Insurance

Mitch Blaser, Co-CEO

Mosaic Insurance

Krishnan Ethirajan, COO

Oxford Nanopore Technologies

Jason Hendrey, Senior Director, Global Customer Services

WS Audiology (WSA)

Christof Steube, Director of Finance Excellence

Kiwi.com

Leonard McCullie, Director, Vendor Management

Kiwi.com

Petra Reiter, Vice President, Customer Services

Flight Centre

Aaron Fadelli, Business Leader

Healius Pathology

Alex Cook, Head of Finance Operations

Varo Bank

Breanna Rivers, Partner Performance Manager

Yorkshire Building Society Group (YBS)

Jessica Lockwood, Process Automation Manager

WS Audiology (WSA)

Sharang Patil, Director of Group Finance Excellence

Priya Madan Mohan, VP for Group Accounting & Controlling

United Airlines

Chris Kenny, VP and Controller

GFG Alliance

Phillip Irish, General Manager, Shared Services Delivery, Quality & Governance

Energy Australia

Steve Corden, Outsource Operations Leader

Delaware North

Christopher Lozipone, Senior Vice President and Global Business Services Head

Moneycorp

Nick Haslehurst, Chief Financial & Operating Officer

Prodigy Finance

Nico Barnard, Head of Operations

M&T Bank

Chris Tolomeo, Senior VP & Head of Banking Services

Minerals Technologies Inc. (MTI)

Khem Balkaran, CIO

Church's Chicken

Louis J. Profumo, CFO & EVP

The Client's Challenge

Our client, a global media and entertainment company, had multiple growth objectives. First to identify and track the ‘true1’ engagement of their established artists with their vast fan base. Second, to compare and contrast the engagement of these artists with the competitive landscape across defined geographies. Third, to identify amateur and promising talent.

An overarching objective was to eliminate any scope for human bias in artist selection or contract renewals.

The Approach

WNS deployed its unique big data and social media analytics platform, SocioSEER™, to solve the client's challenges.

SocioSEER™ used its proprietary machine-learning algorithms, in-house taxonomies and deep domain infusions to benchmark artists on their 'virality' using social media engagement scores (for example, the number of fans, favorites, likes, dislikes and comments). The cloud-based interface of SocioSEER™ effortlessly managed complex, unstructured information in real-time for both timely action and decision-making across millions of impressions and hundreds of artist pages across platforms.

SocioSEER™ tracked 1600 artists across seven social media platforms and 13 geographies. More than 50 Million structured and unstructured impressions / records were analyzed through SocioSEER™ to categorize viewer comments and determine sentiments associated with each artist across platforms. Competitor benchmarking was done across 20 other areas.

The Music and Entertainment module of SocioSEER™ enabled:

  • Text analytics for sentiment and theme classification: Categorized all comments, including video text, for theme generation and predicting artist sentiments

  • Face detection and AI for audience analytics: Created insights related to the audience — their music preferences, genre, demographics and so on. Leveraged these insights to create a single view into each investment by the record label to ascertain its effectiveness

  • Machine-learning to enable language detection and translations: Deployed the platform across multiple geographies to create a unified view for deeper insights and effective decision-making

The Benefits

  • Creation of the 'SocioSEER™ Index' (social media standing of an artist vis-à-vis competition)

  • 100 percent reduction in bias while signing and renewing established artists

  • ~20 percent optimization in channel spends for promoting artists

  • Operational savings made by identifying and dropping non-performing artists

  • Reduction in acquisition cost by identifying and signing amateur and promising talent early-on

  • Creation of a 'decision workbench' to allow for optimized and accurate marketing spends among artists

About SocioSEER™

With social media usage growing at an astounding rate, brands are inundated with data and information, but have very little insights into relevant customer conversations.

WNS SocioSEER™ provides a single and seamless platform for global brands across industries to:

  • Cut through the 'white noise' with the help of our proprietary RECOINSM (Refine, Contextualize, Index) methodology

  • Filter conversations that truly matter — from both structured and unstructured sources including social media, call center data and blogs

  • Avoid brand blind spots and build industry-specific, relevant and actionable context

  • Leverage advanced analytics to track online reputation and focus on brand equity drivers

  • Measure brand impact and track progress with a single unified metric

In simple terms, WNS SocioSEER™ has the power to impact your top-line and brand equity for real. It goes beyond attitudinal to cover behavioral insights; it goes beyond benchmarking against co-brands to benchmarking an entire market; and goes beyond white noise to uncover true customer conversations.

WNS Case Study - Social Media Analytics and AI SocioSEER

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