CRM with Big Data - EdgeVerve big data can be leveraged to create an insightful CRM solution. CRM with Big Data WhiTe pApeR. 2 | infosys Big data is all about processing,

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  • Big data is one of the latest buzzwords in the technology lexicon. The potential, reach and impact of big data technologies is the subject of much debate, and the hero in many success stories. Another concept, albeit older, is Customer Relationship Management (CRM), which has made a huge impact on the business world over the years, directly improving profitability, branding, and satisfaction. This paper looks at how big data can be leveraged to create an insightful CRM solution.

    CRM with Big Data

    WhiTe pApeR

    www.infosys.com/finacle

  • 2 | infosys

    Big data is all about processing,

    interpreting and representing huge data

    typically, petabytes or even zettabytes of

    data sourced from text, database fields,

    voice, video, blogs, kiosks, social networks

    and websites in a way that is meaningful

    and actionable. As of 2013, we have

    more than 2.4 billion internet users, more

    than a billion Facebook subscribers, and

    at least 200 million users of professional

    networking sites like Linkedin, generating

    a mountain of data in the form of blogs,

    web clicks, likes, preferences and so on. Big

    data technologies impart the capability to

    interpret these vast data into information

    and knowledge and valuable insights,

    such as, the best time, channel or incentive

    for an advertising content to directed at

    a particular segment; context pertaining

    to an organizations customers, business,

    environment or employees; or forecasts

    of greater accuracy. Whats more, by

    providing information in near real-time, big

    data technologies enable faster turnaround

    and response times.

    in short, the possibilities of big data

    the data itself and the technologies for

    harnessing it are quite amazing.

    The goal of all CRM solutions is to

    increase customer satisfaction en route

    to achieving organizational business

    objectives. CRM believes in investing in the

    customer, who is the prime asset of any

    business. implemented right, CRM helps

    organizations to understand and engage

    customers better, become more relevant

    to customers and users, empower and

    engage the latter, and eventually earn a

    higher share of wallet.

    Yet, there is room for improvement.

    CRM solutions can become smarter by

    converting their data into customer

    insights, subsequently using these to

    improve customer processes. That would,

    in turn, improve customer satisfaction,

    conversion, loyalty, advocacy and share of

    the wallet. here are a few examples of how

    the big data gathered by CRM solutions

    can make a profound impact on them.

    In marketing

    A typical marketing campaign extends to

    billboards, advertising, carpet-bombed

    calls to all on all devices, annoying ads and

    pop-ups in social media and so on. While

    these methods do create brand awareness

    they come at a high cost and very low

    ROi and conversion rates, besides being

    a nuisance to customers. Now imagine a

    world with big data, and the possibility

    of targeting the right product to the right

    person at the most opportune time and

    place. Think of how valuable it would be

    to have the ability to model products and

    offers that could meet the requirements of

    a target class, or to create campaigns that

    make the greatest impact by promoting

    the right offers to customers when they are

    the most receptive. Big data insights can

    enable all the above.

    Big data also provides near real-time

    feedback on the progress of an ongoing

    campaign to help fine tune the resources,

    content and channel, and make the

    campaign more effective.

    For instance, it could suggest a golf event

    as a way to promote a business plan to

    golf loving venture capitalists. it would

    pick a date and time based on their busy

    schedule and the weather forecast. Then

    it would go on to suggest the ideal menu.

    While the fate of the business plan rests on

    its merit, the insights from big data could

    surely tip the scales.

    In sales

    it is natural to question the need for big

    data analytics when so much analytical

    capability already rests with the

    organization and its experienced sales

    team. Thats akin to saying that there

    is no need for permanent dwellings as

    long as there are caves. The fact is that

    about 80% of an organizations data

    exists outside of the structured data in

    files and databases. Most of this data is

    outside the organization even, very likely

    in unstructured form. There is immense

    potential to harness this data effectively

    to serve goals, such as improvement

    in processes, sales, conversions and so

    on. Simply put, deeper knowledge of

    opportunities and customer preferences

    enables better management of sales.

    Sales has always benefitted from

    contextual data that is available on

    demand. By providing this, big data

    technologies could enable predictability

    and conversion, and in retrospect, result in

    the betterment of processes, products and

    people.

    In servicing

    Servicing is an area, which can directly

    impact customer satisfaction and loyalty.

    hence, it is essential to clearly understand

    customer issues and make all efforts to

    resolve them. if customer data including

    queries on different channels were to

    be made available in a way that was both

    meaningful and actionable, many of the

    complaints would disappear. Also, if there

    were a way to accurately assess staffing

    requirements, based on product, channel,

    and time of day and so on, it would

    mitigate risk to a large extent. Big data

    could be of particular relevance to virtual

  • Module-Based Individual Banking

    Solution Is a specialized, standalone

    solution that supports banking

    operations in specific business areas

    like loans, treasury, customer analytics,

    wealth management and so on.

    Monolithic Core Banking Solution Is a

    single solution that can handle the entire

    gamut of the banks products, modules

    and business areas.

  • 4 | infosys

    agents when they respond to individuals.

    Many of the issues and complaints could

    be handled with ease. A satisfied customer

    is the best advocate and is receptive to

    cross selling and upgrade. insights into

    channel usage can be used for better

    channel control and optimal processing

    .The viral updates and advocacy across

    social media or traditional channels can

    also be measured to gauge service aspects

    and make improvements to enhance

    customer satisfaction.

    Big data can bring a lot of sophistication

    to CRM and help ensure optimal sales and

    customer satisfaction. Whereas earlier,

    harnessing huge volumes of data was a

    problem, it no longer is so, thanks to big

    data technologies. processing big data

    on the cloud puts the power of advanced

    analytics within reach of those who cannot

    afford to install expensive hardware and

    software.

    A word of caution

    Big data technologies should be used in

    conformity with rules and regulations,

    including those pertaining to customer

    privacy, intellectual property rights and

    security, with digital data abounding as

    well as scope for its misuse, there needs to

    be a defined policy on the legitimate uses

    of data.

    One other point is that big data is only as

    useful as the quality of the source data.

    Garbage in Garbage out (GiGO) applies

    as well to big data as it does to say,

    application programming. it is very easy

    to make incorrect inferences if the source

    data lacks consistency or is not properly

    analyzed. in such a case, there is a need

    for an alternative data source or rework of

    inferences.

    Shriram parthasarathyprincipal Consultant, Finacle, infosys

  • 2013 Infosys Limited, Bangalore, India. All Rights Reserved. Infosys believes the information in this document is accurate as of its publication date; such information is subject to change without notice. Infosys acknowledges the proprietary rights of other companies to the trademarks, product names and such other intellectual property rights mentioned in this document. Except as expressly permitted, neither this documentation nor any part of it may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, printing, photocopying, recording or otherwise, without the prior permission of Infosys Limited and/ or any named intellectual property rights holders under this document.

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    www.infosys.com/finacle