Home Retail Majority of Indian businesses under-utilising data analytics: Report

    Majority of Indian businesses under-utilising data analytics: Report


    Despite investing more in data-driven digital platforms and tracking systems, majority of Indian businesses are failing to utilise the data generated from online sources, reveals a new survey by global market insight firm Taylor Nelson Sofres (TNS).

    Indian businesses are increasingly investing more in data-driven digital platforms and tracking systems to help them understand the challenging online landscape. However, as much as 70 per cent of marketers in India admit that they find it difficult to integrate data from different sources, the TNS study notes.

    TNS Marketing Monitor was carried out in eight markets in Asia Pacific, including India, China and Australia and is based on responses from 2,716 marketing professionals across markets, the company said.

    With so much data available, businesses know they should be able to make decisions in real-time, but many are struggling to integrate traditional and digital measurements.

    “India’s online environment is developing at break-neck speed. As more and more people start connecting to the Internet through mobile and accessing digital platforms, the amount of data is set to explode. The key is to understand how to use it effectively now, before the volume becomes unmanageable,” says TNS India Managing Director (South India & Sri Lanka) and Head of Brand & Communications practice S Visvanathan.
    “Today, 70 per cent of Indian marketers are unable to integrate multiple data sources – such as social media, blogs, website traffic and search data – leaving them unsure what action to take,” he added.

    Adding to the importance of online data, retail advisory firm Technopaksaid, “These businesses can approach several aspects of the business including merchandising, supply chain, inventory management, pricing strategy, marketing strategy, cross-selling, upselling, fraud prevention, optimising payment mix, etc. in a scientifi c way so as to optimize costs and improve revenues. Moreover, they can also detect bottlenecks and identify
    opportunities, and accordingly plan for the future with the visibility that data solutions offer.”

    According to the survey, the current market research methods like sales uplift metrics are still used as the number one way of evaluating the success of marketing campaigns, however these are not helping businesses make quick and informed decisions.

    Internationally, the use of data analytic is widespread, both in the Brick & Mortar and the online retail space, says technopak. Several consumer behaviour models have been developed with a primary objective to identify the most valuable customer segments, the opportunities to improve their experience and influence their behaviour, which helps allocate resources for the greatest impact. Some of the analysis used and developed by them are stated below:

    Consumer Behavior Analyses Details
    Predictive Customer lifetime Value Analysis helps in optimizing acquisitions based on customer lifetime value, i.e. the amount of revenue or profi t a customer generates over his or her entire lifetime


    Persona Analysis looks at all the purchases a customer makes over their lifetime to identify types of customers and allows the brand to tailor its marketing via a more comprehensive understanding of what customers might like to buy


    Churn Detection helps understand individual customer tendencies and notifi es when they veer from their normal habits so that they can be reached before they drift away


    Customer Segmentation helps understand the customer lifetime value across every customer segment using lifecycle, persona, demographic, and product dimensions, and enables better marketing that can target highvalue segments


    Cohort Analysis Drills down past aggregates and defi nes how different groups of customers behave over time


    Trend Analysis helps in learning how every customer segment is changing year-over-year and month-over- month


    lifecycle Segmentation looks at every customer’s unique buying tendencies to fi nd out exactly to what stage of the customer lifecycle they belong and allows designing a communications strategy that reaches out with effectively tailored messages when most necessary


    Satisfaction Analysis Quantifi es satisfaction with the online experience and helps in predicting future behavior across customer touch points to reveal which improvements have the greatest impact and the highest roi


    TNS further explains that tapping into digital data has the potential to unlock future opportunities for those businesses that can leverage it.
    “As the pace of change accelerates across the region, we need to start using data to gaze into the future, not just measure the here and now. Tracking social and search data to form the basis of a predictive spine delivers insight months ahead of survey data or sales figures. This give businesses the power to anticipate changes to brand equity in time to actually do something about it,” said Nitin Nishandar, Managing Director of Brand & Communications, Asia Pacific, TNS.

    “In such a volatile environment, having a telescopic view into the future is an invaluable competitive advantage, and one that businesses can’t afford to overlook, ” Nishandar concludes.

    The Technopak inputs were extracted from the India Retail Report 2015