 "Diving deep into data")
There has been an increasing use of big data analytics in recent years, and with the evolution of new research techniques (both offline and online), more and more organisations are using primary, secondary and third-party syndicate data that cover all aspects of consumer behaviour.
With the growing relevance and usage of big data in predicting consumer behaviour from a marketing perspective, the integration of macro- and micro-trends in the marketplace is now increasingly being used in sell-out management and predicting a realistic scenario for the industry and organisations.
Advanced techniques in quantitative and qualitative research are also being increasingly used to understand the consumer better. Ethnography, eye tracking and brain mapping are being utilised to capture the consumer's subconscious mind for various product and concept tests. Also, advanced techniques in netnography are being deployed to effectively track the online consumer. Apart from mobile forms of surveying and understanding social media behaviour, netnography is also used to analyse real-time data related to various stages of the consumer's decision-making journey.
Besides competition benchmarking, brand equity tracking and pricing related decisions, newer techniques in big data analytics are continuously being used for trade and sell-out management, demand planning and forecasting, micro-geography market sensing and district-level market planning. These complement real-time consumer insights and are used as tools to increase counter and market shares.
Most of the organisations are dealing with big data more effectively due to the implementation of an advanced information technology (IT) architecture. Both big data and IT implementation are highly correlated. With the increased focus on ROI (return on investment)-based marketing and sell-out management, advanced analytics models are also being used to effectively monitor and plan media costs (offline/online), and assess overall marketing and sales targets and efficiency.
Using advanced data analytics, organisations now have a better assessment of major trade channels in terms of revenue, profitability, growth and better understanding of consumer segments at these places.
Consumer insights are at the core of the organisation strategy, and real-time consumer data have made it possible for marketers to get the bigger picture and at the same time track customer micro-trends at the retail place. Real-time big data analytics have enabled and increased the importance of sell-out management in the entire marketing ecosystem.
Pre- and post-marketing ROI analysis with real-time data has now become an integral part of a company's sales and marketing strategy.
The consumer preferences in the Indian scenario are changing very fast, in terms of brand as well as channel selection. With the deep-dive analysis of real-time data, brands now have faster access to the customer's regional and cultural preferences. Hence, they are planning better for both peak festive and non-festive seasons.
Real-time consumer insights have enabled brands to plan and offer smart deals of bundling category and non-category mix products, which are preferred by the customer nowadays. The planning for the peak season is more organised, and the companies' main objective is to increase the engagement time with the consumer and invest more in shopper in-store activations to influence the end customer for smart deals. Various shopper researches have shown that the consumer has a higher preference for value added smart deals rather than plain discounts in the past few years, and due to the accessibility of real-time customer preferences the brands are able to offer better deals each year.
Latest business intelligence (BI) tools are also being used by organisations to align internal business data with external primary and syndicate data for effective business decision-making at all levels. Some of the latest BI tools such as Birst, Bizzscore, Clear Analytics, IBM Cognos Intelligence and Microsoft BI platform are increasingly being used for providing real-time access to data, performing interactive and multidimensional analysis, budgeting, planning and forecasting to provide real-time view of the business and improvement areas.
With the growing relevance and usage of big data in predicting consumer behaviour from a marketing perspective, the integration of macro- and micro-trends in the marketplace is now increasingly being used in sell-out management and predicting a realistic scenario for the industry and organisations.
Advanced techniques in quantitative and qualitative research are also being increasingly used to understand the consumer better. Ethnography, eye tracking and brain mapping are being utilised to capture the consumer's subconscious mind for various product and concept tests. Also, advanced techniques in netnography are being deployed to effectively track the online consumer. Apart from mobile forms of surveying and understanding social media behaviour, netnography is also used to analyse real-time data related to various stages of the consumer's decision-making journey.
Besides competition benchmarking, brand equity tracking and pricing related decisions, newer techniques in big data analytics are continuously being used for trade and sell-out management, demand planning and forecasting, micro-geography market sensing and district-level market planning. These complement real-time consumer insights and are used as tools to increase counter and market shares.
Most of the organisations are dealing with big data more effectively due to the implementation of an advanced information technology (IT) architecture. Both big data and IT implementation are highly correlated. With the increased focus on ROI (return on investment)-based marketing and sell-out management, advanced analytics models are also being used to effectively monitor and plan media costs (offline/online), and assess overall marketing and sales targets and efficiency.
Using advanced data analytics, organisations now have a better assessment of major trade channels in terms of revenue, profitability, growth and better understanding of consumer segments at these places.
Consumer insights are at the core of the organisation strategy, and real-time consumer data have made it possible for marketers to get the bigger picture and at the same time track customer micro-trends at the retail place. Real-time big data analytics have enabled and increased the importance of sell-out management in the entire marketing ecosystem.
Pre- and post-marketing ROI analysis with real-time data has now become an integral part of a company's sales and marketing strategy.
The consumer preferences in the Indian scenario are changing very fast, in terms of brand as well as channel selection. With the deep-dive analysis of real-time data, brands now have faster access to the customer's regional and cultural preferences. Hence, they are planning better for both peak festive and non-festive seasons.
Real-time consumer insights have enabled brands to plan and offer smart deals of bundling category and non-category mix products, which are preferred by the customer nowadays. The planning for the peak season is more organised, and the companies' main objective is to increase the engagement time with the consumer and invest more in shopper in-store activations to influence the end customer for smart deals. Various shopper researches have shown that the consumer has a higher preference for value added smart deals rather than plain discounts in the past few years, and due to the accessibility of real-time customer preferences the brands are able to offer better deals each year.
Latest business intelligence (BI) tools are also being used by organisations to align internal business data with external primary and syndicate data for effective business decision-making at all levels. Some of the latest BI tools such as Birst, Bizzscore, Clear Analytics, IBM Cognos Intelligence and Microsoft BI platform are increasingly being used for providing real-time access to data, performing interactive and multidimensional analysis, budgeting, planning and forecasting to provide real-time view of the business and improvement areas.
Joginder Chhabra
Head, market and consumer insights, LG Electronics
Head, market and consumer insights, LG Electronics