This paper will illustrate how AI algorithms on big data sources (social media, search, e-commerce, Internet of Things, Mobile data) can be developed and applied for transforming consumer insights and marketing programs. This transformation will be on two counts: re-invention of existing programs by making them better, granular, cheaper, faster, and development of new programs to harness the opportunities provided by the new connected world like personalisation strategy, real-time optimisation, development of early warning system and integration of NPD with digital activation. The focus will be on what kind of AI algorithm will work in marketing application context, bringing this to life with real-world cases and generate learnings for us as an industry.
This presentation will illustrate how AI algorithms on big data sources (social media, search, e-commerce, Internet of Things, Mobile data) can be developed and applied for transforming consumer insights and marketing programs. This transformation will be on two counts: re-invention of existing programs by making them better, granular, cheaper, faster, and development of new programs to harness the opportunities provided by the new connected world like personalisation strategy, real-time optimisation, development of early warning system and integration of NPD with digital activation. The focus will be on what kind of AI algorithm will work in marketing application context, bringing this to life with real-world cases and generate learnings for us as an industry.
This paper establishes the relevance and need of an appropriate pricing construct (not price per se) in driving the profit growth and illustrates how research feeds into the construct. The same would be explained with the help of a case study in a B2B scenario (logistical services industry) in Asia Pacific. The paper also demonstrates, using a combination of research techniques, the importance of taking into account the interaction of price with brand, looking at pricing in the overall scheme of other factors, linking findings from different studies and linkage of research findings to the customer's database helps in the identification and implementation of an appropriate pricing policy, not to mention the usefulness of a common framework across countries in a region and across continents, thereby maintaining consistency.
This paper will establish the relevance and need for moving away from consumer segmentation to need-state segmentation, especially for FMCG categories. The paper will illustrate some of the drawbacks of conventional segmentation approaches and how the same can be overcome using the concept of need-state segmentation. This would help in incorporating the concept of 'multiple me', thereby explaining the reason for different variant and brand usage on different occasions.The usefulness of the approach is illustrated with the help of a case study in the area of brand strategy development: brand positioning, communication, product portfolio, and targeting strategies.