An FMCG marketer wishes to identify a product mix that would allow it to maximize its reach amongst consumers, yet limit the number of product variants. Through a combination of customer surveys and TURF analysis, the marketer is able to clearly identify consumer preferences for the various product variants being envisaged. In addition, an effective segmentation of the total addressable market enables the FMCG marketer to arrive at the strategic direction for launching the optimized product mix.
Read MoreOne of India’s biggest auction houses, when venturing into tea procurement and auctions, wanted to develop an analytical model to predict the auction bid-start price in order to get a competitive advantage. Using 4-year auction pricing data for a tea board, a predictive model was built using a combination of hedonic pricing analysis and auto-regressive distributed lag (ARDL) modelling, together with mixed-effects regression modelling approaches. The predictive model enabled the client to reduce its dependence on tea tasters and enhance the price-discovery effectiveness of the auction process.
Read MoreA soft-drinks marketer wishes to understand customer perceptions of a new product, relative to existing products and competing brands. Customer surveys provide data on consumer likes & dislikes along various product specifications, such as sweetness, color, flavour, calorie content, packaging, pricing, etc. Multi-dimensional scaling techniques are used to reduce the respondent scores along each of these product specifications into a reduced number of dimensions that reflect the unique product attributes. The resulting perceptual map enables the soft-drinks marketer to understand the relative strengths & weakness of its new product vis-à-vis old products as well as competing brands. This allows the marketer to tweak product features to generate greater attraction for its new product, apart from identifying gaps in the product landscape that indicate the opportunity to design further new high-potential products to satisfy customer desires.
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