Sensory Market Research
Demystifying the customer preferences for Ready to eat products
It is very true that as customer’s life style and preferences change, teams analyzing the current products in market have to revisit their marketing strategies. Every aspects in terms of segmenting the customer, targeting the potential groups and positioning the right product variant become open for strategy revisit to optimize the product lines.
To analyze the customer preferences in ready to eat products which exactly fits in above criteria requires constant improvement in various product features and attributes to remain viable in the market.
The approach followed to decide on customer preferences has original variant benchmarked to new variants on product and packaging features The typical performance indicators for which one has to collect the data are listed below.
- Liking and intent parameters- These are main parameters which would indicate the overall likings and intent for the current product and its variant. Usually likings are represented as aggregated scores whereas intent in terms of proportions of total population
- Just about right (JAR) parameters- Indicators which suggest how are the products off from the just about right features. These parameters would range from size, flavor, taste, texture to filling ratio for product constituents. Usually the off categories and JAR levels are expressed terms of proportions of total population
- Preference parameters- Indicators which split the survey population in terms of product preference
- Occasion parameters- These indicates the different moments for which the products would satisfy the customer need. After looking into occasion data, one could investigate the opportunities
The processed data containing above parameters is put for below score analysis
- Univariate/Bivariate – Mapping the liking variable with product intent and expectation to observe clear indication for product likings
- JAR analysis- To analyze the survey proportions for all JAR levels and indicate issue with product features
- Penalty analysis- This is the primary analysis to identify the opportunity lost due to decrease in customer preferences on certain product features. High penalty values above threshold value signify the areas for which the product has to be improved.
- Preference analysis- To analyze the preference with significance testing to know about the preference share Based on above analysis, marketing teams could finally arrive at preferred product. Also, one could understand the feature gaps which need to be addressed in current product to sustain it in the market