Case Study 1 – Conjoint for SKU Launch
- The client; a Middle East - based research and analytics firm wanted to understand whether its client – a soft drinks manufacturer can introduce the 500ml can and withdraw the 400ml PET and 355ml can from the market and the effect this would have on market shares vis-à-vis it’s main rival.
- It also wanted to understand price sensitivity and whether the new 500 ml can should be priced at R2 or R1.5
- The study was to be conducted in two major urban centers
- The project team conceived the study as a conjoint exercise with brand, SKU and price as the attributes. For ease of administration and given the objectives of the study and the fact that both competitors in the market had similar SKUs, Brand x SKU was conceived as a single attribute with levels like “Brand X 300 ml PET”, “Brand Y – 355 ml can” etc.
- The project team worked with a partner to conduct 150 face-to-face interviews each in the two city centers. Out of these, in each city, 75 interviews were conducted with consumers of the focal brand and 75 interviews with consumers of the rival brand. 5 versions of the conjoint design was used with equal number of respondents per version per city.
- Data collected from the survey was cleaned and the conjoint data was analyzed using Sawtooth Software’s CBC module.
- After computation of utilities and attribute importance, market simulations were carried out to understand the impact on own and rival’s total market shares as well as market shares of own SKUs as a result of introducing the 500 ml can at R2 and R1.5 with and without withdrawing the 400ml PET and 355 ml can.
- The results showed that the client’s rival was clearly ahead in terms of brand preference.
- The analysis showed that the client should include the 500 ml can at R2 per unit without withdrawing the 400 ml PET and 355 ml can even though this price was higher than the rival’s 500 ml can
Case Study 2 – Identifying and Profiling Core Loyal Segment
- The client; a North America-based research and analytics firm wanted HBG to carry out backend analysis on one of the surveys earlier conducted by them.
- The objective was to iteratively segment the US beer market until the core loyalty group for a particular brand of beer was identified. Once identified, the different characteristics of this core group were to be displayed through Quad maps.
- The project team, after conducting a detailed check on the data/documents of the existing processes and SPSS codes for Quad map generation, removed all redundancies in the process and integrated relevant filters into the code to generate data for the Quad maps.
- In stage I of the project, factors were extracted from the data by using attribute-based variables. Next, clustering was done based on the reduced set of those variables, which had the biggest loadings with the factors. Then, two measures of frequency were developed for beer use and customer loyalty.
- Finally, the existing and generated measures were plotted in the form of Quad Maps, allowing the client to measure the change in customer loyalty according to the inherent reasons for consuming that particular brand of beer.
Case Study 3 – Product Placement Study
- The client is a manufacturer of a leading brand of shampoo in the Indian market and wanted to undertake a market research to understand whether it should make changes to its current brand. Towards this end , they wanted to undertake a consumer study to understand how consumers would respond to the shampoo overall and how they would respond to the planned attributes of the changed product. The client also wanted to understand how the brand would be perceived by consumers on 4 functional dimensions including anti-dandruff and anti-hairfall.
- HBG conceived the study as a product placement study with consumers whose most preferred brand was the current brand of the client. We needed to reach respondents whose major motivation for using the current brand was one of the 4 functional attributes which the client wanted to evaluate the new product on. The product would be placed as an unbranded product with appropriate packaging. We also formed 4 different respondent groups to evaluate the consumer receptivity to the product on these 4 functional dimensions. HBG then designed a questionnaire to be administered post placement of the product with respondents for a period of 2 weeks. The questionnaire had questions on overall likeability, likeability compared to current brand, overall fragrance, fragrance during application, ability of shampoo to cleanse oil and dirt, foaminess and other product attributes. Questionnaire also included questions on how testers evaluated the product on the 4 functional dimensions each of which was broken down into a battery of more granular attributes. Besides this, willingness to purchase the product if it replaced the current brand was also asked about. Questionnaire was mostly quantitative with some qualitative “why” questions for each product attribute. A combination of Likert-type and “just right” evaluation scales were used.
- A sample size of 1880 was obtained after cleaning with more than 400 respondents in each group. Data was collected from households in the and C socio-economic groups. Only metro cities were selected for the testing.
- Analysis was carried out using frequencies, cross-tabulations and mean scores for the most part. A Bayesian Belief Network analysis was also conducted to understand how perceptions on the different attributes influence one another and the final dependent variable – likelihood of purchase. The results were shared with the client in PowerPoint format with recommendations and an executive summary
Case Study 4 – Customer Satisfaction for Potential Investor
- The client, a private investor, wanted to understand customer satisfaction for a brand of ‘halal’ cosmetics available in India which he had invested in. The line is sold through both general online retailers as well as physical branded stores.
- The client shared a database of users of the brand. HBG planned the research as a traditional quantitative customer satisfaction and loyalty study with some qualitative questions. The major questions were on a) product likeability b) overall satisfaction c) willingness to repurchase d) willingness to recommend. Further deep diving was done on dimension level satisfaction like product quality, product range, Price and in-store experience etc. A sample size of 400 was planned through random selection from the database. The final sample size achieved was also 400.
- The data was analyzed using frequencies and cross-tabulations in line with the business objectives. An NPS score was also calculated. Further slicing of the data was done for and comparisons made between two age groups – 18-35 and 36 and above. Besides this, a structural equation model was used where the granular attributes were classified as planned into broader performance dimensions like contemporariness, style, innovation, gentle, product quality etc. The model helped understand major drivers of willingness to recommend the brand. The model had the following structure: Performance Dimensions, Overall Customer Satisfaction, Loyalty (Willingness to repurchase + willingness to recommend). Besides this, open-ended verbatims were textually analyzed to understand major strong points of the brand in terms of likeability and major weaknesses in terms of customer perceptions. Questions were also asked on source of awareness of the brand.
- The results were presented in the form of a PowerPoint presentation with an executive summary of results as well.