Research Objective

• A leading healthcare technology company needed to identify existing product attributes within a product line that were not optimizing incremental customer reach.
• The focus was on both product features and offers.
• A survey would need to be designed, scripted, and fielded among healthcare professionals.

Scope & Methodology

• A MaxDiff and TURF analysis was required to identify the best/ideal set of product attributes and build an optimal model of product combinations/attributes that would reach the maximum number of unduplicated customers.
• After completing the analysis of the best product attributes, an interactive simulation of customer preferences was designed to observe all possible attribute combinations.

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Value Delivered

• As a result of these analyses, the client was able to build a more effective product line consisting of the most preferred product line while also maximizing customer reach.
• With this information, they determined that 90% of participants were very likely to purchase from this combination of product offerings.

Learn more

• Understanding Relative Importance of Healthcare Imaging Features for New Product Development – A survey + MaxDiff case study
• Optimizing Healthcare Technology Offerings to Avoid Cannibalization | A MaxDiff TURF case study
• Tips for the First-Time Conjoint Analysis Researcher

Research Objective

• A top retail food chain wanted to understand consumer product substitutions in order to prevent potential cannibalization in sales.

Scope & Methodology

• A survey was designed to gather consumer perceptions of multiple product flavors.
• Hierarchical Cluster Analysis/segmentation was conducted using the following process:
  • Identify data requirements and build a survey designed for a cluster analysis
  • Identify product sets with 2, 3, or 4 flavors along with their potential substitutions
  • Map purchase intent for product flavors to understand the impact of substitution

Value Delivered

• The results showed that certain sets of flavors were less likely to lead to substitutions and cannibalization. The client was able to choose a set of flavors where consumers would be more likely to use more flavors and remain loyal to the brand.

Check out other food case studies

• Measuring Consumer Preferences for Successful Ready-To-Eat Development | A Sensory Research Case Study
• Benchmarking Brand Awareness and Competitive Brand Space – A consumer food survey case study
• Sentiment and Content Analysis of Qualitative Consumer Comments – A food survey + text analysis case study

Research Objective

• A leading food company wanted to understand the sales impact of various trade schemes.
• They wanted to deconstruct sales in order to differentiate the impact of various schemes (lift analysis) and to understand how price, promotion, schemes,and competition activity impacted sales.

Scope & Methodology

• Created multiple regression models for key SKUs to determine the impact of trade promotions, slab based discounts, internal cannibalization, competition activity and seasonality on their overall sales
• Calculated sales lift & ROI for each promotion to help optimize budget allocation

Value Delivered

• A scheme simulator was built that allowed the business team to align their trade promotion calendar to meet budget constraints and achieve the desired sales lift for their portfolio.
• The simulator now guides future investment decisions.

Check out other retail case studies

• Consumer Perceptions Towards Online Ordering – A retail survey + desk research case study
• Launching a Fast Food Franchise In A Competitive Market – A retail survey + competitive analysis case study
• Improving Operational Effectiveness at a CPG Company – A retail B2B survey case study