Optimize product offering and pricing based on primary customer insights

What we measure via conjoint analysis

• Attribute importance:

  Identifying which product features customers consider most deciding in purchase decisions

• Optimal product configuration:

  Determining the feature and price combinations that maximize sales, margins, revenue, etc.

• Willingness to pay:

  Quantifying to which extent customers are willing to spend more on features of products or services

• Competitive simulation:

  Assessing how changes to your offering in price and/or attributes impact competitive position

How we apply conjoint analysis in projects

• Attribute Definition:

  We interact with you to gain in-depth understanding of your product/service an define which attributes and options to measure

• Experimental Design:

  We design a choice-based survey covering all attributes and options for respondents to evaluate via hypothetical product/service comparison

• Statistical Modelling & Analysis:

  We calculate utility scores for each attribute level and price point based on choices made by respondents

• Simulation & Strategy substantiation:

  We test scenarios based on the results and translate data into concrete product and pricing strategy recommendations

Typical primary data sources we use

• Customer and consumer panels
• Targeted online survey audiences
• Your current (and possibly former) client base
• Pre-determined custom respondent lists

The output we deliver

• Actionable strategy recommendations:

  Clear and concise advice on how to optimize price and product offerings, supported by objectively quantified customer preferences

• Simulation reports:

  Documentation of tested scenarios and expected outcomes for evaluated price/attribute combination

• Interactive simulation dashboards:

  Visualization of results that allows decision-makers to explore scenarios and sensitivities interactively

When conjoint analysis is most valuable

• When launching new products or services
• When developing new pricing strategies
• When deciding on product/service (re-)positioning
• When making feature prioritization decisions in R&D