Conjoint Analysis

Conjoint Analysis is a sophisticated technique for understanding how consumers make trade-offs, thus it mimics the real purchase situation.

When we purchase a plane ticket or the options package when buying a car we do not just look at the price in isolation but we weigh up (trade-off) different aspects in our mind. For example, with a plane ticket, the consumer will think about price, width of seat, if it is a direct or connecting flight. The consumer does not think about each attribute in isolation. Conjoint analysis examines these trade-offs to determine the combination of attributes that will most satisfy the consumer.

Consumers are asked about their preference of  various product/service configurations. Statistics is then used to work out the trade-offs the consumer makes in his mind to arrive at the ideal product/service.

Example = cereal
Brand
Benefit claims
Product features – fat content , salt content, fibre content
Pricing
Promotion – toy

This tool allows us to:

• Measure actual or perceived benefits of your product/service
  
• Tailor marketing programmes to communicate the benefits that your target market most value in your product/service
  
• Redesign existing products or create new products
  
• Find those combinations of features with the highest purchase probability.
  
• Determine the price-performance ratio with the highest preference.

By including competitive offers, tendencies about alternative marketing strategies’ chances of success can be deducted.

understand how customers make tradeoffs in benefits, and thereby can be used to ultimately segment a market. Conjoint analysis is also useful for understanding how customers make tradeoffs in attributes, and this can be highly useful in designing products, understanding price sensitivity, and examining other practical issues.

Potential Objectives

Conjoint analyses are particularly suitable for:

• Testing new products’ readiness for marketing
• Reviewing the market position of established brands
• Checking the impacts of product modifications
• Testing the acceptance of new product versions
• Estimating the market shares of new products in their competitive environment
• Determining the optimal prices (with PRICE.TUNER® - profitability based on correct pricing)

Packaged goods. Decide on benefit claims, product features (for example, fat content, flavour, salt content), packaging (can versus bottle), labeling, and pricing.

Telecommunications. Decide on pricing structures (monthly or per minute pricing) and service features.

Financial services. Decide on optimal service bundles (for example, credit card annual fees, interest rates, and rewards).

Tourism. Decide on optimal combinations of attributes for package tours (destination, number of days, number of meals, and package price).

Consumer electronics. Decide on electronic features and pricing.

Automotive. Decide on options packages.