Why use conjoint analysis

Posted on 29 August 2016, updated on 30 December 2016

Do you know what your customers value the most (and least) about your product? With conjoint analysis, you can. Uncovering customers’ preferences provides valuable information to guide decisions about new products, marketing strategy, advertising and promotion to increase sales.

This technique is frequently used for all types of products such as consumer goods, electrical goods, life insurance plans, retirement housing, luxury goods and air travel. Don’t have a large marketing budget to use conjoint analysis? That’s OK: Conjoint.ly does simple conjoint analysis for you. Even small businesses such as local grocery stores or restaurants can benefit from conjoint analysis. A profit motive is not necessary either, for example charities can use this technique to find out donor preferences.

Where is conjoint analysis used?

Conjoint analysis can be used in a number of different industries for a variety of applications where you need to know what kind of product your customers are likely to buy.

Pricing. Need help deciding on the right price for your product, balancing the uptake by customers and profitability? Conjoint.ly helps you find optimal price by simulating customers’ behaviour in the market based on their revealed preferences?

Product feature selection. Deciding which features to implement in your product? Conjoint.ly reveals your customers’ true preferences, including how much they are prepared to pay for different features.

Plan creation for telcos. $40 or $70 a month? 3GB or 5GB data inclusion? Conjoint.ly will help you decide the best option to grow your business without expensive in-market testing of different product combinations.

For FMCG companies. Want to quickly test an idea for a new flavour or size? Conjoint.ly will help you automatically set up an experiment, gather and analyse responses – no need for big market research budgets.

Principles of conjoint analysis

Conjoint analysis is a proven statistical technique used in market research to measure how much customers value an attribute (or product feature) of a good or service. There are many types of conjoint analysis. Conjoint.ly uses the most proven, tested, and theoretically sound type: choice-based conjoint analysis (CBC). All types of conjoint analysis have the same basics: products are broken down into features, and customers are faced with trade-offs when deciding which combination of features/attributes/levels to buy. In choice-based conjoint, respondents are presented with several questions, each a set of two to five products, and are asked to say which one they would buy or choose. The results are then used to calculate a numerical value (known as a “utility score”, “utility” or “part-worth”) that measures how much each attribute and level influenced the customer’s decision to make that choice. These scores are not absolute, but relative to other attributes and levels within the experimental settings.

What is unique about doing conjoint analysis on Conjoint.ly

Quick to set up. It only takes a few minutes to set up your experiment with a simple wizard, which will help you choose appropriate settings and suggest the minimum sample size. You do not need to customise and test any survey with Conjoint.ly – our system does that for you. You can either get Conjoint.ly to send out invites to participants on your behalf or share a link with them.

Easy on respondents. Experiment participants only need to respond to several questions of which product concepts they prefer most. It typically takes a few minutes and is easy to answer on their mobile phone, tablet, or computer.

Smart analytics done for you. You do not need to know the theory of discrete choice experimentation (DCE) or conjoint analysis. Conjoint.ly guides you through the process, uses state-of-the-art analytics behind the scenes to crunch the numbers, and checks validity of reporting.

Insightful reporting. Conjoint.ly gives you insights about customer preferences of different product features and pricing in a simple interactive report, which you can export and share with colleagues.