- How do I appeal to the largest number of consumers? (TURF analysis)
- How do I prioritise marketing messages or product attributes? (Max Diff)
- How do I find out what people value in my (new) product / service? (Conjoint)
- How do I identify what drives a desired behaviour or outcome? (Key driver analysis)
- How do I know what to prioritise to meet strategic goals? (Gap analysis)
- How do I build consumer loyalty? (Consumer journey mapping)
- How do I use behavioural science to improve my research? (Cognitive biases)
- How do I live without you? (LeAnn Rimes)
- How do I know how many people will buy my product at a given price? (Van Westendorp’s price sensitivity meter)
- How do I assess the impact of my advertising? (Ad effectiveness)
- How do I turn data into clear findings (Data visualisation)
- How do I tap into the unconscious perceptions that influence decision-making? (Implicit response testing)
- How do I reduce a large amount of data into something more meaningful? (Factor analysis)
- How do I group people together based on shared characteristics? (Segmentation)
- How do I forecast market share at a given price point? (Brand price trade off)
- How do I account for cultural differences when surveying across markets? (ANOVA)
- How do I judge brand performance relative to competitors (Correspondence analysis / brand mapping)
What does your target audience want?
Human beings are complex creatures. Sometimes we make a choice seemingly instantaneously (yes please, I’ll have another dark chocolate digestive), sometimes we spend hours researching a product only to end up not quite convinced. Unsurprisingly then, if you have a multi-faceted product or service in a competitive marketplace, it can be tricky to rely on consumers to articulate what they really value when comparing your proposition to your competitors, or what they value enough to commit to your product / service.
How then, can you understand why your product or service is liked, know how to focus on the attributes that are most valued, estimate take up of a new product or service, or test the impact of price on likely take up? With a little help from a cheeky technique called conjoint analysis is how.
What is conjoint analysis?
Conjoint is one of the more sophisticated statistical techniques available, which makes it a super powerful analysis tool. There are several ways to approach conjoint, but to avoid information overload we’ll focus on one of the most popular approaches for now – choice based conjoint (do get in touch if you’d like to chat about other types of conjoint!)
A choice based conjoint exercise presents respondents with decisions that mirror those they might face in real life, asking them to weigh up the totality of a proposition in order to decide which best serves their needs. The data captured from these choices reveals the trade-offs consumers are making in their minds, consciously or subconsciously. This data is used to model market decisions based on an understanding of how important attributes are, and the impact of varying these attributes.
The survey experience for respondents is usually quite fun. The respondent will be presented with different variations of a product / service and asked which one they would choose. A ‘none’ option can be included to accurately reflect a real-world scenario, or a response can be forced in order to capture as much data as possible and a follow up question can be used to assess whether they would really go on to make the purchase (this is called a dual-response ‘none’ approach).
What insight will conjoint give me?
Analysis of a choice based conjoint exercise provides three main outputs that can be explored by different audience subgroups:
- The importance of each element of the product / service being tested. For example, if a respondent always chooses the proposition that includes Brand X, regardless of the other components of the propositions, that respondent is very brand orientated with high loyalty to Brand X. Across all respondents we might see that brand accounts for 20% of the decision for your product / service
- Within each element, the most preferred option. For example, an 18 month contract is preferred by 32%, a 24 month contract by 25% etc.
- The ability to model how changes to different elements of the product / service e.g. price, core proposition, delivery mechanism, contract length etc. impact likely take-up
In summary, choice based conjoint provides you with a playbook for how to develop your product or service in line with what your target audience wants.