However well informed marketers are about their audience segments, the real factors that affect their decisions can sometimes feel like an unfathomable mystery.
If only we had a crystal ball to tell us what people want from our product, and how much they’d be happy to pay for it.
Crystal balls are in short supply, but there is a survey methodology that is explicitly designed to tell you what your customers are really thinking when they’re making a purchase: conjoint analysis.
Conjoint analysis sounds complex, but it’s really just a statistically sound method of comparing choices. By taking the time to understand and deploy it you can gain you amazing, almost psychic, insight into your market, your competitors, and your next marketing strategy.
Conjoint Analysis Simplified
A conjoint analysis survey presents respondents with full descriptions of various products and asks them to choose which among the presented options they would buy.
Conjoint questions look something like this:
Which of the following fitness tracking gadgets would you purchase?
|worn on the wrist
|clips to clothing
|put in pocket
|syncs automatically with mobile device
|requires manual sync to mobile device
|does not sync with mobile devices
|battery life 8 hours
|battery life 6 hours
|battery life 4 hours
By repeatedly asking them to choose between fictional products that have different combinations of features, we can identify which features are the most important to our audience and which ones don’t matter so much.
Some conjoint surveys also include an option of “I would defer my purchase” to indicate that none of the proposed feature sets are appealing.
This particular type of analysis is known as “choice-based” because it offers respondents a choice among different products, and it’s the most commonly used method. There are other variations, but we’re going to focus on the choice-based model here.
At the end of this type of study you should be much more familiar with your audience’s inner workings. Specifically, a good conjoint study can reveal:
- The trade-offs your customers are willing to make between various features
- A price point that your market finds appealing for your chosen feature set
- Which features are of the highest value to your chosen market
- What share of the market prefers your competitors’ feature set and/or price to yours
- How potential new features will impact your market share
- A forecast of what impact your proposed product changes are likely to have on your product’s place in the market
Our goal in running a conjoint analysis is one of predictability. We want, “a set of data that can be used to build market models which can predict preferences or estimate market share in new market conditions in order to forecast the impact of product or service changes on the market.”
When to Run a Conjoint Analysis
Designing and administering a conjoint analysis is a complex undertaking, so you want to make sure you’ve got a strong need for its insights.
In the case where most of your audience’s buying decisions are based on emotion, conjoint probably won’t be revelatory. Sadly you’ll be restricted to your crystal ball.
But if your product offers a discrete feature set that is likely to be compared with those of your competitors, conjoint is almost certainly a perfect fit for you.
Brett Jarvis offers a very helpful list of appropriate scenarios in his article Conjoint Analysis 101. According to him, these “difficult aspects” of a marketers job can benefit from conjoint:
- Product development
- Competitive Positioning
- Product Line Analysis
- Resource Allocation
Additionally, if you find yourself asking these types of questions, conjoint will be just the psychic power that you’re looking for:
- How should we price our new product to maximize adoption?
- What features should we include in our next release to take market share from our competition?
- If we expand our product line, will overall revenue grow, or will we suffer too much cannibalization?
- For which value-added features is the market willing to pay?
Setting Up Your Conjoint Analysis Survey
Avoiding survey fatigue and getting statistically relevant weights for each of your product options are vital parts of constructing this type of study.
You can’t show respondents too many different combinations of features without risking burnout and poor data, so it’s best to limit the product features you’re testing (called attributes) to no more than three or four per study.
By then keeping your levels to three as well you create a manageable number of combinations for your audience to rank. This keeps the survey sufficiently short and gets you the best possible data.
For our example above, the attributes and levels look like this:
|Brand A, Brand B, Brand C
|$250, $100, $75
|syncs automatically with mobile device, requires manual sync to mobile device, does not sync with mobile devices
|8, 6, 4 hours
Then you’ll create combinations for each of these attributes and levels.
How Deal With Conjoint Data
After each respondent has ranked each combination, you’ll be able to create values for each of your levels. These will give you direct insight into the relative importance of each one for your target audience(s), as well as what trade offs they find acceptable.
The goal here is to get to the point where you can predict with a strong level of confidence which combination of price and features will allow to increase your market share and/or steal some from the competition.
So in our fitness gadget example, we might get the following values for our battery life and mobile sync levels:
|Battery Life Options
|Mobile Sync Options
Now we can create fictional products and predict which one our audience is likely to prefer using these level values:
|automatic sync with mobile device
|manual sync with mobile device
|6 hour battery life
|4 hour battery life
|worn on wrist
|placed in pocket
Without ever making these products, we can see which one has the best chance of getting purchased, thanks to a conjoint analysis.
In case that wasn’t enough, “[t]hese values can be calculated for individuals as well as for the overall market, which means you can use conjoint analysis to segment your market based on respondent characteristics, needs, and preferences.”
Hello, crystal ball.
Conjoint Analysis: Complicated, But Worth It
Breaking your product down into distinct attributes can be challenging, as can designing and administering the survey. The right software is crucial, but so is a careful approach to the conjoint process.
But the payoffs — insight into your audience’s priorities, purchase intent, and preferences — will more than reward you for your efforts.