Draft engaging surveys to understand customer preferences
Distribute surveys and get pertinent data from your customers
Perform statistical analysis on the conjoint analysis survey data
Chart out detailed plan of action based on the conjoint analysis results
What is Conjoint Analysis? A question whose answer can open the portal to a whole new dimension of possibilities and hitting the jackpot with smart strategies. It is quintessential to know what are the factors customers desire the most while launching a new product/service. Conjoint analysis helps businesses to uncover what are the factors which drive a customer to buy or not buy their product. Products these days have multiple features, and it is essential to know which are the factors which have struck the right chord with your customers. Conducting conjoint analysis helps to find out this and more.
Conjoint analysis is a statistical market research technique that allows organizations to understand what their customers value most about the product or service. Once they can tap this info, it is only a matter of tailoring their product to suit the needs of the majority of consumers. This is carried out by posing options into customers and asking them to pick one, just like a trade-off. These options are various combinations of the product’s features and other attributes like the price, for instance.
Consider two smartphones. One is of silver grey color and has instant delivery, while the other has rose gold color and takes a week for delivery. When you put forth the two options to your customers, their choice will reveal a lot about their preference. People who pick silver grey value delivery time more while the customers who choose rose gold value the color more. This is a simple example that compares two attributes of a product- the color and delivery time.
Another common example is that of diners picking a restaurant. Say there’s restaurant A which offers excellent food and is budget-friendly, but has poor service. On the other hand, restaurant B has meager-tasting food and is expensive, but has excellent service. With conjoint analysis, the options picked by diners will help restaurant owners to know the factors which patrons give preference to. This will help them to design the restaurant properly, find suitable locations, and fix the appropriate price.
Conjoint analysis can take up multiple attributes, builds various permutations & combinations of a product, and presents it as choices to the audience. The responses are then analyzed, and insights are drawn.
Conjoint analysis asks the question “Which product would you pick” while conventional marketing asks “How good is this product?”. Therefore, instead of asking what products customers prefer, conjoint analysis urges respondents to point the features they would pick in a real-life scenario. This trade-off helps the companies to conclude how consumers rank each attribute of a product.
There are diverse conjoint analysis methods prevalent. However, there are broadly three main categories.
CBC analysis involves prompting consumers to imitate real-life purchase behavior. It is one of the most popular methods of conjoint analysis. Here, all the features of the product are presented to the audience and the choice of the respondents are noted. Therefore, in CBC what consumers essentially do is to mimic the same behavior they do while browsing and purchasing a product in the real world. They consider the options, compare the features, and pick the one which appeals to them the most. Consequently, the feature(s) that is valued most is uncovered and made use of.
Adaptive conjoint analysis, as the name suggests, is an approach that adapts to the choices given by respondents during the course of taking the survey. The survey begins with a baseline that’s common for all, containing all the product attributes. Progressively, the nature and preferences of the respondents start becoming more evident. As a result, many features get removed while many others become prominent. The process is repeated until a specific product portrait is sketched. For example, if respondents repeatedly reject options for a smartphone with a particular OS, the options containing the OS as a feature is no longer shown to them. Therefore, the adaptive conjoint analysis proceeds with the method of pinpointing what’s relevant to a user and removing the rest from the list.
MaxDiff conjoint analysis prompts respondents to select their most valued and least valued feature(s) from the listed choice. A blend of many features is presented as multiple options from which the audience picks their most & least favorite ones. As the survey progresses, the respondents naturally rank the feature sets shown. For example, in a choice of headphones A, B, C, D, E, assume respondents pick A. But, suppose A is not in the list, they choose the option E. From this, we can understand that E is their second-favorite choice of headphones. MaxDiff conjoint analysis subtly makes the respondents rank their preferences without presenting it to them straight.
Conjoint analysis traverses through three distinct stages:
Conjoint analysis begins with collecting data from respondents, most popularly in the form of online surveys. The survey questionnaire helps the organization to know what are the preferences of their target audience; what features they like/dislike, what are the things they value while making a purchase. Since conjoint analysis involves mimicking the real-world purchase via trade-offs, the data gathered is accurate and immensely helpful. An engaging survey questionnaire helps to collect pertinent data from respondents.
Once the respondents enter their choices and data is collected, the next phase of conjoint analysis is to analyze the data. The data undergoes statistical analysis which yields results that businesses can use to understand customer needs and market trends. The data is presented as detailed reports, graphs, pie-charts, and the likes to get a firm idea. Based on the insights the survey data throws light on, the business can make better decisions.
The final stage of conjoint analysis is to take actionable plans based on the survey insights. The business has the data and the insights to understand what the next course of action must be- whether it is a decision to introduce a new feature, improve an existing one, alter the price, etc. The organization can now easily come up with strategies that help to position the product correctly in the market, surpassing the competition, and cater to customer needs efficiently.
Conjoint analysis helps a business to uncover crucial data about their target market and customer preferences. Multiple features are presented to respondents and broken-down to get the feature which appeals the most to customers. There are many benefits of employing conjoint analysis to data.
Conjoint analysis helps to find out the individual preferences of customers based on the trade-offs they are prompted to do while selecting various features of a product together. Unlike conventional marketing, these trade-offs mimic real-life purchasing trends which help to understand what factors resonate best with consumers.
Conjoint analysis yields insights and valuable conclusions which enable businesses to make better decisions and develop effective strategies. In addition, it also throws light on the areas which require attention. For example, if consumers are consistently skipping choosing a particular feature of your product, you can understand that it either is of little importance to them or they dislike the current version of it. Consequently, you can either improve it or rope-in new features which provide value to clients.
Performing conjoint analysis helps an organization to understand if their product fits market needs and reaches customer expectations. Understanding this is crucial; the market instantly sinks a poorly positioned product with misfit features that offer no value to customers.
Conjoint analysis enables companies to understand where their brand stands amidst competition. For example, if respondents are picking a particular brand of potato chips over others recurrently, it is evident that the brand value of that company is high.
Evaluating brand equity and gauging the impact of market share is yet another evaluation conjoint analysis does. As a result, companies can allocate their resources better as they know what appeals to their audience the most and eliminate all superfluous features which offer no or little value to them. Consequently, the business can terminate all additional and unnecessary overhead costs which translate into better sales & development.
If a brand is thinking of revamping their product and services, conjoint analysis helps them best. Many examples show that even making the slightest change can impact the market value of a brand drastically. Therefore, it is always good to tread with caution. Do the homework thoroughly before venturing out.
Conjoint analysis is your best bet if you are:
On a concluding note, conjoint analysis help to understand what your customers expect and want and do the needful accordingly. With conjoint analysis, in addition to knowing what customers want, you can also understand what you are capable of providing them as well. Employ conjoint analysis for:
SurveySparrow comes with a conversational survey interface which brings an increased survey completion rate of up to 40%. With display logic and skip logic features, you can build smart surveys that pose only relevant questions to the audience and skip the rest. With diverse question types like image choice, multiple choice questions, opinion scale, etc., you can engage your audience and get pertinent info from them. When implemented right, conjoint analysis can bring huge returns to your business. Figure out what are the preferences of customers and why they are so. This will help you get a clear picture of how your product can make a difference.
SurveySparrow is an awesome survey software when it comes to completion rate. It helped me get 93% of completion rate for my recent survey, which I got below 25% with another tool.
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