Successful conjoint analysis can get the market to work for you
Product management has been all about trade-offs. It does not matter if the objectives have enhanced the market share, revenue, or profit margin, every product manager would be required to make trade-offs such as –
- Quality vs. cost
- Richness of the offering vs. ease of use
- Time to market vs. breadth of features
The question to ponder upon would be how to know what the market wants. You may also want to know
- What market segments exist
- What would they pay
- What do those segments prefer
The answer would be to get the market to make the trade-offs for you. However, it would not be the entire market, but a representative model of the market. If you wonder how conjoint modeling uses feature tradeoffs to optimize products, let us delve into it.
You could do it as a product manager through conjoint analysis. Understanding the trade-offs market would help you understand the trade-offs you will make. Henceforth, apply your enhanced market insight to your revenue, share objective, and profit.
Is conjoint analysis suitable for you?
Conjoint analysis has been applied successfully in several industries. It would be inclusive of Smart Phones, Air Travel, Computers, Health Care, Financial Services, Electronics, and Real Estate. Does your job include configuring a set of features for a specific product or service? Rest assured that the consumer’s decision to buy would be rational. The conjoint analysis would help you with it.
However, on the other hand, if your consumer’s decision to buy has been impulsive, rest assured conjoint is not a suitable tool for you. For a technology product manager, the conjoint analysis would be easily accessible.
Due to conjoint analysis helping you understand the preferences of your market, you could apply it to a wide variety of difficult aspects of the job. It would be inclusive of competitive positioning, product development, pricing, segmentation, product line analysis, and resource allocation.
- How should you price your new product for maximizing adoption?
- What specific features should you include in your next release for taking market share from the competition?
- Will the overall revenue grow when you expand your product line? Will you suffer much cannibalization?
- What are the added-value features for which the market intends to pay?
A technology company would feel the pressure from a lower-cost alternative along with the debated lowering of its prices. The results of the conjoint analysis have shown the market valuing their products separately from their counterparts. They would not lower their prices but reconfigure the offering slightly. Consequently, the business would grow and realize significant profits that they otherwise would never have seen. Not every situation has been dramatic, but a conjoint analysis done right has been impactful.
What is conjoint analysis?
Conjoint analysis has been a set of market research techniques. It measures the value of the market places on every feature of your product and predicts the value of the different combinations of features. At the essence, conjoint analysis has been all about trade-offs and features. Using conjoint analysis, you would ask several questions forcing the respondents to make trade-offs among various features –
- Determining the value they place on every feature based on the trade-offs they make
- Simulating how the market reacts to various feature trade-offs you consider
Using conjoint analysis, you would gain insights into the value of your brand, the value of product features, and determining the price sensitivity.
Surveying the market
Conjoint analysis survey queries could take a wide variety of forms based on your study objective. However, the most common kind of query would be –
- Which plans do you intend to choose?
Deriving values for every level
From responses to these queries, conjoint analysis uncovers the underlying value for every level. It would be based on how often a level has been included in the chosen product. The relative value of the levels has been what is relevant. How the value of one level compares to the value of another.
Predicting preference for several products
After you have seen the part-worth, you should understand what trade-offs to make so a product would be relatively more desirable to the market. Such predictive feature has been the real power of conjoint analysis.
Simulating competitive markets
Every attribute level has an associated part-worth. You could develop any number of competitive scenarios by blending and matching the levels along with enhancing or reducing the number of products. It would not be wrong to suggest that the result of all conjoint analysis studies would be a simulation model. It would enable you to simulate the share of the market that prefers your product against the product of your competitor.
Simulating shares of preference has been powerful. You could run simulations endlessly. For instance, if your counterpart changes its product, you could run simulations to assist in determining your response. For those looking forward to adding a new product, you predict if that has been deemed beneficial and from which product in the present market your latest product would grab the maximum share.
These examples have been simple yet effective of the several ways that conjoint analysis might be used. For a competitive landscape, inclusive of all competitors and ensuring the predictive capacity of the approach in time, consider thinking carefully at the initial stage about the levels and attributes you intend to include in your study.
Due to conjoint analysis allowing endless scenarios to be tested in a competitive landscape, the preference share would enable the powerful what-if analysis. It would provide the insights you require for making the trade-offs eventually that you come across daily as a product manager. It would not be wrong to suggest that the insights gained regarding how you may change your position in the market, respond to competitive threats, penetrate specific segments, and grow revenue, etc. They could have a dramatic effect on the overall success of your product.
Analyzing purchase likelihood
Despite your product is relatively new and has created its market, the conjoint analysis would provide powerful insights. For market simulations and preference shares, the conjoint analysis would analyze the likelihood of your product purchase. It would be pertinent to mention here that product likelihood analysis makes the most of the total utility of the product for determining a percentage indicating the relative likelihood that the product would be bought, given several combinations of pricing and features.
Due to purchase likelihood focused on a single product, it does not consider the competition. It would be specifically helpful when you launch a new product relatively new to the market. Rest assured that purchase likelihood has often been deemed perfect for micro-level product design as well when the main product decisions have been made already. The focus would be on getting the right details.
What is the most suitable way to move forward?
The software would help you design, conduct, and analyze a conjoint analysis study on your own. However, there have been different conjoint methodologies, with everyone having their approach for the collection of data. The perfect one for you would be based on the objective of your study. Unless you were personally going to a conjoint study at least a few times a year, the chances would be more than you would look forward to engaging someone with experience in the arena to assist you to navigate such nuances.
It could be surprising to most people. However, the person you engage in the study would not be required to be an expert in your arena. They would require being an expert in applying conjoint analysis for real business issues.
Therefore, if you were looking forward to making trade-offs as a product manager, consider using conjoint analysis to get your market for making the trade-offs for you.
Optimizing pricing strategy
With numerous applications of Conjoint Analysis, your focus should be on optimizing the pricing strategy. Foremost, you should look forward to understanding how people feel about the program. You would also be required to conduct an online brainstorming tool. You would learn from the online brainstorming session and overlay it with the details about the program.
The conjoint analysis would accomplish three big things –
- Identifying the areas their current program is lacking
- Identifying the attributes of their program had the greatest impact on participation
- Identifying the maximum mix of attributes driving the highest participation rate and revenue
Benefits of using conjoint analysis
There have been several benefits associated with the use of conjoint analysis. Some of the benefits have been mentioned below –
- Replicating consumer choice and trade-off behavior
- Choosing a product among several alternatives
- Test objective is not apparent for respondents
- Inclusive of compensatory and non-compensatory models
- Flexible experimental research designs
- Predicts preference shares
- Maximum product configuration and item prioritization from the standpoint of the consumer or business
Rest assured that conjoint analysis is usually done through a respondent’s survey. You would be required to determine the levels and attributes for testing while keeping the end objective in mind.