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How to conduct a product optimization study

Learn how to improve your products with feedback from your target customers.  

Are you preparing to launch a new product or refresh an existing product line? How do you know what additional functionality or features to include? Running a product optimization study will provide you with quantifiable data to use in your decision-making. Using surveys, your study gathers information directly from your target market, indicating their preferences for your products.

Conducting a product optimization study prevents you from spending time and money on product features that aren’t important to your target customers. 

Let’s look at what’s involved in a product optimization study and how you can conduct one for your products.

When you’re developing a new product or updating an existing one, you likely have a long list of features that could be added. It’s impractical to add all the features from your list—so, how do you decide which features need to be added to make your product successful? And what should the price be once you decide on the latest version?  

A product optimization study is research conducted to direct your product development, improvement, and feature decisions. It yields quantitative data and focuses on what your end user wants most. Surveys are the best way to conduct your study because the information is collected directly from your target customers. 

Brands use product optimization studies to better understand the relationships between:

  • Feature sets: Which collection of features has the most impact on purchase decisions?
  • Price points: Which price is most attractive to customers?
  • Sales & marketing efforts: Which messaging resonates with your target customers?
  • Development plans: Should you expand your line to include specific new features or models to appeal to different customer segments?

Market research, like product optimization research, helps companies make decisions that help launch successful products and updates that are backed by data.

The two most commonly used techniques to optimize products are conjoint analysis and MaxDiff analysis. Both are valuable tools for making informed decisions about products and features, and each one provides different information.

Conjoint analysis is used to evaluate how customers value different products or features compared to others. MaxDiff analysis is used to determine what your customers consider to be the most and least important features or attributes of your product. 

Use conjoint analysis, also known as trade-off analysis, to learn how your target consumers value different features or attributes. This type of research requires survey respondents to use similar behaviors as those that made shoppers make purchase decisions. 

Respondents are provided with combinations of features to compare. They are asked to read through the options and select the set they would choose to purchase. They are then presented with another group of sets with varying features to choose from. This is repeated several times, and the respondents’ answers are analyzed to determine how preferences are impacted by the presented features.

Examples of survey questions for conjoint analysis:

Question 1: If you were shopping for a new smartphone, which of the following options would be most appealing to you?

ModelSamsung Galaxy A50iPhone 12 Pro MaxGoogle Pixel 4a    None
Price$140.99$1399$479I would not choose any
Screen Size6.2 in6.7 in6.2 in
Storage64 GB512 GB128 GB
Selection

Question 2: If you were shopping for a new smartphone, which of the following options would be most appealing to you?

ModelSamsung Galaxy A50iPhone 12 Pro MaxGoogle Pixel 4a    None
Price$140.99$1399$479I would not choose any
ScreenGorilla GlassCeramic ShieldGorilla Glass
Colors available263
PlatformAndroidiOSAndroid
Selection

Questions continue in this manner, with varying combinations of attributes. Avoid survey fatigue by showing respondents no more than 10 sets of features.

Regression analysis of your gathered data will lead you to the best combination of features for your product—as determined by the people who will use it. Regression analysis is a statistical method used to estimate the relationship between a dependent variable with one or more independent variables. We can help you with the analysis and data review in your SurveyMonkey dashboard.

MaxDiff analysis is also known as best-worst scaling. This is a different way for you to quantify your target market’s preferences. Rather than presenting survey respondents with several sets of features like we did in conjoint analysis, this methodology presents one set of features and asks respondents to select only the best and worst. 

With MaxDiff analysis, you eliminate vague responses so you can hone in on only the features your respondents feel strongly about. When you know what your target market truly wants from you and your products, you can invest your time and money in developing the features that are identified as the most important ones.

A MaxDiff survey question may look like this:

Please indicate the smart TV feature that would be the most important and which feature would be the least important in your purchase decision.

Most ImportantFeatureLeast Important
◻️4K UHD streaming◻️
◻️Music streaming◻️
◻️Price◻️
◻️App store◻️
◻️Voice control◻️

This question would be followed by a series of similar questions using the same format and multiple combinations of features. Data analysis is used to quantify the value of individual criteria based on the responses of your target market.

You can analyze the data manually or use SurveyMonkey to do the calculations for you. For a look at MaxDiff and conjoint analysis in action, take a look at the Momentive study of telecom and streaming preferences.

When you’re ready to start your product optimization process, SurveyMonkey is here to help. Whether you’re looking to optimize features of your existing product or evaluate attributes for a new product, our market research solutions have you covered.

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