{"id":7094,"date":"2020-07-23T07:00:46","date_gmt":"2020-07-23T12:00:46","guid":{"rendered":"https:\/\/flevy.com\/blog\/?p=7094"},"modified":"2020-12-18T21:11:18","modified_gmt":"2020-12-19T02:11:18","slug":"a-must-have-tool-for-market-research-and-pricing-strategy-conjoint-analysis","status":"publish","type":"post","link":"https:\/\/flevy.com\/blog\/a-must-have-tool-for-market-research-and-pricing-strategy-conjoint-analysis\/","title":{"rendered":"A Must-Have Tool for Market Research and Pricing Strategy: Conjoint Analysis"},"content":{"rendered":"

\"\"Identifying what the market wants is a critical issue for most executives.\u00a0 Likewise, the decision on how much to charge for a product is also crucial for planners. \u00a0This is where Market Research<\/a> comes to rescue.<\/p>\n

One of the Marketing Research methods that researchers most commonly employ is the Conjoint (Trade-off) Analysis<\/strong><\/a>.\u00a0 Conjoint Analysis helps in identifying product features that consumers prefer, discerning the impact of price changes on demand, and estimating the probability of product acceptance in the market.<\/p>\n

In contrast to directly inquiring from the respondents about the most important feature in a product, Conjoint Analysis makes the survey participants assess product profiles. \u00a0These product profiles comprise various linked\u2014or conjoined\u2014product features, therefore the analysis is termed \u201cConjoint Analysis.\u201d\u00a0 Conjoint Analysis simulates real-world buying situations where the researchers statistically determine the product attributes\u2014that carry the most impact and are attractive to the participants\u2014by substituting the features and recording the participants\u2019 responses.<\/p>\n

The Conjoint Analysis Approach<\/strong><\/p>\n

The Conjoint Analysis is useful in creating market models to estimate market share, revenue, or profitability.\u00a0 The Conjoint Analysis is widely used in marketing, product management, and operations research. \u00a0The Conjoint Analysis approach entails the following key steps:<\/p>\n

    \n
  1. Determine the Study Type <\/strong><\/li>\n
  2. Identify Relevant Features<\/strong><\/li>\n
  3. Establish Values for Each Feature<\/strong><\/li>\n
  4. Design Questionnaire<\/strong><\/li>\n
  5. Collect Data<\/strong><\/li>\n
  6. Analyze Data<\/strong><\/li>\n<\/ol>\n

    \"\"<\/a><\/p>\n

    1. Determine the Study Type <\/strong><\/p>\n

    The first step of the Conjoint Analysis involves ascertaining and selecting from a number of different types of Conjoint Analysis methods available.\u00a0 This should be determined based on the individual requirements of the organization.<\/p>\n

    2. Identify Relevant Features <\/strong><\/p>\n

    The next step of the Conjoint Analysis entails categorizing the key features or relevant attributes of a product.\u00a0 For instance, setting the main product attributes in terms of size, appearance, price.<\/p>\n

    3. Establish Values for Each Feature <\/strong><\/p>\n

    After selecting the key features of the product, the next step in Conjoint Analysis is to choose some values for each of the itemized features that have to be enumerated. \u00a0A combination of features in different forms should be chosen to present to the participants. \u00a0The presentation could be written notes describing the products or in the form of pictorial descriptions.<\/p>\n

    4. Design Questionnaire <\/strong><\/p>\n

    The basic forms of Conjoint Analysis\u2014practiced in the past\u2014encompassed a set of product features (4 to 5) used to create profiles, displayed to the respondents on individual cards for ranking.\u00a0 These days, different design techniques and automated tools are used to reduce the number of profiles while maintaining enough data availability for analysis.\u00a0 The questionnaire length depends on the number of features to be evaluated and the Conjoint Analysis type employed.<\/p>\n

    5. Collect Data <\/strong><\/p>\n

    A statistically viable sample size and accuracy should be considered while planning a Conjoint Analysis survey.\u00a0 It is up to the senior management to decide how they want to gather the responses\u2014by taking the responses from each individual and analyzing them individually, collecting all the responses into a single utility function, or dividing the respondents into segments and recording their preferences.<\/p>\n

    6. Analyze Data<\/strong><\/p>\n

    Various econometric and statistical methods are utilized to analyze the data gathered through the Conjoint exercise.\u00a0 This includes linear programming techniques for earlier Conjoint types, linear regression to rate Full-Profile Tasks, and Maximum Likelihood Estimation (MLE) for Choice-based Conjoint.<\/p>\n

    Types of Conjoint Analysis<\/strong><\/h2>\n

    There are a number of Conjoint Analysis types available for the marketing researchers to choose from, including:<\/p>\n

      \n
    1. Two-Attribute Tradeoff Analysis<\/li>\n
    2. Full-Profile Conjoint Analysis<\/li>\n
    3. Adaptive Conjoint Analysis<\/li>\n
    4. Choice-Based Conjoint Analysis<\/li>\n
    5. Self-Explicated Conjoint Analysis<\/li>\n
    6. Max-Diff Conjoint Analysis<\/li>\n
    7. Hierarchical Bayes Analysis (HB)<\/li>\n<\/ol>\n

      Interested in learning more about Conjoint Analysis<\/a>?\u00a0 You can download an editable PowerPoint on Conjoint Analysis Primer<\/strong> here <\/u><\/a>on the Flevy documents marketplace<\/a>.<\/p>\n

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      \u2013 Omar Hern\u00e1n Montes Parra, CEO at Quantum SFE<\/p>\n<\/blockquote>\n","protected":false},"excerpt":{"rendered":"

      Identifying what the market wants is a critical issue for most executives.\u00a0 Likewise, the decision on how much to charge for a product is also crucial for planners. \u00a0This is where Market Research comes to rescue. One of the Marketing Research methods that researchers most commonly employ is the Conjoint (Trade-off) Analysis.\u00a0 Conjoint Analysis helps… A Must-Have Tool for Market Research and Pricing Strategy: Conjoint Analysis<\/span><\/a><\/p>\n","protected":false},"author":110,"featured_media":7096,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"","footnotes":""},"categories":[81],"tags":[2099,2100,2093,2096,2098,2103,2083,2102,1602,2076,2095,2101,2094,2097],"class_list":["post-7094","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-strategy","tag-adaptive-conjoint","tag-choice-based-conjoint","tag-conjoint-analysis","tag-data-collection","tag-full-profile-conjoint-analysis","tag-hierarchical-bayes-analysis","tag-marketing-research","tag-max-diff-conjoint","tag-product-management","tag-product-pricing","tag-research-surveys","tag-self-explicated-conjoint","tag-trade-off-analysis","tag-two-attribute-tradeoff-analysis"],"_links":{"self":[{"href":"https:\/\/flevy.com\/blog\/wp-json\/wp\/v2\/posts\/7094","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/flevy.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/flevy.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/flevy.com\/blog\/wp-json\/wp\/v2\/users\/110"}],"replies":[{"embeddable":true,"href":"https:\/\/flevy.com\/blog\/wp-json\/wp\/v2\/comments?post=7094"}],"version-history":[{"count":8,"href":"https:\/\/flevy.com\/blog\/wp-json\/wp\/v2\/posts\/7094\/revisions"}],"predecessor-version":[{"id":7815,"href":"https:\/\/flevy.com\/blog\/wp-json\/wp\/v2\/posts\/7094\/revisions\/7815"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/flevy.com\/blog\/wp-json\/wp\/v2\/media\/7096"}],"wp:attachment":[{"href":"https:\/\/flevy.com\/blog\/wp-json\/wp\/v2\/media?parent=7094"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/flevy.com\/blog\/wp-json\/wp\/v2\/categories?post=7094"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/flevy.com\/blog\/wp-json\/wp\/v2\/tags?post=7094"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}