The Clickstream Conjoint node calculates the Importance of Product Attributes to Customers by passing an eCommerce Clickstream into a Conjoint Analysis. By replacing a traditional survey-based study, this node vastly increases survey size, eliminates survey costs and complexity, and studies what Customers actually do (versus what Customers say in a survey).

Conjoint Analysis is a market research tool that helps determine how Customers value different Products Attributes. Product Attributes are those features, functions, and benefits (including Price) that characterize Products. Conjoint Analysis is used in marketing, product management, and operations research. It is frequently used to test Customer acceptance of innovative new Products and Services, evaluate Product Positioning, and test new Pricing.

Conjoint Analysis traditionally depended upon physical surveys that caused test subjects to make trade-off decisions between a set of Product Attributes. For example, the test subject may be asked whether they would be willing to pay a specific premium for a higher performance version of a given Product. The survey format presents each test subject with a choice between at least two Products, along with a subset of Features from which to base a selection.

While Conjoint Analysis has been proven as powerful science over many decades, there are drawbacks that limit its application. Designing a Conjoint Analysis study can be complex, and each test subject must iterate through many rounds of choices before Product Attribute Importance can be accurately assessed. Furthermore, shoppers often respond differently within a survey environment than when actually shopping for Products (what shoppers say is not the same as what they do). This results in small sample sizes and expensive studies that lag real-world Market conditions.

Replacing a survey with an eCommerce Clickstream solves these problems. eCommerce sites usually offer a vast selection of Products to take advantage of the “Long Tail” of Customer preferences. These Product selections encompass a comprehensive range of Product Attributes – many more than could be covered by a Conjoint Analysis survey. Sample sizes are also vastly greater, comprising hundreds of thousands of actual shoppers versus merely tens or hundreds of survey participants. There is no survey to design as consumer behavior is captured during actual shopping events.

Conducting continuous Conjoint Analysis on the Customers shopping at an eCommerce site provides opportunities to give shoppers a better experience while simultaneously increasing the retailer’s profitability – even when the identity of those shoppers remains anonymous. Using Conjoint Analysis results to cluster shoppers into Customer Segments means the retailer can provide the shopper with a more personalized experience – highlighting only the Products that address the needs of the Customer Segment, and suppressing Products that clutter the website, confuse the Customer, and lead to Cannibalization. And because Conjoint Analysis results are available nearly instantaneously, it is possible to adjust Product Positioning in real-time. By highlighting those features of most Importance to the Customer, the retailer can help the Customer make quick decisions unimpeded by extraneous information.

But results also satisfy the traditional needs of Conjoint Analysis. Part-Worth Utilities can be utilized by the retailer or fed back to manufacturers during New Product Development cycles. These new Product concepts can be designed to fill gaps in a Product Line or satisfy the unmet needs of emerging Customer Segments. Market Simulation can be used to predict future Market Share and optimize Prices.

This is Patent Pending Technology.

This Premium Node is not available as part of the free Community Edition. Premium Nodes help clean and connect real-world data to Market Simulations, and provide advanced Market Science analysis. Note that these descriptions are often deliberately vague.

The Clickstream Conjoint node calculates the Importance of Product Attributes to Customers by passing an eCommerce Clickstream into a Conjoint Analysis. By replacing a traditional survey-based study, this node vastly increases survey size, eliminates survey costs and complexity, and studies what Customers actually do (versus what they say in a survey).

Product Rankings

The Output Product Rankings lists the calculated results from the first step of Conjoint Analysis. The estimated preference for each Product is ranked by Customer according to an algorithm that is applied to the Clickstream Log File.

Partworth Utilities

The Output Partworth Utilities table contains the calculated results from the second step of Conjoint Analysis when a multiple regression analysis compares each Customer’s Total Utility against the presence or absence of the Categorical Attributes of the Products, as well as the Numerical Attributes of the Products. The beta coefficients are calculated for each Attribute-Level according to a Least Squares Multiple Linear Regression algorithm.

Attribute Importance

 The Output Attribute Importance table contains the results from the final step of Conjoint Analysis when Part-Worth Utilities from individual Customers are aggregated into overall Importance Levels.