Enhancing Marketing Tactics with XLSTAT’s Advanced Analysis Features

Understand customer preferences, prospect needs, and industry trends with these five advanced data analyses

In the world of marketing, there are countless ways to consume data based on the specific questions and goals of your team. Whether you’re looking to identify your top-performing line of merchandise, release new products based on consumer preferences, or refresh messaging to include priority attributes, XLSTAT can answer all of these questions and more. 

This blog identifies five of the top advanced analytics applications available in XLSTAT – TURF analysis, conjoint analysis, Bayesian networks, MaxDiff analysis, and PLS path modeling – and how they help drive marketing decisions.  

TURF Analysis

TURF — or Total Unduplicated Reach and Frequency — is an advanced analysis method used in marketing to determine a specific line of products that has the highest market share and maximum reach. 

Let’s take a look at an example. A large candy manufacturer is looking to maximize Halloween candy sales and has decided to produce a new bag of assorted candy with the company’s most popular candies. After surveying current customers and looking at purchasing behavior and data, the marketing team runs a TURF analysis to determine which six (you can choose whichever number you’d like) has the greatest reach and frequency.

The results show that consumers love the peanut butter-, dark chocolate-, and caramel-flavored candies the best, urging the team to bundle these candies into a new bag for the upcoming holiday. 

Running this sort of data-driven analysis lets the manufacturer focus production efforts on a small subset of candy that will be successful and have the best chance at generating revenue in stores.

Conjoint Analysis

In a conjoint analysis, market researchers and product managers are able to simulate a buying scenario to test new products and understand the preferences of their target market.

Take for example a wireless carrier looking to introduce a new phone plan. They might be interested to know if consumers prefer a prepaid plan or not, how many gigabytes of storage they need, if consumers would like mobile hotspot capabilities, and the cost, among other aspects. These become the features that the company would test in their conjoint analysis: plan type, storage, mobile hotspot, and cost.

XLSTAT’s conjoint analysis feature creates product combinations based on the input factors that uses predictive analysis to confirm the hypothesis done by the expert. Then, a handful of combinations can be presented to potential consumers who choose the combination that they prefer.

With cluster analysis in the conjoint analysis feature, the team can see if consistent groups emerge. The marketing team at the wireless company is then left with information that tells them which combination of features will generate the highest market share to help inform the best phone plan to introduce to consumers. 

Bayesian Networks Analysis

Using Bayesian Networks to analyze data allows users and analysts to discover important causal relationships between variables. This technique is incredibly popular in artificial intelligence as it can help navigate uncertainty.

If a marketing team was looking to learn more about its customers through data analysis, they might use Bayesian Networks. For example, say this team works for a major retailer and the company just released its new line of handbags. The marketing team is working on a new marketing campaign to push the new handbags across various platforms, and they’re considering social media, digital ads, and print ads in popular magazines. They know their main target audience is women between the ages of 24 to 35 that earn between $60,000 and $100,000 in yearly income. 

But what the team might look to understand better is where these women are shopping — or at least browsing. By using Bayesian Networks, this marketing team can correlate browsing and shopping behavior to their main target audience to determine which channel makes the most sense to put more money into: social media, digital, or print. The results could clearly indicate that women in their mid 20s to mid 30s use social media apps far more than other online or print sources. 

MaxDiff Analysis

A MaxDiff analysis is another advanced market research technique that allows companies to understand which attributes are most important to their consumers when it comes to purchasing products and solutions.

For example, at a cosmetic company, the marketing team might seek to understand if sustainably sourced products are important to customers as the trend for greener products grows. They might use the work of a MaxDiff analysis to have respondents rate a list of attributes from best to worst — or from most to least important.

This XLSTAT analysis would provide this marketing team with deep insights through clear data visualization with charts and graphs on which attributes mattered more, especially when up against historically important factors such as price. One customer might feel that against quality and packaging, cost is the most important, but once sustainability is introduced, their feelings change and sustainability becomes the most important attribute.

Marketing managers can take this information and rework marketing campaigns – and even product formulas and packaging, if the results point to that. They can also incorporate these attributes into messaging to help drive the important factor home to consumers. 

PLS-PM Analysis

PLS-PM, or Partial Least Squares Path Modeling, is an advanced analysis and statistical approach for modeling relationships among multiple variables that uses predictive analytics as opposed to causal. 

Let’s consider this use case of a car dealership looking to make sense of its customer satisfaction data. The survey that was sent out to customers asked about quality, price, and customer loyalty. By using PLS path modeling, the market research team at this company is able to determine which factors have the most influence over customer satisfaction and loyalty, allowing them to reconsider elements of quality and price — or whichever factors had the most influence — to improve their NPS. 

Improve Your Marketing Performance with Powerful Data Analytics

As you can see, there are countless applications for advanced statistical analysis and modeling to help drive data-driven decisions in marketing, and XLSTAT makes it easy to execute all of these and more. 

To learn more about XLSTAT’s advanced analysis capabilities, get your free XLSTAT trial today or contact us at lumivero.com.