Understanding customer preferences and optimizing product offerings are critical for business success in any industry. Take Amazon, for example: had it continued to only sell books online, it likely wouldn't be the global retail giant it is today. Instead, it evolved with its customers' needs and preferences. Two advanced market research techniques, Maximum Difference Scaling (MaxDiff) and Total Unduplicated Reach and Frequency (TURF) analysis, provide deeper insights into consumer behavior to help companies do just that.
MaxDiff analysis determines the relative importance of various attributes by asking respondents to choose the most and least important options from a set. This helps prioritize product features and develop effective marketing strategies. TURF analysis identifies the optimal combination of products to reach the maximum number of consumers with minimal overlap, aiding in portfolio optimization and market segmentation. This blog explores the concepts and applications of MaxDiff and TURF analysis, including a case study illustrating their use in enhancing customer loyalty.
MaxDiff Analysis
MaxDiff is a survey-based research technique used to measure preferences among a set of items. Unlike traditional ranking or rating methods, MaxDiff forces respondents to make trade-offs by choosing the most and least preferred items from a subset. This approach reduces response bias and provides a clearer picture of relative importance.
Why Use MaxDiff?
- Measurement of relative importance: MaxDiff measures the relative importance of various attributes by asking respondents to identify the extremes (most and least preferred) within a subset. This method provides more discriminatory power than simple rating scales.
- Reduction of response bias: By requiring respondents to make trade-offs, MaxDiff minimizes the tendency to give extreme or identical ratings to all items, leading to more reliable data.
- Reduced survey fatigue: Traditional ranking methods can be challenging when dealing with many items. MaxDiff simplifies this by determining the overall order based on respondents’ selections, making the process less tiring and more efficient.
Example Application in Loyalty Rewards Programs
A typical MaxDiff survey might ask participants to choose between different features of a loyalty rewards program, such as the ability to save points, extend expiration dates, or receive rewards automatically at the store register. The results help identify which features are most valued by customers and should be prioritized in the program design.
TURF Analysis
TURF analysis is a technique for identifying the combination of product attributes or marketing messages that reach the largest audience with the most efficiency. This method is beneficial when resources are limited and reach needs to be maximized without overextending.
Why Use TURF Analysis?
- Portfolio optimization: TURF analysis helps select the optimal combination of product features or marketing messages to maximize audience reach. This is crucial when trying to achieve the highest impact with limited resources.
- Flexibility in reach criteria: TURF can adapt to various criteria for what constitutes "reach," whether it is the top choice, the top three, or another defined metric. This flexibility allows for a tailored approach to different market needs.
- Data input variability: TURF can utilize data from multiple types of survey questions, including MaxDiff, rank order, and single or multiple selections, making it a versatile tool in market research.
Example Application in Product Marketing
In a product marketing scenario, TURF analysis might evaluate which combination of features (e.g., price, product type, promotional offers) appeal to the broadest segment of the target market. By analyzing different combinations, the business can determine the optimal product mix to maximize market penetration.
Case Study: Enhancing Customer Loyalty
An Andrew Reise client in the retail auto parts industry wanted to enhance its customer loyalty program using MaxDiff and TURF analysis. The objective was to identify the program's most valued features and optimize the design to increase customer satisfaction and engagement.
Project Summary
The project involved distributing a survey to 420,000 customers, with 2,193 completed responses. The survey included 22 questions designed to capture preferences and behaviors related to the loyalty program. The insights gained from this survey were used to inform decisions about program enhancements.
Key Findings from MaxDiff Analysis
- Preference for banking points: The ability to save or bank points for future use was identified as the most preferred feature. Customers value the flexibility to redeem points when it is convenient for them.
- Extended expiration dates: Another highly valued feature was extending the expiration date of rewards from 90 days to 6 months. Customers expressed a desire for more time to accumulate and use their points.
- Automatic rewards at register: Receiving rewards automatically at the store register, instead of via mail or email, was also a popular preference, indicating a desire for immediate gratification and ease of use.
Key Findings from TURF Analysis
- Optimal feature combination: TURF analysis revealed that the combination of extended expiration dates and the ability to bank points reached the largest audience. This combination was preferred by a significant portion of the customer base, maximizing the program's reach and effectiveness.
- Importance of immediate rewards: The analysis also highlighted that automatic rewards at the register should be included in the loyalty program to cater to a broader segment of customers who value convenience and immediacy.
Enhance Customer Satisfaction and Loyalty Today
MaxDiff and TURF analysis are powerful tools in market research. They provide deep insights into customer preferences and optimize product offerings. The case study of the auto parts organization's loyalty program illustrates how these techniques can enhance customer satisfaction and loyalty.
By leveraging MaxDiff analysis, businesses can accurately measure the relative importance of various attributes, reducing response bias and survey fatigue. TURF analysis complements this by identifying the optimal combination of features to maximize reach and efficiency.
As customers become increasingly malleable, the application of advanced research techniques like MaxDiff and TURF analysis will remain crucial for businesses aiming to stay competitive and responsive to their needs. Through continuous engagement and feedback, organizations can ensure their offerings remain relevant and appealing, promoting long-term customer loyalty and satisfaction.
Do you need to reduce customer churn, discover your organization’s "CX superpower," align employee actions with customer expectations, or address another significant customer experience challenge? We can build and implement a plan tailored to your unique customer experience needs. Learn more about Andrew Reise consulting here.
