Thought Piece
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The right research methodologies provide deep, actionable insights into your target consumers’ preferences, behaviors, and needs – leading to confident decisions. We leverage the most advanced and trusted methodologies to get you the answers you need so you never have to go into a meeting unprepared again. Wondering which methodology is right for you? Read on and send us an email if you’d like help.
What it is: A research method used to determine preference levels among multiple items. Respondents are asked to select the most and least important items from a list.
How it works: Participants see sets of items and choose the most and least preferred within each set. This process is repeated across multiple sets to capture consistent preferences. (See how we do this)
When to use it: When you need to prioritize features, benefits, or messages. It’s particularly effective in product development and marketing strategy. Can be used instead of a ranking exercise as it provides a relative ranking result to know how much more important one item is compared to another. (MaxDiff is best when you want a total ranking of 5+ items/options/benefits)
Example: A tech company can use MaxDiff to determine which features of a new smartphone are most valued by potential customers.
What it is: Comparing items in pairs to evaluate their relative importance.
How it works: Respondents compare two items at a time and choose which they prefer. The process is repeated until all possible pairs are compared.
When to use it: Ideal for evaluating a small set of items. Useful in decision-making processes where trade-offs are considered. Can be used instead of a ranking exercise as it provides a relative ranking result to know how much more important one item is compared to another.
Example: A food company can use pairwise to determine which flavor of a new snack product is preferred by consumers.
What it is: Helps to identify the optimal combination of items to maximize market reach.
How it works: Calculates the total unduplicated reach (the number of unique consumers) and the frequency (how often they are exposed) of different combinations of items.
When to use it: Best for product assortment decisions and marketing campaigns where maximizing reach is essential.
Example: A beverage company might use TURF analysis to determine the best combination of drink flavors to offer in a new product line.
What it is: Measures customer loyalty and satisfaction by asking one simple question: "How likely are you to recommend our product/service to a friend or colleague?"
How it works: Customers respond on a scale of 0-10. Scores are categorized into Promoters (9-10), Passives (7-8), and Detractors (0-6). The NPS is calculated by subtracting the percentage of Detractors from the percentage of Promoters.
When to use it: Ideal for measuring customer loyalty and predicting growth. Use it regularly to track changes over time.
Example: An online retailer can use NPS to gauge customer satisfaction and identify areas for improvement in their shopping experience.
What it is: Helps determine how customers value different features of a product or service.
How it works: Respondents are presented with a set of products/services with varying features and asked to choose their preferred option. The data reveals the relative importance of each feature.
When to use it: Perfect for product development and pricing strategy to prioritize the features that are most compelling to consumers
Example: An automotive company can use conjoint analysis to determine which car features (e.g., fuel efficiency, safety, price) are most important to potential buyers.
Whether you're prioritizing product features with MaxDiff, measuring customer loyalty with NPS, or exploring preferences with conjoint analysis, each method offers unique advantages.
