For many businesses, uncovering genuine customer preferences feels like trying to read minds. Traditional surveys frequently fail to reveal true preferences because they don't force people to make tough choices similar to those they make in real life. Enter Best/Worst Scaling, which makes it easier to prioritize product features based on data.
Best/Worst Scaling, also known as MaxDiff, is an analytics tool that helps businesses understand what their customers truly value. It's like a tug-of-war for product features, where consumers must choose the best and worst options from a list. This method reveals what people like and how much they like it compared to other options.
Best/Worst Scaling can be a valuable tool to cut through the noise and get clear answers, including to:
Fine-tune marketing messages
Understanding customer preferences
Prioritize product features
What is Best/Worst Scaling?
Best/Worst Scaling is a survey method that asks people to pick the best and worst options from a list. We use this approach to help understand how much people like or dislike each item on the list.Â
The strength of this method is that it forces choices, providing a clearer picture of true preferences.
To understand why Best/Worst Scaling is valuable, it's important to compare it to other ways of measuring preferences.
Best/Worst scaling compared to ranking questions
Ranking questions asks people to rank items from best to worst. This shows the order of preferences but doesn't reveal how much one thing is liked over another.Â
Best/Worst Scaling solves this problem by providing numbers that show the order and the strength of preferences for each item. Sometimes, the gap between people's first and second choices is huge, while other times, it's tiny. Knowing these distinctions can help businesses make smarter decisions about what to focus on.
Best/Worst Scaling can also handle longer lists. Ranking becomes difficult with more than 7-10 items, but Best/Worst Scaling can work well with 30-40 items, sometimes even up to 100.
Best/Worst Scaling compared to conjoint analysis
Both Best/Worst Scaling and conjoint analysis make people choose between options, revealing true preferences. However, they're used for different purposes.
Conjoint analysis examines multiple things together, considering features, price, and brand all at once. Best/Worst Scaling usually looks at one type of thing at a time, such as product features or marketing messages.
It is simpler to set up and analyze, making it great for determining which items on a list are most important. Conjoint analysis is more complex but can show how different factors affect people's choices.
Researchers often use Best/Worst Scaling to decide which features to focus on when making a product. Conjoint analysis helps understand how different combinations of features, price, and brand affect purchasing decisions.
How businesses use Best/Worst Scaling
Businesses use Best/Worst Scaling in different ways. Product teams use it to identify the most important features for customers. Marketers use it to test different messages and decide which ones resonate best with the audience.
It helps brands understand their unique selling points in customers' minds, differentiating them from competitors.
Businesses can also use it to improve customer experience by learning which aspects of their service matter most to people. For example, when designing packaging, companies can discover which elements customers care about most.
Best/Worst scaling in action
Mill, a company that makes a food recycler, used Best/Worst Scaling to test about 20 different product messages. Our goal was to identify which messages would work best with their customers.
The results showed that different messages resonated better with different groups of people. Tech-loving early adopters preferred trendy, innovative messages, while others responded better to more general messages about how the product works.
The information gathered from Best/Worst Scaling helped Mill create better marketing campaigns. They used trendy messages for the initial product launch and used more general messages later to attract different customer segments.
How to create a good Best/Worst Scaling study
We plan carefully and consider several factors to get the most out of Best/Worst Scaling.
Some best practices for setting up your Best/Worst Scaling survey include:
Creating items to be of equal character length - otherwise, some items might be more preferred purely because they were quicker to read.
Be consistent in your use of bolding and italicizing.
Use clear, concise, and unambiguous language.Â
Collaborate with stakeholders and subject matter experts to brainstorm a comprehensive list of potential items.
Conduct pre-tests with a small sample of respondents to identify any issues with item clarity, relevance, or length. Use the feedback to refine and improve the items before launching the survey.
Things to watch out for
While Best/Worst Scaling is useful, it has some limits. The scores for individual items can't be added up to see how well they work together. If that information is needed, conjoint analysis might work better.
Sometimes, what people say they prefer in a study might not match what they actually buy. Real-world decisions often involve more factors than a study can cover.
We avoid these drawbacks by using thorough and experienced researchers to design and run surveys. Â
Best/Worst Scaling is just one tool in the market research toolkit. It works best when combined with other methods. Qualitative research, like focus groups or interviews, can provide context for the Best/Worst Scaling results. Follow-up surveys can dig deeper into the reasons behind people's preferences.
Sharing the results
It’s not enough to just gather insights. Explaining how companies can use insights to improve products or fine-tune marketing strategies is what turns data into action.Â
The key is to keep things simple and focused. Using relatable stories can make complex data more memorable and easier to understand. Charts work well to understand key findings at a glance. Some teams now use interactive tools that let people explore the data hands-on.Â
When everyone in the company can easily grasp and use the research, it leads to better products, smarter marketing, and happier customers. This ensures that valuable insights don't just sit on a shelf but drive real improvements across the business.
Looking to the future of Best/Worst Scaling
Improved tech brings new opportunities for Best/Worst Scaling. Mobile surveys make it easier to reach respondents in real-time and in real-world contexts, which can lead to more accurate and relevant results.
Artificial intelligence and machine learning are also improving Best/Worst Scaling. These technologies can help analyze large datasets more quickly and identify subtle patterns that humans might miss.
Even with these advancements, the core principle of Best/Worst Scaling remains the same. It's about understanding what people value most. This is what makes it such a powerful tool for businesses.
Comments