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Pricing and price visualisation plays a crucial role in impacting consumer choices through the intricate web of psychology. Understanding psychological pricing can give you an edge in marketing and pricing strategy. It's all about understanding consumer psychology to make your offerings irresistible, rather than just the numbers on a price tag. As we continue our series on scientifically supported principles, in this part of the series, we’ll discuss Prospect Theory and Loss Aversion.

The intersection of behavioral economics and marketing has created some of the most ingenious techniques for capturing consumer attention and inciting purchasing action. At the forefront of this technique is Prospect Theory – a concept so potent that its creators, Daniel Kahneman and Amos Tversky, altered fundamental assumptions about human decision-making and rewrote the rules for 21st-century marketers.

What is prospect theory?

Prospect theory is all about how we, as human beings, perceive value. It underscores the simple reality that people are not always rational, and economic decisions are not always made based on final outcomes of maximal utility. Instead, losses and gains are immediate, causing emotional reactions that can transform the landscape of what's considered 'valuable.'

Prospect Theory proposes that individuals tend to value losses and gains differently. This theory, also known as Loss Aversion, suggests that people tend to make decisions based on potential gains rather than potential losses. The foundation of this theory lies in two key principles: Loss Aversion (the feeling of loss being stronger than the pleasure of an equivalent gain) and the importance of Framing (the impact of how options are presented).

Understanding this theory is the first step in leveraging it to create pricing (and communication) strategies that appeal to the deeper workings of the human psyche, but it's just the beginning. As we continue our series on psychological pricing techniques, we're going to explore in-depth how you can apply Prospect Theory to revamp your pricing communication and gain a competitive edge in the market.

How to apply prospect theory when messaging your prices?

How many times have you seen a banner flash 'Only 5 left!' and it's those last few that seal the deal for you? This strategy is not just a coincidence but a clever use of scarcity to trigger loss aversion. The fear of missing out (aka FOMO) is a powerful psychological motivator, compelling consumers to act quickly lest they 'lose' an advantage.

Or let’s take a warranty as an example to make things even clearer. Money-back guarantees, free trial periods, and satisfaction assurances not only reframe the purchase as an opportunity (the possibility of extra gain) - but can also drastically reduce a potential loss (i.e. being unsatisfied with the purchased product, seen as ‘money lost’) in consumers’ mind.  

To implement the Loss Aversion principle in your pricing, consider these messaging approaches:

1. Arrange prices strategically: When you arrange your products from highest to lowest price (e.g. as standard sorting in the web shop), customers are more likely to opt for the pricier options that are presented at the start. This behavior highlights how people gravitate towards avoiding losses, considering choice as a loss, and feeling the impact of loss.  
   By showcasing the more expensive items at the top of the list, customers perceive a decline in quality as they scroll down or look further onto the shelf, ultimately choosing the initially presented, more expensive selections as the 'safe choice'. So, think twice before prioritizing your lowest-priced items by default just to create an image of being an affordable brand.

2. Strategic timing for discounts: Offering discounts towards the end of the month can significantly boost the effectiveness of marketing campaigns. Research shows that customers are more financially capable at the beginning of the month, making it an ideal time for promotional, non-discount activities. Discounts, conversely, are more positively received towards the end of the month as individuals prioritize saving money during this period. This timing aligns with the 'Bottom Dollar Effect' in behavioral economics, where expenses feel more burdensome towards the month's end.  
   So, to link this with the Loss Aversion theory: the pain of losing extra dollars at the end of the month is harder than losing them at the beginning of the month. Making price discounts many people’s best friend at the end of the month.

3. Implementing a steadily decreasing discounts (SDD) pricing strategy:  
   The steadily decreasing discounts (SDD) pricing strategy engages consumers in a psychological game. By gradually reducing discounts (instead of keeping them the same or increasing them!), customers are driven by a fear of missing out, anticipating future price increases. This fear prompts them to make purchases sooner (i.e. stimulating impulse buying) to avoid higher prices later, again leveraging the principles of loss aversion and scarcity.

In all these cases, the key is to gently guide the customer towards the feeling of 'missing out' on a product or a deal. This involves highlighting the potential 'loss' that the customer might experience by not making a purchase decision immediately.  

The pitfall of overusing loss aversion strategies

The strategic use of loss aversion can be a powerful tool for marketers, but relying too heavily on playing up potential losses can diverge into manipulative territory, reducing trust in your brand and sacrificing long-term customer loyalty.

The ultimate goal shouldn’t be manipulation of your customers’ emotions but aligning with their needs and expectations in a way that builds trust and nurtures meaningful relationships.  

In conclusion, tapping into loss aversion through the lens of prospect theory is a potent method on its own, however by combining this approach with a focus on building strong customer relationships, businesses can create a winning strategy that drives long-term success.

Using psychological communication techniques to maximize your sales is one thing, but setting the right price at the base, considering your brand strength and customer expectations, is something entirely different. Both are important.  

If you're looking to take your business to the next level, you need to nail your pricing strategy. At boobook, we understand this and are committed to helping you navigate the complexities of pricing. Our approach combines robust consumer-based data analysis topped with insights from behavioural economics to create pricing strategies that align with your customers' decision-making processes.

Don’t miss our upcoming final article in this series on psychological pricing techniques, delving into cognitive biases and decoy methods with explanatory examples.

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Our Insights Director, Eva Vandenberge recently attended the annual ESOMAR Congress and in this interview, she shares her insights.

This annual event by the global association for market research and insights offers researchers and consultants from all over the world the chance to connect and discover the latest trends and innovations in their industry. More than 1,000 people from 78 countries attended this year’s congress in Athens and boobook’s Insights Director, Eva Vandenberge, was one of them. With over 135 speakers, choosing which sessions to attend was a daunting task, but judging by the insights and reflections she shares with you today, she mastered it gracefully.

It was not the first time you attended the congress. What keeps you coming back?

“Nowhere else do you get such a comprehensive image of the current state of affairs in market research and a glimpse into its future. The presentations from the industry's top minds are inspiring, and the informal conversations with researchers from all over the world are fascinating. While listening to their insights, success stories and challenges I get so many new ideas to help our clients even better with their business questions. The industry has been rapidly evolving since the arrival of AI. It is important to keep track of the developments and discover whether new technologies and tools can help us gain better and more reliable customer insights.”

Before we dive deeper into the AI topic: were there any activities you particularly enjoyed?

“I appreciated that ESOMAR organised the YES Awards: a global competition that allows young research professionals to share their - often refreshing - ideas with the public. From all the pitches submitted, a jury selected ten who got to share their 60-second pitch at the congress. Via live voting, the audience selected three finalists who could give their full presentation. The winning presentations were on cultural bias, regression analysis using AI and data collection via WhatsApp in emerging countries. As a young researcher, it is quite an honour to get the chance to share your findings with such an audience.”

“There were no Belgian candidates this year, unfortunately, but I am also a board member of the Belgian Research Federation CUBE, and at the CUBExEsomar event that will take place on 24 October, several young researchers will share their take on the future of research and insights. Hopefully, this will lead to some interesting pitches by young Belgian research talent next year.”  

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Did you discover ideas that you would like to implement yourself?

“Absolutely. One of the YES award winners talked about cultural response bias, something we also struggle with. Certain cultures have difficulty sharing negative feedback and judge everything so positively that we barely detect differences between groups and brands in our analyses, while in reality, of course, there are. In one of our studies, ran in India, we corrected for this during the data analyses, but we are now inspired to tackle this issue by asking different questions. Questions about behaviour instead of attitudes, for example, or questions with neutral rather than numerical scales, so there is no longer a better or worse option. I had a couple of interesting discussions about the topic and will certainly put the new insights to the test.”

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AI was undoubtedly an important topic in Athens. Is it already reshaping the industry?

“AI was a hot topic indeed. Many AI developments and solutions were showcased. And several speakers discussed the potential, but also possible pitfalls of synthetic data, meaning data that has been artificially created as opposed to collected from humans. This could be used in analysis in the same way human data is used. Filling in missing data is nothing new; statisticians have been maximising samples via imputations for a long time. It might be as simple as filling in the occasional empty response with ‘don't know’ or mean scores based on the rest of the sample. Other times more complex models are used to predict those missing values, based on respondents' other answers, and what the rest of the sample says. Using AI, we can now do much more than fill in the occasional missing value.”

What is already possible with synthetic data today?

“As described, synthetic data might be used to complete missing answers, but you can also generate additional cases. If, for example, your study lacks young men from a specific region, you can generate more of them to boost your sample. You could even generate synthetic respondents; virtual participants that provide answers to a survey just like human participants would, and whose answers you can analyse as you normally would. It sounds futuristic, but companies are already experimenting with it, although there is still a lack of trust. Based on what we have seen and tested ourselves, we believe this distrust is justified and we would not recommend making business decisions based on synthetic data at this point.”

It doesn’t look like human respondents will be obsolete any time soon?

“The future will tell. The presented cases show that synthetic respondents can generate reliable results if closed behavioural questions are used. But virtual respondents can’t tell you how they feel, and they can’t answer open-ended questions well. We are curious to see if and how this will evolve.”

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What are some of your own experiences with using AI?

“At boobook, we have done several test on how AI would handle a segmentation study, for instance. When comparing the segments AI came up with the ones we determined, some overlapped but others didn’t. As long as results remain unreliable, real data, captured from real people, remains a must. But, of course, we keep track of the new developments and will continue running tests.”

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What would you like to put to the test in the short term?

“There is quite some enthusiasm about using synthetic cases to map hard-to-reach groups, such as B2B audiences. Synthetic boosters in under-sampled groups would increase the reliability of the study. We have our doubts because it seems unlikely that this data would indeed be reliable. How can it be, when your research pool is small to begin with? But the proof of the pudding is in the eating, so we plan to run a test and find out for ourselves if it could be useful.”

“What was also discussed at the congress, and I very much agree with, is that you should mainly use AI when a human being can’t add value. If using AI to script and translate questionnaires means resources are freed to generate better insights, we can only encourage it. But in terms of data collection and insight generation, we still need actual respondents and human researchers to bring brands closer to their consumers.”

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Which speaker left a lasting impression?

“It is not easy to choose just one, but I will not soon forget the closing keynote by Vivienne Ming, an incredibly intelligent woman who has travelled an unlikely path and achieved so much. She has founded several start-ups and solving seemingly unsolvable problems is her life's goal. She believes AI can be truly transformational and has developed several AI tools, but she is most passionate about maximising our human potential. To do so we need to create open cultures and safe spaces where people dare to experiment. Most of our initial ideas are wrong she claimed, so it is only through failing that we will stumble upon the great ones that can potentially change the world. It left me inspired and proud to be part of the boobook family, where we are all encouraged to share our ideas and get the chance to pursue them.”

“Especially now that there are so many new developments, companies must give their employees room to try new things. If you want to grow you need to accept that you will also fail sometimes. Sharing experiences and ideas is more important than ever, so I would leave you with a warm invitation to connect with us if you want to explore the possibilities of AI together!”

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How can businesses achieve unparalleled growth and maximise profitability in today's competitive landscape? At boobook, we believe the answer lies in our data-powered strategic consulting, anchored firmly on four interconnected pillars: brand, product, pricing, and customer. We guide businesses toward excellence and sustainable growth by understanding and leveraging these fundamental elements.  

Determining the right price for a product can be daunting for many businesses. Often, pricing decisions are based solely on cost or intuition. However, at boobook, we know how important an informed, customer-first pricing strategy is to achieving business success. That's why we created the "Pricing 360°" series to guide you through the complexity of pricing strategy, one aspect at a time.

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In our previous article, we discussed the connection between brand and pricing. Today, we'll continue the "Pricing 360°" series with a second business pillar: the Product.  

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In this article, we will explore the relationship between pricing strategy and product features. We'll delve into the importance of understanding which product features are most valued by customers when setting your price. Adopting a data-driven approach allows you to develop optimal product configurations and corresponding pricing strategies that resonate with your target audience.

The influence of product features on pricing decisions

Setting the right price involves considering various factors, including external influences like macroeconomics, market demand, brand perception, competition, etc., as well as internal pressures such as production costs, company strategy, or corporate finances. While we will cover some of these factors in upcoming articles, for now it's absolutely crucial to acknowledge the pivotal role played by the range and the level of the offered product features in pricing decisions.  

Product characteristics such as design, durability, specific functionalities, product bundling possibility or other technical specs are vital elements to have evaluated by your prospects when determining the value customers assign to a specific product and what they are willing to pay for it, based on its specific product features combination.

It’s essential to avoid letting internal pressures dictate the product features or the price at which they are to be sold and instead focus on understanding and meeting your customers' real preferences, expectations, and willingness to pay. After all, what makes a product excellent is defined by the customer, not the product manager. This is the essence of a Value Based Pricing strategy, in which we strongly believe.

Get your pricing basics right first

Successfully defining an acceptable broad price range for your product(s) involves multiple factors, categorised as internal and external:  

Internal factors:  

1. Production costs: Understanding the costs involved in producing the product is essential for defining an appropriate price range that ensures profitability.  

2. Financial resources: A company's financial capabilities indirectly determine its pricing strategy. E.g. the level of promotional efforts at launch, the level of investments in product development that come with an impact on its final price, etc.

3. Positioning strategy: How the product is currently positioned in the market and its perceived value influence pricing decisions. A premium positioning strategy may warrant higher prices, while a value-for-money oriented positioning may require more competitive pricing.  

4. Pricing strategy: The chosen pricing strategy directly affects the product's final price.  
   Different methods, such as cost-based or value-based pricing, have distinct implications for profitability and market positioning.  

External factors affecting pricing decisions include e.g. the state of the (national) economy, market demand, level of competition or even seasonal influences.  

How to measure product needs  

Even though it’s important to have these internal and external aspects in mind, the key question you have to ask is what product or service features contribute the most to its value, and therefore, drive willingness to pay?  
Is it its design? Or maybe the width of the colour range you can choose from? Or could it be one of the more technical (and often underestimated) specs that really drives interest and willingness to pay? It is essential to be open to learning and understanding. These important nuances of what the customer thinks are crucial to a product and bring value and what are superfluous extras that they aren’t willing to pay more for.  
To further enhance your understanding of product-related customer insights, at boobook we use advanced methodologies such as conjoint analysis, Max Diff, or key driver analysis.  

Conjoint analysis is particularly useful for understanding the value of each individual product feature.  
In conjoint analysis, customers are shown all possible variations of product features/specs (levels) and are asked to choose which variation of features and specs-level they would be most likely to purchase, given a specific competitive and pricing situation.  
The different product variations, including competition (!), are presented on a simulated shelf to create a realistic shopping experience and the exercise must be done several times to ensure all possible competitive and pricing situations are tested. This is the only way to make robust, statistically significant, data-based insights afterwards.

Let’s take a look at the example with smartphone comparison. A product is characterised by its attributes and levels, which depend on the variations to be tested. A minimum of two attributes are required (for instance, price and brand) to create a design grid.

At boobook, we employ a scenario simulator for conducting key conjoint analysis. The simulator allows us to analyse the following:

• Price sensitivity of different product variations in a competitive market

• Estimates of volume, revenue and profit

• Evaluation of the value of various product features

• Potential cannibalisation effects

• Identification of the ideal product range

By analysing the data obtained, we can accurately measure the value of each product characteristic and identify which product variations customers are willing to pay more for. Combining these data-driven insights with our industry expertise, we enable businesses to make informed, strategic decisions that drive growth and profitability.

In conclusion

Conjoint method is a powerful tool that can address various business enquiries beyond pricing alone. Additionally, it can offer multiple simulation options.

However, it requires substantial set-up time, larger samples and is generally more costly compared to simpler methods. Conjoint analysis is best suited for examining the price sensitivity of multiple products, analysing the combined impact of price and product composition, and optimising price and promotional strategies.  

Curious to learn more? Check out our case study with Center Parcs to discover how we helped them identify which product features customers are willing to pay more for.  

Feel free to contact our team if you have any questions or want to learn more about data-driven strategic pricing. Stay tuned for our next article in the series: "Pricing 360°: Customer understanding as key ingredient of meaningful commercial strategies".

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