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Alrighty, I'm gonna get started. The title of my talk is 'What's in a Price? How to Price Your Products and Services.' My name is Michael Herold, and I'm the lead application engineer at a company called Flywheel.
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We help creatives do their best work primarily by providing a world-class WordPress hosting experience. We make it a delight for designers and creatives to host their WordPress websites.
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We are hiring, like everybody else! We are looking for product managers, scrum masters, developers of all kinds. If you're looking for a job, come talk to me or any of my friends here in their Flywheel shirts.
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If you have any questions, please tweet me at @M_Herald during the talk. If you tweet me, I will try to reply to your comments.
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Alright, as an outline for this talk, I’m first going to tell you a story. After that, I'm going to give you a quick crash course in economics. I know that economics isn't something most programmers have a lot of experience with, so I think a quick crash course will help you get your feet under you when thinking about pricing.
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Then, we're going to talk about a model that is really going to help you with your pricing moving forward. It's a very simple model to use, and I’ll walk you through how to use it, when to use it, and why. Finally, I’m going to talk about how the partnerships we can form through pricing and the mindset we gain from this work can help you become better at what you do. But first, let me share my story.
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We were launching a new product, and I heard that we were planning to price it at $99 a month. I innocently asked how we decided on that price. Can you guess what the answer was? We're a very intentional company, so I expected there to be a great answer, but in this case, there was actually not really an answer at all.
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What's missing from this picture? What's missing from the lack of an answer to why we are pricing our product at this level? We are an experienced company that has several products we have intentionally priced in the past, and yet we still made this mistake.
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What if you have a side gig? What if you're a solopreneur? Pricing your first product can be scary. It's daunting to put your work out there and ask for money for it. Heck, it's scary to put your work out there for free; just ask any open-source maintainer.
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Having money enter the equation makes it even scarier. Pricing your first product is also hard, especially if you’ve never thought about it deeply. How do you do it? What if you do it wrong? What if you overprice or underprice?
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Pricing your first product is full of angst, fear, and uncertainty. You might worry about embarrassing yourself or jeopardizing your job and your reputation. What if you fail? It doesn't have to be like this.
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How can we make it easier? How can we go from feeling overwhelmed to a state of comfort with what we’re doing?
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So that’s my story. Now, I'm going to give you a quick crash course in economics.
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Economics is an interesting discipline that can be summed up succinctly. So, what's in a price? When you hear the word 'price,' what do you think of? A price is just a mutually agreed-upon construct for bartering.
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We happen to use money now, but in the past, transactions were done entirely through bartering. Now that we have money to facilitate transactions, we don't have to agree on the value of a cow versus a chicken; instead, we use dollars or other currencies to determine relative prices.
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In economics, everything starts with two axes. The vertical axis is price, while the horizontal axis is quantity. The price axis is based on the price per unit of what you're selling, and the quantity represents the number of things being sold.
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When we graph supply, supply curves always slope up and to the right. They start at a point above the zero axis, where you must cover your costs unless you choose a peculiar pricing strategy that involves taking a loss on a product.
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Supply curves begin above the zero point because they reflect the resources and efforts needed to produce an item. This upward slope illustrates how production capacity is generally a logarithmic curve due to technological constraints.
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Demand, on the consumer side, exhibits a downward slope. When prices drop, we tend to want more of the product. Conversely, if prices are high, such as with cars, we prefer to buy fewer of them.
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The intersection of these two curves is known as equilibrium. The equilibrium price reflects the collective knowledge of consumers and producers in the market.
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At this point, producers don’t want to create more than they can sell, which wastes resources, and consumers are only willing to purchase the amount affordable to them.
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We can derive two significant insights from this graph. The red shaded area indicates consumer surplus, which represents the difference between what consumers are willing to pay and what they actually pay.
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Consumers enjoy that feeling of buying something at a bargain price—an amount below what they were prepared to spend.
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Now on the flip side, producer surplus is approximately equal to profit. This includes factors like opportunity cost, where the resources spent on one product preclude their use for another, but we can think of it primarily as profit.
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So what does this graph mean for us? Supply is largely controlled by us; the people who create the products. For instance, if you have written an e-book, your supply curve will be relatively flat since your only costs are connected to hosting.
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However, larger services like GitHub have many hosting costs and backend processes, making their supply curve more complex. Nevertheless, the supply is primarily managed by the producers.
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Demand is driven by consumers, who are aware of what they want and will make choices based on what makes them happiest. To set the right price, we must first understand the demand for our products.
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Without grasping demand, pricing is akin to throwing darts at a board—you have no real sense of where you’re aiming, which is the root cause of the anxiety experienced during those initial pricing decisions.
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For developers, it's time for an abstraction. We’ve covered economics, and now I’m going to introduce the model that will dominate the rest of the talk.
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Economics applies across many disciplines. Many people think of economics solely in terms of finance, especially relating to the stock market.
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Economics also has applications in accounting. Accountants perform more tasks than merely counting profits and losses—they often engage in forecasting and even conduct post-mortems on failing businesses.
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There is also an entire field called political economy that studies interactions between markets, law, customs, and government.
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Additionally, economics can inform fields such as neuroscience, particularly through a sub-discipline known as neuroeconomics, which studies models explaining phenomena in the human brain.
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However, the particular field we are interested in is market research. Market research employs economic principles to build models that help us better understand customers.
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There are many methods available; the one I've chosen to focus on is called the Van Westendorp Price Sensitivity Meter. This model was first presented in a paper in 1976 for the European Society of Opinion and Market Research and is still widely used today.
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The Price Sensitivity Meter is user-friendly, requiring no special skills or preparation. When you apply it, the results are easy to understand and interpret.
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It's also lightweight, allowing for quick implementation in front of an audience without needing extensive upfront preparation or follow-up analysis.
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This method is based on surveys, something most of us have likely encountered in our lives for various purposes, including pricing.
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What does this process look like? Let's discuss the steps necessary to implement the Van Westendorp model.
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First, you need to establish your pricing scale. You might wonder why this scale is necessary if you’re learning how to price using this model. But it’s essential.
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Presumably, you've conducted some market research to determine whether your idea has potential. The pricing scale should reflect that research.
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You don't have to nail down the exact price, but you should map out a range. Aim for about 25 to 45 discrete steps within that scale, covering both improbably low and unfeasibly high values.
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For instance, consider pricing a granola bar. A minimum step might be 50 cents, which is generally unreasonably low. Conversely, it’s hard to imagine someone paying $10 for a granola bar.
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Your pricing scale should feature both ends: the zero to 50 cents bucket and the $10 bucket. The range in between will provide a comprehensive perspective.
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After establishing the pricing scale, you need to survey your audience. Start with a clear and detailed explanation of your product or service.
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Better yet, begin with a demonstration. If you have a working product, show it off. If you haven't built it yet, use mock-ups.
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Demonstrations effectively communicate what you’re selling, whereas explanations alone can confuse potential customers.
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In your survey, include questions that start with asking respondents at what price they think the product becomes 'so inexpensive that they might doubt its quality.'
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For example, would you buy a new car priced at $100? Many might hesitate because they wouldn’t trust its safety.
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Next, ask at what price they consider the product an excellent deal. This is crucial for determining the range where consumers feel they are getting value for their money.
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The third question gauges at what price the product starts becoming expensive, but they might still consider purchasing.
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Finally, ask at what point the cost becomes too high to even consider. For example, some might find brands like Mercedes too far out of their budget.
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These four questions yield four pieces of critical information from each respondent regarding pricing perceptions.
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You want to ask these questions in both increasing and decreasing order, which helps mitigate the psychological effect of anchoring.
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For instance, if you ask about $1 and then ask for a higher amount, respondents may feel anchored to that lower number.
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By evaluating answers in both directions, you can better balance the biases affecting your respondents' answers.
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If you encounter impossible answers, the original paper suggests simply correcting them. For example, if someone says $30 is too expensive but might consider $50, just correct that inconsistency.
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After gathering your surveys and acquiring your data set, it’s time for some statistics, so brace yourself.
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Statistics can be intimidating for some people, so let’s break down the one key concept you'll need: cumulative distribution functions.
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This function assesses the probability that a random variable is less than or equal to a specified value.
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In this context, a 'random variable' refers to observations gathered from your survey responses, like preferences on pricing.
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For example, one person might consider $1.22 cheap, another might say $9.99, and someone else might go with $4.88; these responses comprise your random variable.
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X represents the maximum values from each step in your pricing scale—those values you previously set.
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In the granola bar example, X would comprise values like 50 cents, one dollar, and so on up to $10.
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Next, we apply a function to each step in the scale, referred to as the cumulative distribution function or CDF.
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To compute CDF, you must count all observations that are equal to or less than the value you’re analyzing.
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Then, you divide that count by the total number of observations to get the probability.
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This process can be executed in a few lines of Ruby code. Yes, we just tackled some statistics.
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Next, we want to graph the CDFs — humans are naturally visual, so seeing data helps in understanding it.
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Let's graph the inexpensive and expensive curves and look for their intersection.
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The point where the orange 'cheap' curve and the blue 'expensive' curve intersect indicates the indifference price.
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This indifference price might correspond to the market average—or the price signals from a market leader.
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In our granola bar scenario, a well-known brand could help set that market price expectation.
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Next, you must recognize psychological thresholds. These large jumps in price reflect points where consumer perceptions change significantly.
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For instance, consumers are sensitive to price changes around thresholds; retailers frequently price items at $0.99 to avoid crossing psychological boundaries.
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We've seen similar behaviors on the expensive curve, noting steep jumps where people suddenly reconsider whether they will spend their money.
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Now we want to graph the 'too expensive' and 'too cheap' curves. This intersection represents the optimal pricing point.
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The optimal pricing point shows where there is minimal resistance to change. Shifts from this point won’t significantly change consumer perceptions on value.
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Collectively, these intersections provide insights into the acceptable price range for consumers, which gives a striking visual understanding of market dynamics.
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Finally, we want to graph all four curves together to see which pricing ranges fall within acceptable limits for consumers.
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The more you differentiate between the optimal price and the indifference price, the more sensitive consumers may be regarding price changes.
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Now that we have clarity on acceptable pricing, it’s your turn to decide based on your specific values and market objectives.
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Our next question to consider: are prices inherently adversarial? Oftentimes, companies seem focused on extracting maximum value from every customer.
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However, pricing doesn’t necessarily have to feel this way. You might find better results by creating consumer surplus.
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Happier customers are more likely to spread word-of-mouth suggestions and create positive interactions with your business.
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Moreover, happy customers often become your greatest advocates. In fact, some businesses thrive on word-of-mouth referrals rather than advertising.
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They gain this goodwill from pricing that creates a consumer surplus—making customers feel skilled about their shopping choices.
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Back to my earlier points, we did encounter some challenges while applying this model.
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Firstly, we forgot to explicitly define the pricing scale before surveying participants. This upfront work is essential to prevent extraneous values.
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Anticipating the maximum amount you want to charge helps in filtering noise—and prevents results such as one person mentioning $10,000 per month.
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If possible, segment your participants into logical groups. Different customers have varying pricing sensitivities based on their context.
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For instance, individual designers, design agencies, and enterprise customers each have distinct price perceptions, and combining them can muddy the results.
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Make sure to verify further within each segment and ask in both increasing and decreasing orders to eliminate anchoring bias.
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It’s vital to be clear with your descriptions. I cannot stress enough that conducting surveys with actual mock-ups gives you better data than mere explanations.
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Words can be ambiguous, leading to misguided interpretations that distort your findings.
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Finally, let’s reflect on the lessons learned from studying the model and applying it.
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This is just one model; there are others. You could use price sensitivity analyses to measure your brand power or evaluate discount effectiveness.
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You may also want to consider how product bundling can enhance value for customers.
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Learning from other disciplines is important for all developers. We must liberate our ideas and learn from each other for growth.
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How amazing would it be to partner with someone experienced in pricing and help them become a developer while fostering collaborative friendships?
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We developers excel at abstraction. Computer science is the study of abstraction, but it's easy to lose sight of the human elements within our systems.
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Instead of thinking of customers as mere users, let's understand their motivations, which allows for intentional design that serves them best.
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By doing so, we help our customers feel awesome, which is something everyone strives for—whether it’s in shopping or their day-to-day activities.
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Lastly, consider your customers as partners rather than just clients. Partners are vital advocates for your business.
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As referenced in the last talk, many businesses thrive on referrals from satisfied customers; thinking of customers as partners fosters that loyalty.
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I hope this talk has given you valuable insights to think about pricing strategically. My name is Michael Herold, and I am the lead application engineer at Flywheel.
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If you want to help creatives do their best work, please come talk to me or anyone in a Flywheel shirt. Thank you for your time.