Finding the right pricing strategy is a tough challenge. Mispricing can mean lost revenue, a weakened brand, and missed opportunities.
The good news is that pricing doesn't have to rely on intuition or guesswork. The right tools empower businesses to make data-driven decisions about their products.
Many businesses use a tool called a pricing simulator. It's the primary deliverable of a technique called conjoint analysis.
These simulators can be used across various industries, in both B2C and B2B, and they let companies test out different pricing scenarios and see the impact without having to change real-world prices.
Let's explore how pricing simulators work and why we believe they are crucial to smarter pricing decisions.
What is a pricing simulator?
A pricing simulator predicts how customers will react when a product or service changes its price. It's part of a broader market research technique called conjoint analysis which, in itself, is more than just asking customers what they would like to pay.
At Numerious, we believe asking customers directly about pricing preferences can lead to unreliable results. What people say they'll pay doesn't always match their actual buying behavior. This mismatch can lead to costly mistakes in product development and marketing.
A market simulator helps you figure out what happens if you raise prices by 10%. And because we’re simulating the competitive market, it can also determine the price at which customers start to prefer your product over a competitor's - or vise versa.
Market simulators can answer strategic questions about your pricing like:
Who will choose our product or service?
At what price will people switch to a competitor?
And typically, conjoint experiments don’t just include brand and price - but many other product features that you can add or subtract from your offering.
This allows you to answer additional questions like:
Can we modify our product to reduce cost while maintaining market share?
If we can't deliver on a specific feature, how does that affect our preference share?
Will delivering a particular feature gain enough incremental preference to justify the cost?
The simulator tool also gives you the flexibility to test out additional product skus for you or your competitor. Allowing you to answer questions like:
Should we launch a high-end product, a budget model, or both?
Would a new product cannibalize current sales?
If a competitor launches a budget version, will that steal share from our product?
As you can see, the pricing simulator provides a wealth of information, helping you make informed decisions with less risk of costly mistakes.
How a pricing simulator works
Pricing simulators rely on the model that is built on the data from a conjoint analysis survey. These surveys show people different product options with various features and prices and ask which they’d be most likely to buy.
In a survey about smartphones, respondents might see several options. One could be a Samsung Galaxy phone with 12GB storage for $499. Another might be a Google Pixel phone with 16GB storage for $1,199. A third option could be an Apple phone with only 4GB of storage for $799. Respondents choose which option they'd most likely buy, or they can opt out of the purchase if none of the options are for them.
After data collection, the research can build a model that reveals how much value people place on different brands and features, including price. The pricing simulator then predicts customer behavior based on this data.
The simulator shows how many people would choose a product at different price points. It also predicts how price changes might affect market share.
Benefits of using a pricing simulator
Pricing simulators offer many benefits to businesses. They allow price testing without real-world consequences. This approach reduces the risk of costly pricing mistakes.
These tools help businesses understand customer preferences. They show how much customers value different product features, and how sensitive (or insensitive) they are to price changes. This information helps find the right balance between profit and customer satisfaction.
Simulators predict changes in market share. When a business adjusts prices, the simulator estimates how it might affect sales and which products consumers will turn to if they do. They also help with competitive planning. Businesses can test how competitor price changes might impact their own sales.
A real-world example
Let's look at a simple example of how a pricing simulator might work. Imagine a company launching a new smartphone. Their current phone costs $699, and the pricing simulator forecasts that 18% of consumers would buy it at that price.
The company plans to add a new sku but isn't sure about the price. They build out the new sku in the pricing simulator and test out an $899 and $1,199 price point.
With the new sku on the market, the original model's market share would drop from 18% to 14%. However, the new model at $899 would capture 19% of the market, increasing the total share for the brand to 33%.
If the new model is priced at $1,199, not surprisingly, fewer people are interested in the higher price point. But the total share for the brand still increases to 29% (up from 18% with only one SKU).
Now the brand has an important decision to make - do they want to be in more pockets (in which case they should price it at $899) OR do they want to make more profit (in which case they should price it at $1,199.
The information from the simulator allows comparison of different pricing strategies. A lower price might bring in more customers but could affect sales of the existing model. The higher price might attract fewer new customers but could be more profitable overall.
You can imagine how valuable a war-gaming exercise could be among product planners and product managers - building out different product skus at different price points and seeing which ones drive the most interest and/or profit. And the number of possibilities is endless!
Limitations of pricing simulators
Pricing simulators are powerful tools, but they're not perfect. They make assumptions that might not always match reality. For example, simulators assume all products are equally available to customers. They also assume marketing is equivalent and all sales teams perform equally well. And, they don't account for out-of-stock situations or if some brands have been on the market longer than others.
These factors can affect real-world sales in ways the pricing simulator can't predict. Keep these limitations in mind when using a simulator. The best way to use the results is to guide decisions, not make them automatically.
Not to mention, the levels of price you test in the conjoint experiment will impact how you’re able to use the results. A wide range of prices is helpful but too wide can muddy the results.
Pricing simulators in the bigger picture
Pricing simulators are one tool in the market research toolbox, but perhaps the most impactful. They can provide a better understanding of how to optimize pricing or a feature set at a level more sophisticated than any other marketing research pricing technique.
Better yet, you can level up the impact when combined with other techniques and data sources. Using a pricing simulator alongside customer interviews, sales data analysis, and competitive research can provide extremely valuable context.
The goal of using a pricing simulator isn't finding the highest price customers will pay. The real goal is finding the right price that balances profitability, customer satisfaction, and market share goals.
Pricing simulators give businesses a significant advantage. These tools help navigate pricing decisions with more confidence and insight when used wisely.
Take the next step
Want to learn more about pricing? Numerious can help you figure out what your customers really want using advanced analytics. Contact us to get started.