The right pricing can make or break a business. Copying your competitors might mean starting a price war, but making a guess could leave you balking at abysmal sales numbers.
Successful price optimization is a matter of finding the sweet spot between valuable and lucrative — a balance that can have a major impact on your sales, customer satisfaction, profits, and achievable growth goals.
Our guide is here to help. Each section breaks down basic price optimization concepts so you can create and apply a solid pricing strategy. Both new and established businesses can benefit from these tips, so choose a place to start and bookmark this guide for reference.
To find the optimal price, you also have to understand how consumers will react to price changes. That means stepping back to economics 101 for a refresh on a basic pricing concept.
Price Elasticity of Demand
Price elasticity measures how a change in consumption of a commodity relates to a change in price. Formulaically, it’s expressed as:
Price Elasticity of Demand = % Change in Quantity Demanded / % Change in Price
That equation is used to understand how a price change is reflected in a product or service’s supply and demand — if demand stays the same when its price changes, the commodity is inelastic.
If demand decreases when the price fluctuates, it’s considered elastic. For example, if the price of gas rises, car owners will typically still fill up their tanks — making gas an inelastic commodity.
Simply put, an inelastic product or service is less sensitive to price changes, while an elastic product or service can see considerable changes in demand when prices shift. This information can be key to successful price optimization — it helps to know how customers will react to price increases or decreases.
Now that we’ve covered the basics, let’s walk through the steps to find your optimal price point.
How to Optimize Pricing
Figuring out the right price for a product or service starts with understanding your customers. You need to go deep to learn as much as possible. What features do they need? What are their values? And why did they choose you over your competitors?
You also need to understand your market and industry trends. For instance, pricing for B2B is much different from B2C. And retail plays by different pricing rules than travel or food.
Feeling overwhelmed by the amount of data needed? Just take your time working through each of these steps.
1. Dig into data.
Price optimization isn’t a guessing game — you need hard data to do it right. This includes both qualitative and quantitative data to figure out how much customers will pay for your product or service.
Quantitative data includes information on demographics, psychographics, inventory, supply and demand, historical market specifics, sales metrics, churn rate, product features, and price sensitivity.
Qualitative data is also crucial. Customer surveys are a good starting point to collect information, but it’s important to speak to existing and potential customers as well. Ask questions to find out your competitive advantage, perceived value, sales tactics, loyalty programs, promotions, discounts, or any thoughts on current pricing.
Most companies looking to optimize pricing have profit-focused goals — but more profit is just one of many objectives that can be achieved by finding the perfect price. Improving customer loyalty, upselling, or attracting new customers are all possible goals.
Define your goals and constraints to get clear on your objective. Maybe, you want to increase the perceived value of your product. Maybe, you can’t drop below a set price point. Or maybe, you want to hit a certain sales quota.
Whatever the aim, write it down. You need to know where you’re going in order to get there.
3. Know your value metric.
The way you charge customers needs to align with the value people get from your product or service. Seems simple, right? It is — provided you have the right value metric. Your value metric is what and how you charge for your product or service.
If you sell software, you might charge for specific features, customer contacts, or hours of hosting. If you sell a physical product, you likely charge per unit.
Figuring out the right value metric is important for price optimization because it showcases how customers value your product and what you can charge for the value you offer. Start by learning what customers value in your product or service and experiment with ways to charge for that value. This article by Price Intelligently breaks down the steps to find your value metric in detail.
4. Create pricing tiers.
Once you have your customer data and value metric in hand, it’s time to develop pricing tiers for your product or service. Each tier should correspond to a particular customer segment that you found in your research and should align with your value metric.
For example, HubSpot charges per marketing contact and offers additional features for each tier. They offer different pricing for marketing, sales and CRM, and customer service tools, with recommended bundles for various customer segments.
Adobe offers different pricing tiers for each app — with options to license a single app, multiple apps, or all apps in their product offering. They even segment their users into four categories (individuals, business, students and teachers, and schools and universities) to cater pricing and bundles to each group.
If pricing tiers don’t make sense for your product or service, you might be able to offer bundles or a sales section to reach different customer segments. A good example of this is Patagonia — customers can buy full-price items or shop less expensive used gear through the “Worn Wear” collection.
Price optimization isn’t something you figure out once and forget about for the next decade. It’s constantly changing and continually optimized. As you update features, branch out into new markets, and gain customers, it’s smart to revisit your pricing every one to two years to see if it’s still at the optimal point.
5. Continuously monitor pricing.
Set up a way to collect data to make sure the value you’re offering aligns with customers’ needs and pricing expectations. If the data shows it’s time to change, don’t be afraid to reevaluate your pricing strategy. Just don’t change prices too quickly or too often because fluctuations can frustrate existing customers or turn off potential customers.
Price Optimization Examples
While price optimization may seem complex, we are familiar with it in our everyday lives. Let’s take a look at some real-world examples
Airlines are pros at price optimization. They use price elasticity to keep up with the fares of competing airlines. How? By aggregating the pricing of flights by their competitors in real time. This is why fares tend to increase or decline in the same pattern. This is an industry practice even low-cost airlines participate in.
2. Real Estate
As tech continues to advance, you can find it in all sectors, including real estate. Algorithms can be combined with housing price data to help landlords and property management companies decide what to charge for a particular property. This can sometimes backfire — a Class Action suit was filed against property management software company Real Page, alleging the company sold software that pushed rentals too far above competitive levels, resulting in price fixing.
3. Event Tickets
Anyone who has tried to purchase concert tickets within the past few years knows the pain of logging onto the event website, looking for seats, and then getting a major sticker shock when the prices are displayed. Ticketers, like other industries, use algorithms for what’s called dynamic pricing. This means the higher the demand, the higher the price. You may experience a similar situation when trying to use a ride-share service at peak times and encounter “surge pricing.”
Next, we’ll dig into specific price optimization models to help you choose the right one for your brand’s needs.
Price Optimization Models
If you dig into pricing research, you find two schools of thought when it comes to price optimization models. One deals with finding the right pricing strategy for your business, and the other is catered to math whizzes who get their kicks from crunching numbers. Here’s a breakdown of each.
Pricing Strategy Models
Before getting into the various pricing strategies, it’s important to distinguish the difference between a pricing strategy and price optimization.
A pricing strategy is a method used to set the best price for a product or service. Each strategy has its pros, cons, and best-use cases — depending on the industry or business. If you’re ready to compare how one strategy compares to another, try the Sales Pricing Strategy Calculator to plan and calculate your revenue.
Once you choose a strategy, then comes the optimization part. Setting an optimal price is a part of any pricing strategy and ensures you’re pricing products or services in a way that meets your goals. Here are a handful of common pricing strategy models.
Take time to analyze your current pricing strategy — it might make sense to switch to a better model! Ideally, you can do this while you’re updating a product, launching a new one, changing your marketing strategy, or setting new pricing goals.
Pricing Optimization Models
The second type of optimization model is for everyone who raced to math class. As someone who chose chores over calculus homework, this explanation relies on people way smarter than me.
Optimization models are math-based programs that use data on demand, price level, costs, inventory, customer behavior, and more to recommend prices that maximize profits.
These solutions have been evolving for decades, with recent advancements in artificial intelligence and machine learning technology changing how to determine the best price. The tools can help you set the initial price, the discount price, or the promotional price of your product or service without asking analysts to labor over a spreadsheet.
Here are the steps to effectively use a model:
Select a modeling tool — considering the features, data analysis, and outcomes. Certain solutions can tell you which product features people prefer and help create buyer personas for customer segmentation.
Round up data — like past pricing and promotions, competitors’ prices, inventory, seasonal and geographical considerations, fixed and variable costs, and customer demographics.
Confirm your pricing goals, and set rules to guide the modeling process to align with those goals.
Input the data, run the model, and revise as needed.
Gather the results and go over them with your pricing team. Make sure every agrees on the next steps to implement the pricing strategy.
Track results and collect updated data to continuously run the model and optimize pricing. Tools should be able to monitor your pricing versus competitors to ensure you stay competitive while also achieving your goals.
Price Optimization Software
Today’s pricing software makes it simpler to plug-in data and determine if your current prices hit the mark. Different companies need different software, especially when it comes to B2B versus B2C — as each type has unique considerations.
B2B companies usually sell a lower volume of products or services, making it more difficult to source data on customer behaviors, price sensitivity, and customer segments. When optimizing prices for a B2B business, it’s best to look for a tool with elasticity-based pricing.
This allows you to select an optimal price range, rather than a single price point, for more sophisticated quotes. You can also combine price optimization tools with your CPQ and CRM tools for a seamless sales process.
B2C companies often struggle with gauging customers’ reactions to price fluctuations and determining the equilibrium market price (where quantity supplied meets quantity demanded) of a product or service.
That’s why B2C companies benefit from a price optimization tool that helps figure out how sensitive customers are to price. Look for features that gather historical customer data, segment customers, create behavior profiles, and consider price sensitivity.
More companies are starting to take advantage of price optimization software, with Gartner estimating the market grew by 9% in 2020. With those considerations in mind, here are several price optimization software options that may be a good fit for your business. Just remember to consider integrations, so the software works with your current systems.
Pricefx is a cloud-based dynamic pricing solution that uses artificial intelligence to manage prices in real-time. With clients in spaces from automotive to chemicals to manufacturing, Pricefx has extensive B2B and B2C experience. The software comes in three different packages (plan, price, profit) for you to choose from based on your pricing goals.
Prisync is a competitor price tracking and monitoring software with solutions for price checking, MAP monitoring, price management, dynamic pricing, price matching, and price scraping. It offers three pricing tiers ($59, $129, and $229) and integrates with Shopify and Magneto — as well as through an API.
Price2Spy is a price monitoring tool offering price comparison, price change alerts, reporting, analytics, and spidering. With three pricing tiers ($49.95, $249.95, and an enterprise option) and integrations with Shopify, Magneto, Google Shopping, and more, it works well for companies looking to keep an eye on competitors’ pricing.
A dynamic pricing solution primarily for retail companies, Omnia allows users to set pricing rules and takes price elasticity into account for automatically optimal pricing. Two products, one for monitoring competitor pricing and another for dynamic pricing, lets you choose which features are best for your business.
Competera is a primarily B2C artificial intelligence-powered pricing platform that helps retailers enhance strategy and increase revenue. It has products for gathering competitive data, pricing automation, and price optimization. The solutions are organized by industry, and you can request pricing based on the product that’s best for your business.
Specifically for B2B business, Vendavo aims to optimize commercial, pricing, and sales outcomes through artificial intelligence tools. It has multiple products for pricing, including a dynamic pricing tool, deal-specific pricing, a profit analyzer, and a margin analyzer. A contact form is required to find out a pricing for each solution.
Zilliant addresses B2B pricing and sales issues for distribution, manufacturing, and services industries. It uses artificial intelligence to align prices with the market and offers a handful of solutions for specific pricing needs.
NetRivals is a competitive product and pricing analysis tool for retailers and brands. It caters to a number of industries, including fashion, music, toys, beauty, and sports.
With products for gauging competitor pricing on Amazon and Google Shopping — along with online product analysis and value analysis from ratings and reviews — it’s a robust solution for e-commerce companies.
With PriceShape, users can perform detailed competitive analysis, design their own pricing strategies, establish automatic repricing to remain competitive, and use smart data to optimize Google Shopping features.
This tool complements businesses across industries.
Why Price Optimization Fails
Price optimization isn’t simple. It requires research to understand both your customers and your business. However, if not following proper guidelines your price optimization efforts can fail. Here are some of the most common reasons your strategy may fall short:
1. You’re not using accurate data.
Your optimization strategy is only as good as the data it’s based on. That’s why it’s imperative that the data you have is accurate. Opting for best guesses or subjective data can really skew your results. Using price optimization software will help you avoid the pitfalls of using inaccurate data. In fact, Gartner found that using price optimization software had a payback on investment in less than six months.
2. You’re offering too many discounts.
Discounts are certainly a good strategy for gaining new customers but they can also backfire if not balanced. Offering heavy discounts can throw a wrench in your price optimization strategy by skewing what the price point for your target audience should be.
3. Your pricing isn’t value-based.
Value-based pricing sets prices based on the customer’s perceived value of your product or service. Essentially, companies base their prices on what the customer thinks their product is worth. If your price isn’t aligned with what customers think your product is worth, it can create obstacles in your optimization process.
While this isn’t an exact science, companies can gain insight into what their customers think about pricing through feedback surveys. This feedback can then be used to set prices going forward.
4. Your process is too complex.
Just as important as having accurate data, it’s also key to not make your criteria and processes too complex. Overcomplicating your process can drag down your progress and even lead to conflicting insights. Your brand’s price optimization solution should be understandable to your stakeholders and team.
While it’s not always straightforward, figuring out the best price for your product or service is far from impossible — especially when you have the right tools and a strong understanding of basic pricing concepts.
Perfect your price optimization.
Collecting all of the data and crunching numbers to find the optimal price for your product or service can seem like an impossible task. But if you start by collecting historical data and setting pricing goals, you can get the hard work out of the way. From there, it’s about finding the right tool to help analyze the data and monitor pricing trends, competitors, and goals.
As you work through this process, remember that price optimization requires iteration. You can’t set it and forget it. But by making a plan and setting realistic goals, you can start evaluating if a price is working for you — or if it needs to change. In time, you can find the price that will meet your goals and make your customers happy to do business with you.
Editor’s note: This article was originally published in April 2021 and has been updated for comprehensiveness.