Price optimization is using data from customers and the market to understand how you should most effectively be pricing your product. The optimal price point is the price where companies can best meet their objectives, whether that means increased profit margins, customer growth, or a blend.
Information used in price optimization includes things like:
- Customer survey data
- Demographic and psychographic data
- Historic sales data
- Operating costs
- Machine learning outputs
- Subscription lifetime value and churn data (for subscription business models)
Pricing optimization is a similar process to dynamic pricing strategies used in hospitality, travel, ecommerce, and other industries, although dynamic pricing tends to change much more rapidly as companies tweak pricing to match real-time demand.
Finding the right price for your product—a price that maximizes value for customers and profit for you—starts with gaining a deep understanding of your customers. You need to understand who your best customers are, what features they like, and what features they need. Once you understand that, you can align your pricing with what they value, tracking the results of the price changes you make and improving over time.
(i) Get to know your customers
Optimizing your pricing is all about the data—both qualitative and quantitative. Hard data is the only way to find out how much customers are willing to pay for your product, and it’s the key to breaking free from the guessing cycle.
Quantitative data, like transactional data, customer reviews, supply and demand data, churn rate, MRR, and more show you how you’re doing and what needs to be changed. Software like Price Intelligently can help you make sense of those metrics and turn them into pricing insights by slicing and dicing your data based on demographic, psychographic, and customer preferences.
Just as helpful, qualitative data comes from talking to customers. Surveys are great, but they’re no match for picking up the phone and actually talking to customers, asking them about topics such as their price sensitivity and what features or benefits they value most in your product.
(ii) Quantify value
Once you’ve collected all your customer data, it’s time to work out what “value” actually means to your customers. That means working out your value metric. Your value metric is essentially what and how you’re charging for your product—identifying and pricing along your proper value metric is the difference between surviving and thriving.
(iii) Analyze the data
You’ve collected some customer data and worked out what your customers value—now it’s time to look for patterns in the features, benefits, price points, and value metrics that drive or detract from value. You’ll also find out how willing different segments and personas are to pay different prices for your products.
Use your findings to create tiers and proper packages for your product or services. Each tier should be priced along your value metric, and should align with your different buyer personas so that you’re offering the right amount of product or service to each customer segment.
(iv) Adjust pricing and monitor
Even once you’ve set your prices, you’re still not done—the value you provide versus your competitors’ is constantly changing, so you need to be constantly monitoring and adjusting your pricing.
Pricing is an ongoing process. You should use your pricing strategy to eliminate as much doubt as possible. Think back to our dartboard example from earlier—adjusting your pricing helps eliminate sections of the dartboard, focusing in on the right region for your dart to land as you learn more about what works.
You need to continually collect data and analyze the value customers are getting from your product to make sure that what you’re offering still meets your customers’ needs and pricing desires. Make sure you keep a very close eye on your pricing, and see how customers respond. If need be, re-evaluate and change things up—but don’t be too quick to switch, since you might alienate potential or existing customers.
Need to optimize for
The goal of pricing optimization is to find that perfect balance of profit, value, and desire. Since you can’t control which products and features customers want, and adding valuable product features takes time and effort, most companies start finding that balance by setting two things: the starting price of their product or services, and any discounts or promotions they might offer.
(i) Starting prices
Your starting price, or base price, is important since it lets customers know whether your product or service is worth their time and investment. Starting prices should be optimized to match the baseline demand for your product before any discounts or promotions are applied. Optimizing the starting price works well for companies with products and services that remain fairly stable over time, like groceries, office supplies, or even SaaS products.
(ii) Discounted prices
If you’re in sales, you need to know what works best to pull in new customers. Offering your product at a discount—or, in some cases, even offering a freemium version—is a great way to bring in new customers (customers acquired through freemium offerings cost nearly half as much to acquire as those who sign up for paid offerings directly).
(iii) Promotional prices
What promotional offers would serve you and your customers best? Will markdowns create any additional profit, or are you better off charging the starting price? How big of a discount should you offer below your starting prices? How long will something take to sell at a specific price point? Optimizing your promotional prices can help boost sales for newly introduced products and promotional bundles—for example, a SaaS company launching a new product, or bundling multiple products.
Why many companies fail at pricing?
To make a long story short, most companies aren’t willing to put in the effort to optimize their pricing decisions. All the customer research needed to figure out the right valuations takes time and effort. Surprisingly, the average company only spends less than ten hours per year on their pricing strategy, which is not enough.
Instead, companies turn to strategies like guessing, relying on discounts, and not pricing based on value.
Many companies simply guess what an optimal price point would be instead of using analytics and metrics that their customers have given them. It’s an insidious cycle. With the right positioning and promotion, even guessing at your prices will work to some extent—it’s easy to take that as a sign that your pricing is “good enough.” Ultimately, though, you are leaving money on the table.
(ii) Misunderstanding tiers
Many companies don’t know how many different pricing tiers or levels they should incorporate into their pricing structure. It’s a common misconception that more tiers equals more conversions. Data shows that too many or too few options pushes away potential customers, with a clear decrease in conversion rates as the number of tiers gets higher.
(iii) Relying heavily on discounts
The problem with discounting is that many companies wield discounting like a sledgehammer instead of a scalpel. Yes, it juices your acquisition metrics in the short term, but over time discounting can reduce your SaaS lifetime value by over 30%. Discounted customers have just over double the churn rate of those who pay full price—they’ve either been trained to devalue the product, or they just weren’t the right customers in the first place.
(iv) Not pricing for value
Value-based pricing is the best price optimization model since it includes both you and your customer’s optimal prices. The goal with value-based pricing is to figure out how much each customer is willing to pay for your product, so you can maximize revenue by charging each customer exactly what they’re willing to pay. Figuring out what that price should be, though, isn’t easy.
That’s why so many companies lose out on revenue by setting their prices based on those of their competitors or on their costs—they don’t want to put in the effort.