What is pricing analytics?
Pricing analytics is the process of gathering, combining, and analyzing data about prices from different sources.
Businesses can use it to find ways to make more money, learn about the demand for their goods and services, see how customers react to different price strategies, and guess what their competitors will do next.
Companies can also determine which products make them more money over time by looking at old data and then raising or lowering the prices of those goods.
Pricing data is used in different ways by different types of businesses.
Pricing analytics can help subscription-based businesses figure out how to set prices for different types of customers and how much each customer is worth throughout their membership.
The other way retail businesses can use pricing analytics is to find regular patterns in sales and change prices to reflect those patterns.
Synonyms
- Price analysis examines and researches the cost of goods and services to determine the most suitable pricing structure for a given product or service.
- Price optimization is a strategy used to determine the best prices for goods and services to maximize sales revenue.
- Price intelligence is collecting, analyzing, and interpreting market information to make better pricing decisions.
Why pricing analytics are important
Almost every type of business can benefit from price analytics. Large businesses, which often have complicated pricing structures and lots of products, can benefit from being able to look at pricing data to find ways to make more money.
Some of the benefits of price analytics are:
Find chances to raise prices
Businesses with access to pricing data can find chances to help them make more money.
This is especially important for companies switching from one-time sales to recurring income. The company can make bundles with different price points to make the most money per sale by knowing what customers want regarding different goods and services.
Pricing analytics can also be used to find chances to offer discounts without losing money on the margin. Companies can look at the data to determine which deals will bring in the most customers while leaving them with a good profit margin.
Improve your pricing strategies.
Price optimization is an ongoing process that makes it easy for companies to miss out on sales chances.
There are several ways that business can become complicated:
- A large customer base with different average deal sizes (for example, enterprise, mid-market, and small and medium-sized business buyers)
- Several product lines with different pricing structures (for example, one-time services, subscription models, and tiered/package offers);
- Market situations that change often
- A lot of transactions
- There are a lot of routes and ways to get to market
- Quote-based pricing
There is a slight chance that a business has found the best way to price its goods and services.
Businesses can find holes in their pricing plans and fill them with more accurate, well-informed pricing decisions by looking at old data.
Boost your profits
Pricing analytics is mainly used to set the best prices. This way, the correct number of customers will buy from the business at a price that doesn’t drop too low to keep a good profit margin.
Pricing analytics help a business make more money in many ways:
- More money is made per person on average. Businesses can make more money from each customer if they can closely match their price model to customers’ wants and correctly predict trends.
- They are making more money. Companies can look at price data to find chances to offer deals, which could bring in new money by encouraging customers to buy more.
- Less turnover. When businesses know where their prices are too low, they can fix it and keep more of their customers.
What Customers Think
Pricing analytics help businesses know about their customers and change prices based on demand.
Firms can use this information to learn more about their customers and give them better products by looking at trends in their behavior, demographics, seasonality, and other areas.
They can also use price analytics to make sure that certain groups of buyers get the best deals and get the most for their money.
Sales and marketing teams can better find and connect with their ideal customer profile (ICP) using the correct segmentation and targeting. This lowers the total cost of acquisition (CAC).
Focus on Channels That Make Money
Aside from learning about customers, one of the best things about pricing analytics is that it helps you find profitable outlets.
Prospecting is the hardest part of sales for more than 40% of people who work in sales. Businesses can use the data used for price analytics to determine which customers bring in the most money, which helps them find patterns.
Businesses can put more resources and money into areas that bring in the most high-ticket sales by using data to determine where most of their sales are coming from. This way, they can avoid spending money on outlets that don’t bring in enough sales.
Boost the efficiency of operations.
Businesses can save money and work more efficiently with price analytics. These tools save time for both sales and marketing teams prospecting and targeting campaigns.
Companies can also use their data to automate some parts of their business, like putting together sets of products for customers or making sure that sales and deals happen at the correct times.
Most of these things take a lot of time, are easy to mess up, and require a lot of guessing. Pricing analytics reduces mistakes by giving businesses accurate data they can rely on and use to make quick choices.
Metrics for Pricing Analytics
Companies must look at the correct data to understand customers’ behavior and develop the best price plans.
To understand price, here are the most critical business metrics:
- Price Elasticity of Demand: How much changes in price affect the demand for goods or services, measured by the percentage change in demand for each percentage change in price. When flexibility is high, price changes can significantly affect demand.
- Price Sensitivity: Price sensitivity is how much customers are affected by price changes. It is measured by how much sales or purchases change after a price change. When high awareness increases, customers actively seek better deals or avoid specific prices.
- Revenue per Customer: This number shows how much each customer brings to the business. Different companies and business plans make different amounts of revenue per customer. Comparing your pricing strategy to industry standards is an excellent way to see how well it’s working.
- Quote-to-Cash Conversion Rate: The Quote-to-Cash Conversion Rate shows the percentage of accepted quotes turned into sales. A pricing plan works well if it has a high conversion rate.
- Average Order Value (AOV): The average amount of money a customer spends on each order. Companies with more expensive products can have a high AOV but may still have lower revenue per customer or fewer customers, which means their pricing plan isn’t working either.
- Customer Lifetime Value (CLV): The total money a customer will likely spend with a business. This is linked to customer loyalty. If a company’s customers leave before CLV can grow, it should look at its prices and see if they meet customer standards.
- Gross Margin: This shows how profitable a business is per transaction, considering all the sales costs. High sales numbers can make up for low margins and vice versa.
- By Product or Customer Segment: How much money a business makes from a particular product, service, or group of customers compared to how many resources it needs to make that money.
Different Kinds of Price Analysis
Price analytics can be divided into three main types: descriptive, predictive, and prescriptive.
Giving details
Descriptive price analytics lets you get a big picture of past data, like sales and customer behavior.
Here are some examples:
- Average order value
- Sales per buyer
- Rate of quote-to-cash conversion
Businesses use descriptive analytics to find trends, learn how customers act, and analyze feature value. The results of these analyses help them decide how to price, market, and sell their products.
Ahead of Time
Data mining and machine learning are used in predictive pricing analytics to find trends in the data and guess what will happen in the future.
Some examples are:
- Customer lifetime value
- Price sensitivity
- Price elasticity of demand
Businesses can use predictive analytics to determine how customers will act and determine the best ways to price their goods and services.
Since they are predictions rather than insights from the past, they work best for businesses that make consistent income, which makes the predictions more accurate.
Doing something
Advanced algorithms are used in prescriptive pricing analytics to find the best pricing plans and give real-time feedback on how price changes would affect future performance.
It’s like predictive analytics, but it gives businesses suggestions they can follow instead of leaving that up to them.
This kind of data is made by software that automatically finds the best prices. Businesses can change their prices in real-time to make the most money and stay competitive by answering, “What should we do?”
Prescriptive pricing analytics can also help divide customers into groups and find the ones with the best lifetime value.
What Does Pricing Analytics Software Do?
Businesses can set the best-selling prices or offer the best software subscription plans without hurting their bottom line if they use the right pricing analytics software.
Some of the traits are:
Monitoring in real-time
Businesses can quickly change their pricing strategies by monitoring real-time data about customer responses, rival prices, and market conditions.
This can be done with a pricing analytics tool that keeps track of what customers buy and how rivals’ prices change.
Alerts let companies know when customers’ habits change or when prices at competitors fall. They can also tell you when customer and market data has changed, like when a customer’s buying habits change or the seasons affect the market.
Automatic alerts that give companies information about their competitors help them keep track of their list prices, sales, and discounts so they don’t miss any chances.
Adding things in
Price optimization and data analysis are built right into some tools. It should work with other parts of the company’s tech stack if it doesn’t already, such as:
ERP
ERP software keeps track of customers’ purchases, how prices have changed over time, and other business data.
CRM
Businesses can see information about their customers, like what they buy, how they like it, and how to contact them if they connect with a CRM. This helps them make more relevant offers to each customer and get the right word to the right people.
BI Software
Business intelligence (BI) software should work with analytics tools so that data doesn’t get stuck in separate silos. This way, companies can use the exact source of information to decide on prices, products, and marketing.
Configure-price-quote (CPQ) software helps businesses quickly make correct quotes and set up complicated products. By integrating these two systems, companies can ensure that their CPQ system always shows the correct price for the product or service a customer wants.
Getting paid
A big part of how a business sets its prices is how it handles bills. The pricing analytics tool should be able to connect to automated billing so that businesses can adequately keep track of how much money they make from each customer.
