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What is Pricing Intelligence?
Pricing intelligence is a data-driven process for quantifying, tracking, and analyzing market dynamics and competitor price movements to make educated pricing decisions. Competitor pricing, consumer demand, and web scraping are all sources of pricing intelligence.
A subset of competitive intelligence, its objective is to help businesses understand the impact of market-level pricing intricacies and act on them in a way that maximizes profitability while remaining attractive to customers.
When companies gather pricing intelligence properly, they can use it to do the following:
- Optimize the current pricing strategy
- Identify new revenue opportunities
- Vertically differentiate their product
- Improve in-store shopping experiences
- Boost pay-per-click conversions
- Adopt competitive pricing strategies
- Implement value-based pricing
Since “intelligence” inherently means “data,” pricing intelligence relies on having real-time access to various types of information. For that, businesses use modern data mining techniques like web scraping and machine learning.
- Competitive price intelligence
- Competitive price monitoring
- Ecommerce pricing intelligence
- Online pricing intelligence
Why Pricing Intelligence is Important
In both B2B and B2C, price elasticity varies wildly from one product or customer segment to the next. In that sense, price optimization is a completely unique exercise for every business that requires an in-depth understanding of the data underlying their product (and their product only).
In the B2C world, price transparency has always been a requirement, and it’s quickly becoming a priority for B2B buyers. A 2021 McKinsey survey found that 83% of B2B buyers cared more about transparent pricing than brand reputation and a recent Deloitte poll found that nearly two in every five has switched to a competitor for the lack thereof.
Although giving customers accurate pricing information upfront is sometimes impossible (e.g., in cases of high product complexity), many businesses have at least become more open about their pricing model.
With the abundance of information available to buyers online, it’s become increasingly easy to make purchase decisions based on price. They could be researching a company’s product at any given time, which underscores the need for businesses to actively monitor their market to maintain competitive — sometimes up-to-the-minute — prices.
Competitor Price Comparison
Increased aggression from competitors is another critical contributor to the growing importance of price intelligence — given the large amount of data any company can access with the right resources, it’s become easier and easier to be savvy with pricing.
Although competitor pricing isn’t the be-all-end-all, it does play a critical role in setting prices. By monitoring competitors’ pricing, businesses can accurately compare their own performance to the market and take appropriate action if needed (e.g., lowering or increasing prices).
Understanding Perceived Value
How much a customer is willing to pay for a company’s product is a dynamic factor that varies depending on a customer’s needs and circumstances.
By gathering pricing intelligence, businesses have a better view of their customers’ “perceived value” based on their product’s features and current market prices. They can use this data to set optimal prices based on customer demand while differentiating from competitors.
Pricing intelligence is the backbone of any dynamic pricing strategy. It allows companies to automatically adjust prices based on competitor pricing, market conditions, or a variety of other factors, all while maintaining their desired profit margins.
Massive online retailers like Walmart and Amazon (which change their prices 50,000 times per month and every ten seconds, respectively) are perfect examples of this. To best match any market trend in near real-time, they rely heavily on their pricing intelligence software and machine learning algorithms.
How Does Price Intelligence Software Work?
Since data is usually scattered across multiple sources and in different formats, a price intelligence tool is required to gather and analyze it. The workflow of price intelligence software typically consists of five stages:
In this initial stage, the software identifies and locates product pages on various competitor websites. It scans and crawls these websites, searching for relevant information about the products being compared. This information can include product names, descriptions, images, market prices, and other identifying features.
In the case of data from other sources, such as ERP systems or POS data, the software pulls this information from the backend.
Once the product pages have been scanned or crawled, the software uses algorithms (or, in some cases, human intelligence) to determine if the products match exactly or if they are comparable. This process ensures that only relevant and accurate comparisons are made between the products on different websites.
Several techniques, including text analysis, image recognition, and machine learning algorithms, help companies accurately match products, pricing information, sentiment, and demand.
After identifying matching or comparable products, the software extracts key information from competitor websites, internal databases, or online sources. This includes the price, shipping details, stock availability, and any promotional offers associated with the product. Web scraping techniques or APIs are often used to collect this data.
4. Measurable Data Quality
Once the data has been extracted, it’s added to a database and checked regularly for accuracy. Price intelligence software ensures the gathered information is up-to-date and reliable, as outdated or inaccurate data can lead to poor pricing decisions. Data quality is maintained through continuous monitoring, validation, and cleansing processes.
5. Reporting and Analytics
The final stage involves transforming the collected data into actionable insights. Price intelligence software typically includes reporting and analytics tools that allow users to visualize and analyze the data, identifying patterns, trends, and opportunities.
These insights are considered price intelligence — they inform strategic pricing decisions, such as switching to competitive pricing strategies or targeting specific customer segments with personalized offers.
Benefits of Implementing Pricing Intelligence
Companies using pricing intelligence have access to more (and better) data than those that don’t, which enables them to set their ideal price position in their respective markets. This leads to tangible benefits, including:
- Increased profits thanks to improved pricing accuracy
- Greater customer loyalty due to competitive prices and better offers
- Potential revenue growth in the event of a price increase or better-matched pricing model
- Improved visibility into the market
- Reduced price-related risks
- Quicker feedback loops for faster business decisions
- Reduced manual effort through pricing automation
In short, pricing intelligence helps vendors price their products more favorably — whether that means higher, lower, or match-market prices — to drive additional sales. Customers enjoy prices that match their needs and expectations more accurately.
Pricing Intelligence Use Cases
Just about every vertical can take advantage of the benefits pricing intelligence has to offer at some level. Enterprise companies use AI-driven pricing analytics engines and data science tools to optimize their pricing strategies, but SMBs can use basic scraping and reporting tools to get started.
Common use cases for pricing intelligence include:
- Monitoring competitors’ prices and offers on a regular basis
- Identifying opportunities or threats from new market entrants
- Conducting price audits to ensure accuracy and consistency across channels
- Analyzing customer behavior by tracking sales conversions, average order value, etc.
- Enforcing compliance with local pricing regulations
- Understanding price elasticity to identify when, where, and how much to adjust prices
- Creating dynamic pricing models based on competitor prices or customer segmentation
- Implementing automated repricing based on market conditions
Let’s take a look at how that might play out in reality:
Example #1: B2B SaaS
Suppose a B2B SaaS company is scaling its differentiated product offering to meet the demand of more than one market. They plan to introduce a tiered pricing model but aren’t sure whether to add premium features and pricing or build microservices for different segments.
Using pricing intelligence software, they examine their competitors’ prices and compare their products to their offerings. They also analyze customer behavior and sentiment towards their products, which helps them determine the highest price customers are willing to pay.
Ultimately, they realize the gap in competitor pricing is at the premium level, so introduce a premium tier. Knowing their customers’ needs, they offer discounts for annual subscriptions to ensure better sales conversions and higher ARR.
Example #2: Direct-to-Consumer (DTC) Ecommerce
An ecommerce retail brand sells an in-demand product in an already-saturated market. Since the market is already well-defined, pricing needs to reflect what customers are already willing to pay.
Using pricing intelligence software, they crawl competitor websites and high-volume retainers like Amazon to identify best-selling products and match them with their own. They compare prices, shipping, stock, and promotional offers to determine the optimal price point for their product line.
They then use analytics tools to create reports that show how customers respond to slightly different price points to refine the small numbers.
Example #3: Hospitality
A hotel chain in a major metropolitan area relies on up-to-the-minute pricing so its rates reflect current market dynamics. But the owner doesn’t have time to monitor every large upcoming event or forecast the weather to identify demand.
Using pricing intelligence software, they can monitor prices from competitor hotels and OTAs near their location on a daily basis. They then use real-time pricing (RTP) models to adjust their own rates accordingly, considering factors like demand, occupancy rate, seasonality, and local events.
How to Optimize Price Intelligence to Grow Revenue
Although pricing intelligence is a powerful asset to companies that want to compete, it only works if it’s well-executed.
Identify Your Competitors
Start by identifying the companies in your market segment that actually compete for your buyers’ attention (and money). These don’t have to be direct competitors — they could be suppliers, vendors, retailers, or alternatives. Airbnb, for instance, is a competitor to hotel chains because it offers lodging to people who would otherwise potentially use the chain’s services.
To identify your company’s competitors, ask yourself the following questions:
- What are customers buying instead of our product or service?
- Who do they compare us to when making purchasing decisions?
- Where do they look for better deals, offers, and discounts?
- What other products or services are in the same category as ours?
It helps to look at website and search engine data as well. You may be surprised at some of the businesses that are stealing your buyers’ search interest.
Monitor Competitors’ Prices & Offers
Collect data on your top competitors’ product prices, promotions, and offers to get a better understanding of the market. This will give you insight into their pricing strategies and any changes in their offer mix.
Look at premium sellers, loss leaders, and bulk discounts to understand how your competitors are trying to win customers.
During this step, adding a human intelligence element can help you identify hidden trends (especially if your customers are discreet about their actual product pricing. Interviews, surveys, and mystery shopping can help you uncover valuable insights that might not be visible even on the backend of a competitor’s website.
Analyze Pricing Strategy
Armed with new data, look closely at how your competitors are pricing their products and services to identify patterns.
Are they using geographic targeting to price different segments of customers differently? Do they offer discounts for bulk orders or loyalty programs?
And most importantly, why would or wouldn’t I price my products or services similarly?
Analyzing customer behavior is also key. Competitive price matching isn’t always the best call, especially if customers are willing to pay more for a product or service that solves a more niche or complex problem.
Implement Pricing Intelligence Software
Once you’ve defined your workflow, implement software or an app that can help you carry out the data mining process without so much manual input.
These tools are designed to streamline and automate pricing decisions with artificial intelligence (AI) and machine learning (ML) algorithms. That way, you can price products quickly and accurately while considering market conditions, customer sentiment, and competitor moves.
Integrate with CPQ
CPQ software isn’t “pricing intelligence” per se, but it is an important tool for two reasons:
- It’s a critical data source. Product, sales, and customer data from CPQ gives insights into real customer preferences and sentiment as they play out on the sales floor.
- It keeps you organized. CPQ software keeps track of your pricing, discounts, product configuration, and availability data in an efficient and organized manner, and enforces it in contracts, quotes, and invoices.
Advanced CPQ platforms also have AI-driven pricing engines, which take the guesswork out of pricing decisions by suggesting optimal prices for each product or service without the need for the entire pricing intelligence process.
People Also Ask
What are the benefits of smart pricing?
Smart pricing (i.e., using pricing intelligence to make real-time pricing updates) helps businesses remain agile in their market by providing insights into customer sentiment, competitor moves, and market conditions. The end result is more informed decisions about their product or service prices that more accurately reflect market dynamics.
What is pricing intelligence in retail?
Pricing intelligence in retail entails some level of dynamic pricing to accurately fit market demand. At the enterprise level, companies like Walmart and Amazon change their prices continuously, but even the smallest boutique retailers make price adjustments semi-frequently. AI-driven software and data mining tools help retailers implement dynamic pricing models with confidence.
What is eCommerce pricing intelligence?
Ecommerce pricing intelligence describes the automated process of applying AI and machine learning to monitor pricing, product, and availability changes from competitors, adjust prices according to demand, and optimize offers (e.g., shipping, discounts). The aim is to maximize profits while still ensuring the online retailer remains competitive in a given market.