How does pricing analytics work day-to-day and in budgets?

Every company must have a model to price its goods - it's a method to form the best price for a product. Your pricing model is a fundamental task shared between the marketing and accounting teams as pricing can increase sales, drop margins or send customers to your competitors. In a tough economic environment, sound pricing models are crucial.  

A data driven pricing model coupled with a sales budget that factors in variables such as price, margin and quantity will allow you to make strategic pricing decisions and budget in detail and with confidence.

What is pricing analytics?

Pricing analytics involves the collection, consolidation, and review of pricing data from various sources such as branch (bricks and mortar) sales, online sales and third party sell thru data in your financial planning and data analytics solution. 

Understanding price sensitivity allows business people to make informed decisions about market conditions, to identify opportunities for revenue expansion, understand the demand for their products and services, and visualize how customers respond to different pricing strategies and anticipate competitors’ moves. 

By analyzing historical data, companies can also identify which products are more profitable over time and adjust their prices accordingly. Every company can benefit from having a pricing strategy. Often if you stock many different product lines, you have an array of pricing structures that are implemented in many ways by your different sales reps. When you have a clear, consolidated view of your sales history, you can identify gaps in pricing and make more strategic pricing decisions. 

Depending on the industry, businesses use pricing analytics in diverse ways. For wholesale and retail businesses, pricing analytics can be used to identify seasonality trends and make price changes accordingly or to scenario plan for a potential new distribution channel to determine if the arrangement is worth pursuing. 

The benefits of pricing analysis  

At its heart, pricing analytics is helpful to set optimal prices—at which point, the ideal number of customers will buy from your business at a rate not too low to deliver a healthy margin. 

Pricing analytics improve overall business profitability when sales managers can closely match their pricing model to customer demand and accurately forecast trends, they can increase the revenue generated from each customer. Better margins can also be achieved if you can analyze pricing data and create new sales opportunities by encouraging customers to buy more products or buy in bulk. You can also reduce churn by making pricing changes based on demographic and geographical segmentation.  

Pricing analytics give companies the customer data they need to increase and decrease prices based on demand. 

By looking at behavior, demographics, seasonality, and other patterns, companies can use this data to better understand their customer base and provide better products to them through their effective pricing strategies. 

Sales teams can also use pricing analytics to tailor offers to specific buyer segments, ensuring they get the best value for their money. 

With the right segmentation and targeting, marketing teams can identify and build customer loyalty, lowering the total customer acquisition cost. 

Focus on profitable channels 

Another benefit of pricing analytics is the ability to identify profitable channels. Sales teams like Woodberry in the UK that use Phocas as their pricing analytics tool say:  

Our sales and marketing teams use Phocas to nail opportunities. Last month we identified the healthcare sector was producing some outstanding results. So, we were able to divert some of our sales effort away from low performing sectors into those that appeared to be more lucrative.

By using data and dashboards to determine where most of their high-ticket sales are coming from, Woodberry moved sales team resources away from unprofitable channels to find new customers in more productive channels. 

Improve Operational Efficiency 

Companies can save their sales teams time by giving them access to market research data as they set prices in targeting campaigns, another way that pricing analytics help businesses increase productivity. 

Sales teams can also use their data to automate certain processes, such as creating specific sales budgets for each branch based on the product pricing, customer behavior and profit margins in each demographic. 

Analysing and forecasting sales to this level of detail can be time-consuming and error-prone. However, financial planning and pricing analytics software like Phocas make this possible by providing reliable data that businesses can trust and use to build collaborative models. 

Include pricing tiers in budgeting models  

When using a FP&A and BI solution to budget you can add your pricing analytics data to the model and by doing so include more pricing opportunities. 

Using Phocas you can add other sources of data to showcase this detail. By connecting a sales database to your budget model you include products sold, prices, quantity and margins as well as sales by sales rep, customers and product groups.  

This means you can budget by sales rep and choose to consolidate everyone’s pricing to be the same to prevent leakage or instead use competitive pricing based on your customer segmentation in each vertical or geography. By combining the financial and sales data you can budget for sales as well as cost of goods sold for every rep, product class and new product. 

Pricing analytics takes the guess work out of sales budgeting and forecasting

With pricing analytics, you can price according to your target market. FP&A and BI enables companies to dramatically improve profitability by developing optimal pricing strategies to win more contracts and offer the most value to customers. Combining pricing with analytics and budgeting allows you to leverage your data to understand both the internal and external factors affecting profitability at a granular level. 

Despite the wealth of data available, many companies are still in the dark when it comes to understanding their customers. Yet, facing growing complexity and a omni-channel business environment, companies must be able to answer fundamental questions such as “Who is my most profitable customer?” and “What is my most profitable product or region?” Answering these questions can help you understand your customers and their buying behaviors to create the most effective pricing models. In other cases, analytics can highlight your most unprofitable customers so you can realign their discounts or other incentives to increase profits. With pricing analytics, you have a mechanism that functions as both a catalyst and a metrics engine for managing profitability.