Price analysis: Clean and usable data as a value in itself


How do business price their products?


Do they guess what the fair price is or is there sufficient data?


What are the strategies in price analysis?


What is Price Analysis?


Price analysis determines the price of the products and/or services in the product cycle. It shows how the product, distribution, price, and promos work together to create an effective marketing strategy and product recall.


It analyzes the pricing data to develop a price strategy. This includes a mixture of product lines or strategize for a new product price.




What Is The Difference Between Cost And Price Analysis?


Cost and price analysis are two different thoughts to decide on the appropriate value of products or services prior to purchase.


Cost analysis is the projected price based on the subcontract work done on the product. Whereas in price analysis is the projected price on the evaluation of the new products in test marketing and placement strategy.


Another good example is what do the business executives use to find trends in the market. They use the volume price analysis to predict where the market is going. The volume price analysis gives an overview of the machinations of the market in relation to supply and demand. The fluctuations between the supply and demand are the basis in making the right decisions to sell or buy. With the data from the market trends, you can predict where the price is going. And act accordingly to increase profits.


Often price analysis experts and pricing professionals complain about the quality of the data they need to spend significant time cleaning and reordering before useful price analysis can be performed. In nearly every case we have seen, the data coming out of the corporate systems (see blog on pricing software tools) is incomplete, inconsistent, untidy, non-uniform etc and requires a methodic approach to enable it for purposeful study.


This “data cleanse” is often seen as a necessary evil i.e. something that must be done to get to where we would have liked to be in the first place. Limited value is placed on it other than as a means to an end.


We have numerous examples however, where effectively cleansing data enables more than price analysis but also creates a “viable client value” in its own right. This is particularly pertinent to B2B business where products or services are purchased by a professional procurement specialist.


The problem here is there are no softer data skills like deep comprehension of the problems in the commercial sector, relying more on the decision-makers, to describe the data into comprehensible information and address patiently the numerous issues of those involved in analyzing all the data.


Without the right expertise, methods and people on the work done on the data analysis will fail. More often, price analysts immerse themselves in finding patterns in the data stream. There’s no solution given since they are isolated from the everyday operations of the company. Hiring the right analysts and embedding them to the daily grinds of the business can provide an insight into the problems and will help to improve the company.





 Proper Price Analysis Done Right


  • Inculcate the business goals to the analysts and chart their progress. Though the results will take some time, you can expect real information on cost savings, new revenue, improved customer satisfaction, or risk reduction.


  • Get the right pricing analysts and assign them to departments that need their expertise. With their knowledge of the daily operations, they provide solutions to improve the company.


  • Describe clearly the problem to the analysts. Not to be muddled by office politics, fear and conflicting agendas by those making the problem. A clear cut description of the problem can provide a simple and effective solution. Even without data analysis and without office politics.


  • Teach even to the non- price analysts about proper data analysis, people who work in the daily operations of the company can effectively analyse the data. Give to the management for easier decision-making.


The ability of the company to handle the massive data and using that information is essential for its success nowadays. It cannot survive without using the necessary data to continue its business. Less than half to the company’s data used in decision-making and far less one per cent of that data actually read.


How does the company process the data for pricing analysis? Having a chief data officer (CDOs) and data-management functions would be ideal. But without a clear agenda for organizing, governing, analyzing, and deploying the organization’s information assets, it will fail.


Different Approaches To Pricing Analysis


There are two schools of thought in regard to securing data management:


  • Data defence – used in downsizing risks that include following government regulations on data privacy and financial reports integrity, detecting and eliminating fraud, and preventing theft with detection programs. It also ensures security on data flow in the company’s system by authenticating sources such as customer and supplier information or sales data in a single source of truth.


  • Data offence – concentrates more on increasing revenue, profitability, and customer satisfaction. It gathers information on customer insights on their products to help in the decision making of the management. It is more focused on activities such as sales and marketing in real-time than the data defence.


There Must Be Balance


Both of these are crucial to the success of the company. But a balance must be strike between the two to be effective. The balance both depends on which data is standardized or flexible. If the data is uniform or straight forward, it analyzed for security or government compliance, for example, health service or insurance. If flexible, the data analyze on improving the business.


Take for example the Apple pricing analysis. The data defence analyzed if the product is complying the government’s regulations on smart devices. If not, the government will impose restrictions hence affecting its price. The phone’s system gets easily hack so nobody buys it. Thus, security measures are in place in the device.


Whereas in data offence, information regarding the ease of handling, what the user sees in the apps and its price.  All of it used to further improve the device and profitability.




Price analysis benefits – “Do not focus on the price of light bulbs”


Pricing teams will often argue a customer should not focus on the price of unit rates i.e. the individual light bulb, but the cost to light the room over the year i.e. the total cost of ownership for lighting. In itself, this is a completely sensible approach.


We have seen many instances where this approach falls flat because the pricing manager is unable to tell the customer how much they will actually spend over the year i.e. they can not demonstrate that the total cost of ownership approach is more cost-effective.


The most common reason for the failure to do this is, you guessed it, unclean or non-uniform data.


By cleansing data for pricing analytics, we can also much more accurately calculate and demonstrate the financial and other aspects of long term contracts.


We have seen companies gain assurance over the likely total spend relating to a customer and use this in their sales and marketing.


As pricing/cost volatility can be one of the bigger risks when buying a service, a sales pitch that guarantees a cap on that possible price is very appealing.


This practice is commonly used in mobile phone plans – whereby consumers pay more than they need so as to cap their spend i.e. unlimited minutes etc.




  • Price analysis is effective when the massive data can be sorted and turn to useful information. The pricing team analyse and find the fair price for the item.


  • Price analysis uses data defence and offence to balance the factors to find the proposed price.


  • Pricing teams need all the information from the responses of the consumers and competitors’ price comparisons to analyse.


  • Softer data skills needed which the pricing teams often don’t have when they organise price data. They are often too technical and forget about why they are organising the data. As a result, they don’t organise the data properly and subsequent price analysis is largely useless.




  • Data gathering need not be a burden just because it’s too massive to tackle. It just needs to have the right program and trained people to sort it all out.


  • Price analysis is a group effort for the pricing team. They must contribute to the improvement of the company and explain to them the business aims.


  • Start teaching the employees on data analysis so the data flow is easier for the management.



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