Pricing is one of the most powerful tools a business has for improving profitability, according to professional services firms Deloitte.
Price management, according to the firm can increase a company’s margin by two to seven per cent in 12 months, yielding a return of investment between 200 and 350 per cent.
However, according to Deloitte, many companies are unable to unlock the full potential of pricing “because they’re building on a poor foundation in analytics and don’t have the appropriate level of visibility into the true profitability of complex channels, product portfolios and customers.”
Saddled with this shortcoming, most organizations “revert to gut instincts and traditional guidelines” in their decision making process, the company said.
Big data and analytics methods can help businesses better understand how prices for goods and services should be set and how their customers react to the prices they set.
The problem is, different vendors of pricing analytics tools have different approaches to pricing analytics. Each vendor provides detailed analyses as to why the approach they use is better than the rest.
There are three different broad approaches to pricing analytics:
Eliminate deviant behaviour – This approach looks for data outliers among transactions, products, customers, sales representatives and market segments.
Some vendors will recommend analyses for each customer vertical industry, testing potential hypothetical opportunities based on spotting and correcting deviant behaviour.
This approach focuses on looking for things such as low margin by transaction, or low margin by customer and excessive price variations across customers.
This approach can help businesses deviant behavior – spot instances when a customer pushed for a better deal using pricing offered by a competitor and the sales rep failed to push back. Another scenario could be a customer negotiating a volume discount but failing to come up with the volume when they have paid for the discounted price.