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80% of the respondents in a 2019 study think that top-line growth through pricing is the biggest driver of future profit growth. After all, pricing has an immediate and significant effect on profit compared with other tools that require more coordination and time for roll out.

Increasingly, the opportunity in strategic pricing is driven by pricing analytics. Pricing analytics software takes advantage of new, more up-to-date information on the market and the availability of automation to apply complex pricing models. Big Data and pricing analytics are creating new opportunities for pricing strategy.

Pricing analytics marketing comes in three types: price optimization, discounting, and portfolio management. Artificial Intelligence and other advanced techniques are driving the state of the art in these fields.

The price optimization opportunity expands with dynamic pricing

Price optimization initially meant primarily configuring and quoting pricing for solutions with many SKUs and interrelated dependencies. Now, dynamic pricing-a flexible pricing model in which the price varies based on demand-has become available beyond the travel and entertainment industry, where it is common.

This current generation of price analytics marketing uses deal-based data for B2B sales models. Dynamic pricing also estimates demand based on segments and even behavior to maximize the size of wins and lower prices when maximizing volume is needed instead.

Discounting gets better with data

Price incentives – discounting and rebates – play an important role in many B2B and B2C industries. Without data, it is easy to get discounting wrong, typically by charging too little.

McKinsey outlines this tendency in a recent article. In the software industry, SaaS models and open source software are creating downward price pressure for commercial vendors. These trends mean that winning strategies depend on getting discounting right to grow. Pricing analytics takes the guesswork out of deciding which deals should be offered a discount to win the business. In advanced applications, buying signals or behavior can provide indications about intention to evaluate, to buy, and to close without a discount.

Pricing analytics makes portfolio management more strategic

The last type of pricing analytics is portfolio management. Pricing for new products in the portfolio and adjusting prices for new packaging and product line needs are examples of pricing analytics for portfolio management.

Pricing analytics services in this area includes segmenting past buyers to create new segments with unmet needs or refine existing segments to optimize revenue, growth, or other metrics. Other pricing analytics marketing includes cross-selling, or selling additional products to customers, and up-selling, or selling a more expensive offering to a prospect of that offering is a better fit.

Depending on your approach for pricing analytics, several options exist. Pricing analytics software may be available for your particular application or industry. Pricing analytics services from companies like Syntelli Solutions help you get started with low risk or expand your existing pricing analytics initiative.