Pricing Software & Optimization Tools: Select Correctly, Use Profitably

Executive Summary

Companies in retail and e-commerce face the challenge of making their pricing more professional when margins stagnate, resources become scarce, or manual pricing processes are inefficient. Professional pricing software offers strategic added value here: It automates administrative tasks, enables data-based pricing decisions and maximizes sales and profit through intelligent algorithms. While rule-based pricing (level 1) creates transparency and trust, demand-based price optimization (level 2) uses machine learning to forecast optimal price points.

However, the correct selection of a pricing solution requires a systematic approach: Studies show that 60% of companies regret software purchases, often with significant financial consequences. A comprehensive, objective and efficient evaluation of various software solutions – ideally with external expertise – is therefore crucial for the long-term success and ROI of the investment.

1. Introduction: When should you deal with pricing software and price optimization tools?

Three reasons often initiate the introduction of professional pricing software in retail, wholesale and e-commerce:

The margin or growth development does not meet expectations.
The resources in the team where pricing primarily takes place – category management, procurement/purchasing, pricing.
The current pricing is perceived as too manual, not sufficiently differentiated and too “makeshift” or the maintenance effort for the existing pricing system exceeds the time for actual use (some companies also speak of “proliferation” and refer to locally stored Excel spreadsheets for pricing).

In this situation, it makes sense to consider technical support that enables better pricing decisions with less manual effort.

Important: The persons acting retain financial responsibility and substantive understanding of pricing. No one leaves the proverbial “driver’s seat.”

2. What are Dynamic Pricing Software or Price Optimization Tools?

2.1 Dynamic pricing is not frequent, but conscious price changes

In retail and e-commerce, dynamic pricing is often equated with frequent price changes. In our understanding, this is not a mandatory feature. We understand dynamic pricing to be adaptive pricing. Over time, it is regularly (“dynamically”) checked whether the factors and market conditions that determine pricing have changed compared to the last pricing. These factors include, for example:

Purchase prices
Competition prices
Non-binding price recommendations
Range extensions (such as additional (a) brands, (b)
Private labels, (c) price ranges, (d) package sizes, (e) model variants, etc.)
Upcoming, past or parallel promotions and promotional prices

If the factors have changed, it is decided whether a price change is necessary. You can theoretically make price adjustments in real time (“real-time” or “near real-time”). However, if “price stability” is part of your pricing strategy that you want to maintain, evaluate “dynamically” whether the advantage of a price change and price update outweighs the disadvantage of foregoing the desired price stability. You frequently check whether prices need to be changed, and just as frequently decide whether you actually make the price adjustments according to the market changes.

2.2 Pricing Software and Price Optimization Tools

You can perform this regular review of how the market and other factors have changed manually. Likewise, you and your pricing managers can manually check whether you need to manually optimize the current price for each of your products.

The manual review and analysis of the factors that determine your pricing can be automatically taken over by a tool. This automation saves time and makes the work in price management and the adjustment of prices much more efficient.

Pricing managers work with less effort “in pricing” and can devote more time to working “on pricing”, such as developing smarter pricing strategies.

Pricing software not only helps to automate pricing decisions – we speak of “Price Automation” here.

Pricing software also offers support for pricing decisions as such. Setting a best price – in view of a defined pricing strategy – is referred to as price optimization, also as “Price Optimization.”

Among the applications that support Price Automation and Price Optimization, there are some synonymously used terms: Pricing Software, Price Optimization Tools, software solutions for pricing, Dynamic Pricing Solutions and some other creative terms.

3. Why should you deal with a professional pricing software selection?

The selection of pricing software is at least a medium-term commitment and means a short-term investment in implementation. This decision should not be taken lightly.

Because more than half of all companies are dissatisfied with their purchasing decisions for software. A survey of 3,500 companies (350 of them in Germany) shows that 60% (63% in Germany) regret at least one technology purchase of the company in the last 18 months.

Of these, 59% describe the financial impact of the regretted software purchase as “monumental” and “significant.”

While incorrect decisions in software purchases are +68% more likely to be based on a ChatGPT search, successful software decisions are +56% more likely to start with the support of experts.

In short, professional support in the selection process of suitable pricing software is worthwhile from an entrepreneurial point of view.

Source: Capterra’s 2025 Tech Trends Survey, Sample: 3,500 Software Buyers

4. What is the entrepreneurial added value of pricing software?

Important aspects have already been described above, such as how pricing software delivers entrepreneurial added value. We now want to supplement these different sources of added value.

Pricing software…

…replaces manual, administrative work by automating defined processes and rules. Pricing managers can concentrate on strategic, more value-creating activities.
…determines optimal prices and suggests price changes that increase sales, contribution margin or margin – depending on the objective of dynamic pricing.
…requires the configuration of the pricing rules by a pricing manager. This externalizes the implicit “head knowledge” of experts and conserves it in decision trees. The risk of knowledge loss in the event of a change of role is significantly reduced.
…shifts the discussion about individual prices to how they came about. Thinking in rules and mechanisms supports organizational learning.
…and its introduction often act as a catalyst to improve the data quality and availability of important data pots.

5. How do pricing software and price optimization tools work?

In retail and e-commerce, software support for pricing is divided into two levels.

Level 1: Pricing rules lead to trust in an automatic price calculation

The first level includes decision rules that are applied in rule-based pricing (also “rule-based pricing”). An internal pricing manager determines the strategic orientation of pricing and defines corresponding decision trees, which are scaled by a pricing system. These rules begin with a definition of the scope, e.g. range sections and article roles (e.g. all corner articles/KVIs in the category XYZ).

Then rules and rule priorities are set. For example, target prices and target margins are specified, relevant competition prices are defined, maximum distances to competition prices are determined, price distances to related products are maintained, the non-binding price recommendation (RRP) is collected as the maximum price and an absolute minimum margin is set as the price floor (“safety net”).

The result of this price calculation can be traced and recalculated at any time. If a price is classified as incorrect, the underlying rule can be systematically corrected. The configuration of pricing rules promotes thinking in mechanisms and processes that are required for objective pricing. Pricing according to gut feeling or “expert assessment” is replaced by data-based pricing.

This experience of being able to recalculate prices increases trust in an automated price calculation. This trust is important for the second level.

Level 2: Price optimization increases the financial contribution in pricing

The second level builds on the user-defined decision rules and considers them as framework conditions. These framework conditions define a possible price range. Within this price range, an optimal price is set in accordance with the specified pricing strategy, which maximally achieves the target value of a so-called target function. This process and the underlying technology are understood as price optimization.

In this process of automated pricing, artificial intelligence or, more accurately, machine learning takes place. Algorithms predict the demanded sales for different price points within the possible price range. Therefore, this more advanced approach is also referred to as demand-based or demand-optimal pricing (“demand-based pricing”). For each of these price points, all financial metrics and KPIs can then be derived: Sales, contribution margin per unit, contribution margin in total, product margin (“Gross Margin”, in %), units sold. Depending on the chosen objective of the pricing strategy, the optimal price is automatically selected, which leads to a maximum result. This optimization of prices can also be achieved dynamically while complying with constraints: “Set the prices so that a minimum sales growth of 2% is maintained and the contribution margin is maximized.”

Price optimization not only works for individual products in the range, but also for larger range sections. Technically, cross-price elasticities for related products (substitute and complementary products) are taken into account in pricing.

The advantage of demand-based price optimization is an improvement in decisions regarding price changes. Sales and profit as well as their ratio are maximized compared to purely rule-based pricing. The price optimization software sets its own prices in such a way that the best results for the company are achieved in view of the chosen pricing strategies. The demand forecast underlying price optimization simulates the effects of price updates before they are implemented. This forecast ultimately also provides the basis for making pricing decisions and thus for the release of price recommendations by internal pricing managers.

But even if the possible, user-defined price range is specified by an internal expert, the optimal price or the underlying demand forecast can no longer be recalculated. This circumstance can be perceived as a disadvantage in an early phase of the software introduction, which is resolved with increasing experience of the internal team and professional change management.

6. What data does Price Optimization Software work with?

In the retail industry and in e-commerce, at least six data sources are connected to pricing software:

Transaction data provide the basis for training the forecast models for demand-based price optimization.
Data from the product information management and catalog system (PIM) provide central product information (including RRPs, seasonality indicators).
Financial data provide important financial metrics for pricing (e.g. purchase prices, CM1 to CM3).
Inventory data provide information on product availability, inventory levels and inventory quality (e.g. over- or understock).
Competition data and prices of competitors come from price monitoring by crawling providers and market research agencies (instore survey or panel data) on competition prices and availabilities.
Promotions and promotional data connect regular shelf pricing with promotional pricing

7. How do you evaluate different pricing tools in comparison?

The evaluation of different providers of pricing software is ideally carried out (a) comprehensively, (b) objectively and (c) efficiently.

A comprehensive evaluation refers both to (a) a longlist of relevant providers that is as complete as possible and to (b) including all relevant evaluation dimensions and criteria as completely as possible. These evaluation criteria include

the software provider as a company
its reference customers (industry, region, reputation or relevance of previous installations)
functional requirements (also with regard to “Artificial Intelligence & Price Optimization”)
technical requirements (including user experience and customizable user guidance)
organizational & further, specific requirements (service times, liability regulations, etc.)
License, customization and implementation costs

An objective evaluation means that the (a) manner, (b) the evaluation instruments and (c) the evaluation compression into a recommendation are determined in advance (“ex-ante”) and applied equally to all software options – i.e. unbiased (without “bias”).

An efficient evaluation ensures that internal resources are used as productively as possible when evaluating pricing tool options. Efficiency in the evaluation is ensured (a) by a step-by-step prioritization in the evaluation process and (b) by the introduction of the relevant project assets by an experienced expert.

In the course of a career in price management of a company, pricing managers introduce one or two pricing systems. Often it is the first selection ever or the second introduction in a long time. This experience gap can be effectively bridged by external support and the selection project can be accelerated in terms of content and time.

The Price Management Institute has developed a proven selection methodology for this purpose and implemented it in several practical projects: The PMI Pricing Software Roadmap® provides a systematic approach that implements pricing software projects with low risk and profitably. The proven methodology includes all the necessary deliverables, which include the experience and learnings from more than a dozen projects on software selection and implementation and can be used at short notice.

If you would like to get to know our approach, please arrange a meeting with us.

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