PIM or a dedicated pricing solution: Who really decides your prices?
A PIM can store, enrich, and distribute a price. It generally cannot determine whether that price is the right one: price elasticity, competition, cannibalization, and impact simulation fall outside its scope.
The two tools complement each other rather than replace one another: the PIM ensures the reliability of product data, while a dedicated pricing solution transforms that data into simulated, governed pricing decisions.
This decision-making governance is what BOOPER's " Operational Pricing Consulting " module provides: ensuring that the right people approve the right things, beyond simply calculating prices.
When a company implements a PIM, the question almost always comes up: Should it use the PIM’s pricing module, or invest in a specialized solution? On paper, the choice seems simple—the PIM already centralizes product data, and some vendors add pricing rules and multichannel distribution capabilities.
This guide explains why managing prices and setting prices are two distinct tasks, in which cases a PIM's pricing module is sufficient, and when a dedicated pricing solution becomes necessary.
Two roles that are often confused: setting a price and deciding on a price
On paper, the choice seems simple. The PIM already centralizes product data. Some vendors add calculation rules, price updates, and distribution to various channels. Why add a new solution?
Because managing prices and optimizing a pricing strategy are two different tasks. A PIM typically stores, enriches, and distributes prices. A dedicated pricing solution must determine which price to apply to which product, for which customer, in which store, and what impact that will have on margin, volume, and competitiveness.
The difference, therefore, does not lie in the presence of a “price” field. It lies in the depth of the decision that sets it.
What a PIM Does Well
A PIM plays a critical role: building a reliable, shared product repository. In particular, it centralizes descriptions, technical specifications, images, dimensions and packaging details, categories and attributes, regulatory information, and the data required for omnichannel distribution.
Some PIMs go a step further and allow you to store multiple prices, apply multipliers, or calculate a selling price based on a purchase price—enough to cover basic needs: a margin multiplier by product family, currency conversion, multiple pricing grids, distribution to an e-commerce site or marketplace, and a few fixed rules based on the channel or customer profile.
These functions remain focused on data management and flow. They address the question, “How do we calculate and distribute a price according to a defined rule?” but do little to answer the question that really matters:Does this rule actually produce the best possible price? For a broader definition of what a pricing tool encompasses, see our article “What Is a Pricing Tool?”
In fact, the PIM market is evolving toward Product Experience Management (PXM), content enrichment, personalization, and omnichannel distribution. However, pricing optimization (elasticity, simulation, recommendations) has never been part of the historical scope of a PIM, regardless of what it is called today.
A dedicated solution turns data into decisions
A pricing solution does more than just execute a rule. It helps the company define, simulate, and optimize its pricing strategy based on data that a PIM typically does not collect:
- History, sales, past prices and promotions, costs, and margin targets.
- Market, competitors' prices, price elasticity, cannibalization effects, seasonality.
- Internal constraints, inventory, availability, local specifics, regulatory and business constraints.
- Segmentation, store profiles, and customer profiles.
The goal is no longer simply to calculate a price based on cost. It is about identifying the price that maximizes performance across several—sometimes conflicting—objectives: margin, volume, traffic, price image, or inventory turnover. That is where the difference becomes strategic.
Applying a rule is not the same as optimizing a price
A rule such as “purchase price + 35%” is easy to implement in a PIM. But this rule does not specify:
- whether the customer will accept this price;
- if the main competitor is cheaper;
- if a price reduction would generate enough additional sales volume to offset the loss;
- if the product plays an important role in the retailer's price image;
- if that same price is consistent with the rest of the product line.
The cost-plus method establishes a framework. It does not gauge the market’s reaction. However, an increase in the “ Markup ” can reduce the margin in value terms if it leads to too sharp a decline in sales. Conversely, a targeted price reduction can boost sales volume, average basket size, and overall profitability.
This is the average increase in operating profit generated by a 1% price increase, assuming constant volume—one of the most powerful drivers of a company’s profitability, often surpassing an equivalent gain in costs or volume. This leverage effect demonstrates that prices are best managed dynamically rather than using a fixed rule (McKinsey & Company, *The Power of Pricing*).
The Real Differentiator: Simulation
A PIM primarily implements a decision that has already been made. A pricing solution should allow you to test that decision before implementing it. What would happen if the company:
- raised prices by 2% for a particular category;
- lowered the prices of certain products that customers frequently compared;
- set different rates depending on geographic areas;
- protected margins on products that are less price-sensitive;
- Was it aligning certain prices with those of a specific competitor?
Simulation makes it possible to compare multiple scenarios and estimate their effects on revenue, volume, and margin. Without this capability, the company applies rules. With it, the company weighs various strategies. To learn more about this topic, our white paper on pricing strategy and AI details the method.
Complexity increases with the number of prices to manage
The difference between a PIM and a specialized solution becomes even clearer when a company needs to simultaneously manage B2B transfer prices, suggested retail prices, B2C prices, multiple brands, stores in different competitive environments, marketplaces, and regulated categories.
In this context, a single price or a set of coefficients is no longer sufficient. The company must be able to apply a common strategy while tailoring recommendations by store, region, channel, or customer, and maintain clear governance: who sets the rules, who approves the recommendations, and why a price was changed. This level of functional depth is at the heart of a pricing solution; in a PIM, it remains peripheral—if it exists at all.
This is the average percentage of planned price increases that companies actually implement; the gap is most often due to execution and monitoring, not the strategy itself (Simon-Kucher, Global Pricing Study 2025, more than 2,200 executives surveyed in 28 countries, early 2025). Without dedicated governance and monitoring, even the best pricing decision falls by the wayside.
PIM and pricing solutions: complementary, not competing
It would be a mistake to view the two solutions as completely opposed. The PIM structures product data and ensures its reliability. The pricing solution uses this data, cross-references it with sales figures, costs, competition, and external signals, and then generates recommendations.
| How that must feel | PIM | Dedicated pricing solution |
|---|---|---|
| Product Sheet (descriptions, images, attributes) | Core Business | Uses data |
| Pricing Calculation (Coefficient, Target Margin) | Often available (basic) | A starting point, not the end goal |
| Elasticity, competition, cannibalization | Absent | Core Business |
| Impact Simulation Before Application | Absent | Core Business |
| Governance and Approval Workflow | Rarely native | Native |
| Multichannel Distribution of the Final Price | Core Business | The price then passes through there |
- The PIM consolidates product characteristics and master data.
- The pricing analysis solution. Economic and business data.
- It simulates and makes recommendations. It runs through several scenarios before implementation.
- The teams approve the requests in accordance with their governance rules.
- Prices are distributed to execution systems and channels.
The PIM thus becomes a reliable source of data. The pricing solution serves as the decision-making engine.
At Booper: The PIM provides the data; GENIUS Price makes the decisions
GENIUS Price uses your product database; it does not replace it
GENIUS Price combines pricing, bill of materials, alerts, product rules, and simulations with a built-in “conversational AI” assistant. It draws on the data already consolidated by your PIM or ERP system and cross-references it with GENIUS Predict (sales forecasts, price elasticity, and cannibalization) to provide recommendations and quantify scenarios—never executing anything automatically without validation.
This is exactly the observation made by Marc Decremps, Pricing Project Manager / Transformation Department at Coopérative U (1,700+ stores, several million prices managed each year):“Our challenge wasn’t to acquire a new tool, but to improve our ability to make consistent pricing decisions on a large scale. […] The approach proposed by BOOPER won us over with its ability to balance automation, governance, and decision-making control by business teams.”
Check out the platform on our Booper page at Pricing Analytics .
A Checklist Before Making Your Choice
The right choice depends less on the number of features displayed than on the level of decision-making required.
A PIM's pricing module may be sufficient if…
- Your prices are based on a few stable coefficients, not on measured elasticity;
- you manage only a few segments, channels, or brands;
- Competitive pressure remains limited in your product categories;
- Your prices vary little from one period to the next;
- The goal is to centralize and distribute rates, not to optimize them.
A dedicated solution becomes necessary as soon as you're looking to…
- maximize your profit margin in terms of value, not just your Markup ;
- measureprice elasticity and the impact of competition;
- set different prices by store, region, or customer profile;
- simulate the impact of a decision before implementing it;
- explain and justify each rate recommendation.
Questions to Ask the Publisher—Not "Do You Set the Prices?"
- Can you recommend an optimal price, rather than applying a multiplier?
- Can you simulate its impact before it is implemented?
- Do you measure your profit margin in terms of value, volume, and revenue generated?
- Do you take into accountelasticity, competition, and cannibalization?
- Does the engine explain the factors that influence each recommendation?
- Can business teams define their constraints and approve decisions?
If the answers continue to focus on rules, workflows, and distribution, it is likely a pricing management tool, not an optimization solution.
PIM addresses an operational question: How can we ensure we have reliable product information and distribute it everywhere? A pricing solution addresses a strategic question: How can we set a price that best contributes to the company's objectives?
A price isn't just a product data point. It's a business decision that directly impacts margins, volume, competitiveness, and the brand's image. Your PIM can store it. To set it, it's best to rely on a true pricing solution.
To learn more about choosing a pricing solution, our comparison of retail pricing solutions side-by-side the leading options.
Want to know where the right balance lies for your organization? Spend 30 minutes with our team to map out your existing product framework and identify what a dedicated pricing solution would actually add to it. → Let’s schedule a meeting.
FAQ
Do you still have questions? Here are the answers to the most frequently asked questions on this topic.
A PIM (Product Information Management) system centralizes, enriches, and distributes product information, including descriptions, images, attributes, and prices. A dedicated pricing solution goes a step further: it analyzes sales history, the competition, price elasticity, and inventory levels to recommend and simulate the price that maximizes margin, volume, or competitiveness before it is applied.
Yes, most PIMs can apply a multiplier, a target margin, or a currency conversion to generate a selling price. This is a calculation, not an optimization: the rule does not measure market reaction or the impact on volume or margin value.
The two address different needs and complement each other: the PIM consolidates the product master data, while the pricing solution uses it to analyze, simulate, and recommend a price. Replacing one with the other is tantamount to confusing data reliability with decision quality.
When prices are based on a few stable factors, the company manages only a few segments or channels, competitive pressure remains limited, and the goal is simply to centralize and distribute prices rather than optimize them.
A pricing formula (such as cost plus margin) always produces the same result based on the same inputs, regardless of market conditions. A recommendation takes into account sales history, price elasticity, competition, and margin targets to suggest a price that optimizes multiple criteria at once, and can be simulated before being implemented.
Booper is not intended to replace a PIM: the platform draws on existing product databases (PIM, ERP, point-of-sale systems) and cross-references them with sales data, costs, and competitor information to generate pricing recommendations, which are simulated and validated through a governance workflow before being distributed to the execution channels.
To learn more about this topic, read our article “What Is a Pricing Tool?” To assess your needs, check out our price optimization software.
Reversibility is negotiated before the contract is signed, never after. Once the contract is signed and the system is live, the balance of power has completely shifted. Four assets are at stake: your raw data, your rule set, your trading history, and your competitive matching. Only the first is generally covered by contracts.
The gap between perception and reality is well documented: 89% of executives believe they can switch suppliers in less than a month, but among those who have tried, 58% report that the effort failed or took much longer than expected (Zapier, 2026). The goal isn’t to leave, but to have the option to do so: that’s what maintains a healthy supplier relationship throughout the contract term.
Pricing decisions account for only a small portion of the workweek in most organizations. The rest is divided among preparation, coordination, formatting, and justification. This time is not wasted: justifying a price to a buyer is real work. The problem is that it takes the place of what creates value.
The measurement is based on a reconstructed typical week, not on self-reported estimates: the discrepancy between the two is often a factor of two. The correction then follows a specific order: eliminate, then automate, then delegate. Automating a useless task is tantamount to making it permanent.
The accumulation of rules is a cumulative process, not an isolated incident: it grows with every legitimate decision made in isolation, even though no single decision is open to criticism. Five forms predominate: the exception that has become permanent; the seasonal rule that is never suspended; rules that contradict one another; the orphaned rule whose author has left; and the redundant rule.
The cost isn't what you might think: before it eats into profit margins, debt erodes trust. A team that no longer understands why the system suggests a certain price will stop following it. The solution is a consistent routine rather than a major cleanup effort every three years: a quarterly portfolio review, four questions per rule, and an expiration date set at the time of creation.