Your pricing strategy has already failed if all your products are treated the same
There is a question that very few companies ask themselves when they decide to review their pricing strategy, perhaps because the answer is much more uncomfortable than it seems. What role does each product actually play within the business? Most automatically respond that they all exist to be sold, generate income and contribute to profitability. The answer seems logical, even obvious. The problem is that it is also profoundly wrong.
If all products served exactly the same function, it would be enough to correctly calculate their costs, apply a target margin, and update the price list whenever expenses or inflation increased. Pricing would be a relatively straightforward exercise and could probably be solved with a well-designed spreadsheet. However, you only have to observe the behavior of any company for a few months to discover that the reality is very different. There are products that attract new customers, others that generate most of the margin, some that barely sell, but are indispensable to complete a solution, others whose main function is to prevent a competitor from winning a commercial opportunity and a few that remain in the catalog simply out of pure habit, because no one has questioned their existence for years.
The surprising thing is that, even knowing all this, the portfolio continues to be managed as if all these differences were irrelevant. When the time comes to modify prices, define discounts or launch promotions, the catalog ceases to be a set of products with different behaviors and becomes a homogeneous mass on which uniform decisions are applied. The percentage increase is the same for everyone, trade policies are practically identical and profitability expectations are based on the idea that each reference should behave in a similar way. Then the usual questions appear. Why did some price increases drastically reduce sales while others went completely unnoticed? Why do certain products generate huge volumes of turnover, but hardly contribute to the margin? Why does the competition seem to react only when we change the price of certain lines and ignore the others? The curious thing is that the answers are usually sought in the market, when many times the problem began much earlier, within the company itself.
Talking about pricing often leads the conversation to thinking about complicated algorithms, elasticity of demand, artificial intelligence, statistical models, or sophisticated price optimization platforms. All of these elements have enormous value and are part of current best practices, but none solves a conceptual error that continues to be present in organizations of all sizes. Before optimizing a price, it is necessary to understand what is being managed, and that implies accepting an idea that seems simple, although it completely changes the way decisions are made: not all products should receive the same strategy because they simply do not serve the same purpose within the business.
This is probably one of the most frequent mistakes observed in pricing projects. Not because companies lack information, but because they use the wrong information to answer the wrong question. All wrong! For years they have perfected their systems to know how much they sell, how much it costs to produce each item, what margin each transaction leaves or how many units remain in inventory. However, when asked what is the strategic function of each product within the portfolio, the answers tend to be based more on perceptions than on evidence. We talk about the "star" product, the "most important" product, the product "that has always sold well" or the product "that everyone knows", expressions that reflect commercial experience, but hardly constitute a pricing strategy.
There is a huge difference between organizing a catalog and understanding it. The first task is relatively simple because it responds to administrative criteria that everyone masters. I mean that products are classified by families, categories, lines of business or suppliers. This structure facilitates daily operation, inventory control and commercial management. Here the problem arises when that same classification begins to be used to make strategic decisions. And it is here that the company begins to assume that products belonging to the same category should also respond in a similar way to the market, when the evidence often shows the opposite.
Let's think for a moment about any supermarket. Two products may share the same aisle, serve the same need, and even belong to the same brand, but react completely differently to a price change. There are items whose value the consumer knows practically by heart because they are part of their regular purchase. A small increase is enough for them to immediately compare alternatives or decide to change brands. On the other hand, there are other products whose purchase responds more to convenience, trust or availability than to a detailed price comparison. From the perspective of the inventory, both belong to the same category. From a pricing perspective, they may require completely opposite strategies.
The same is true in industrial markets, distribution companies, manufacturers or service companies. Some products represent the entry point to build a long-term business relationship; others are responsible for capturing most of the profitability once the customer already trusts the supplier. There are references that work as volume generators, while others exist to differentiate the value proposition. Some are easily replaceable and compete almost exclusively on price; others incorporate technical attributes, service levels or specialized characteristics that considerably reduce the customer's sensitivity to variations in their economic value.
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However, it is surprising to see how many organizations continue to make decisions as if all these differences were anecdotal. We speak of "updating the price list" as if there were a single list and a single logic capable of explaining the behavior of perhaps hundreds or thousands of different products. It's a simplification that I understand because it makes administrative management easier, but it's also one of the main reasons why many pricing strategies produce inconsistent results. When everyone gets the same treatment, inevitably some products end up overpriced, others underpriced, and a few are left exactly where they should be, though more by chance than by design.
What's interesting is that this practice is rarely questioned. Over time, it becomes part of the organizational culture and begins to be perceived as a natural way of managing the business. Discussions stop revolving around the strategic function of each product and focus solely on deciding what the percentage increase will be for the following year or what level of discount the sales team can authorize. The problem is that those conversations happen too late. By that time, it has already been assumed that all products deserve the same decision logic, when precisely that premise was the one that should be questioned from the beginning.
It's hard to find a sales manager who doesn't know your business deeply. After years of negotiating with clients, visiting the market and observing the behavior of the competition, he develops an intuition that often allows him to anticipate movements with surprising accuracy. That experience is of enormous value and it would be a mistake to ignore it. The problem arises when intuition ceases to be a starting point and becomes the definitive criterion with which the entire catalog is managed.
A different version of the same conversation appears in almost every pricing project. When reviewing certain products, someone affirms with absolute certainty that this reference is strategic because it has always sold a lot. Another responds that the truly important product is the one that generates the most brand recognition. A third insists that the customer will never accept a price increase because "he has always been very sensitive." The striking thing is that, when these statements are contrasted with historical data, it is not strange to discover that several of them are partially true and others simply ceased to be valid years ago.
Business memory has an extraordinary ability to preserve success stories and an equally remarkable ability to ignore the gradual changes that occur in the market. A product that five years ago was driving growth may today be in a stage of maturity or even decline. A benchmark that was traditionally compared with numerous competitors may have developed differential advantages that considerably reduce this competitive pressure. Similarly, an item that for years was considered secondary may have quietly become one of the business's main margin generators. None of this is usually perceived when decisions rest solely on accumulated experience.
The consequence is predictable. Organizations end up segmenting their catalog based on individual perceptions rather than objective patterns of behavior. And when segmentation is born from opinions, the pricing strategy also ends up looking more like a collection of beliefs than a decision model. That is usually the moment when endless discussions appear to justify exceptions, special discounts or differentiated increases, when in reality the debate should focus on something much more basic and that is to understand what the data is telling us about the role that each product plays within the business.
One of the most curious side effects of digital transformation is that companies produce more and more information, but they don't necessarily make better decisions. It has never been easier to know the margin by product, the purchase frequency of each customer, inventory turnover, discount history, sales evolution or profitability by channel. However, it is enough to attend a price review meeting to see that all this information usually ends up being reduced to a handful of general indicators that explain how the business did during the last quarter, but contribute very little to decide what should happen to each product in the future.
The problem lies in the way the amount of data available is used. There is a very marked tendency to use them as diagnostic tools when they work best in guiding decisions. Companies spend time building flawless reports, increasingly sophisticated dashboards, and financial models capable of accurately describing what has already happened. The paradox is that, when defining a pricing strategy, much of that knowledge disappears and decisions are simplified again until they become general policies that affect the entire catalog equally. It is as if the wealth of information is used to understand the past, while the future continues to depend on generic rules that ignore the differences between products.
And this is where segmentation begins to take on a completely different meaning. Classifying a catalog is not about tagging products to make a presentation more attractive or to build a matrix that will end up forgotten in some shared folder. Sorting means accepting that different products require different choices. That's the only reason why it makes sense to invest time in segmenting them. If after analysis all items continue to receive the same discount policy, the same annual increase and the same commercial logic, then the ranking did not serve "a damn". They changed the labels, but it didn't change the way the business was run.
Perhaps this is why many segmentation initiatives generate a certain frustration. Weeks are spent gathering information, complex analytical models are developed, and finally a perfectly classified catalog is obtained. However, a few months later everything is still working exactly the same as before. Sellers continue to negotiate in the same way, promotions are designed with the same criteria, and price revisions continue to be discussed in terms of overall percentages. The project ends up being perceived as an interesting analytical exercise, although with little practical impact. In reality, the problem was never in the classification. It was in the fact that the organization never allowed that classification to modify the decisions it had been making for years.
Good segmentation doesn't just answer the question of how a product behaves. Rather, it responds to what the company should do as a result of that behavior. This apparently insignificant difference completely transforms the purpose of the analysis.
There is an exercise that usually produces uncomfortable results the first time a company performs it rigorously. It consists of ordering all products according to their economic contribution to the business and observing what percentage of the margin, sales or total profitability really comes from each one. What appears almost always confirms a phenomenon widely known in management, and that is that a small part of the portfolio tends to generate a disproportionately high proportion of the economic result.
This principle gave rise to one of the most widely used classification models in business management: the ABC analysis. Its logic is extraordinarily simple and that is precisely why it retains so much validity. Instead of assuming that all products have the same financial importance, it ranks them according to their contribution to the business. Products A represent those that concentrate most of the economic value; B products are of intermediate importance and C products provide a much smaller share, although they usually constitute the largest number of references within the catalogue.
The interesting thing is that many companies are perfectly familiar with the ABC model and, even so, they continue to use it only to manage inventories. Few organizations bring that logic to the pricing strategy. It is common to find companies that know what their A products are, but continue to apply exactly the same commercial policies to them as to the rest of the portfolio. In other words, they correctly identify which products sustain the business, but then act as if that information has no practical consequence.
The question then stops being how to build an ABC rating and becomes much more challenging. If a small group of products generates a large part of the company's profitability, does it make sense to manage those products exactly the same as those whose economic contribution is marginal? Should they receive the same level of competitive analysis? The same promotional policies? The same criteria for authorizing discounts? The same frequency of price revisions?
If all these questions have an affirmative answer, it implies accepting that a product capable of sustaining a significant part of the financial result deserves exactly the same level of attention as one whose contribution hardly modifies the performance of the business, nor moves the needle.
That doesn't mean that C-products are irrelevant. That's a simplistic interpretation of the model, and probably one of the reasons why some organizations end up using it incorrectly. A product with a low economic contribution can play a strategic role within the portfolio. It can make it easier to sell other referrals, strengthen the relationship with certain customers, or complete a higher-value solution. The important thing is to understand that your strategic role does not necessarily coincide with your financial contribution. Precisely for this reason, the ABC classification represents only one dimension of the analysis and not a complete explanation of the behavior of the catalog.
When used correctly, this model forces you to ask questions that rarely appear in traditional pricing meetings. Are we devoting our greatest analytical efforts to the products that really sustain the business? Are we spending time negotiating discounts on SKUs whose economic impact is virtually negligible while ignoring those where a small price improvement would have a much larger effect on profitability? These are uncomfortable questions because they show that the time of the commercial and financial teams should also be segmented.
And well, this article was too long for me, so I'm going to publish a second part that you can see here.
>> How to segment your catalog for a better pricing strategy <<