Competitor Prices: Which Products Should You Really Keep an Eye On?

The classic mistake: trying to keep track of everything

The first reaction of a pricing team that adopts a price-tracking tool is almost always the same: to maximize coverage. Monitor 100% of the product catalog, across as many competitors as possible, at the highest possible frequency. The intention is commendable—to leave nothing out—but it’s based on a false assumption: that all SKUs carry the same weight in the customer’s purchasing decision, and therefore in the retailer’s price image.

This isn't true anywhere. In any retail catalog, the contribution of individual products to the perception of price competitiveness follows a highly uneven distribution, not a flat curve. A handful of products account for the bulk of the effect; the majority of the catalog has very little impact—regardless of the source used to produce this data, whether automated scraping, field surveys, or panels (see “Scraping, Field Surveys, and Panelists: What Are the Differences?”).

There are two direct consequences. First, comprehensive coverage is unattainable while maintaining a consistent level of quality: the broader the scope of monitoring, the more burdensome it becomes to maintain product matching, ensure the robustness of bots against anti-bot protections, and perform human verification of discrepancies—to the point where the collected data becomes too voluminous to verify, and thus too unreliable to act upon. Second, it becomes useless beyond a certain threshold: adding references with low impact on perception or margin does not change the final decision, but dilutes the teams’ focus on the discrepancies that truly matter.

So the question isn't "How many competitors and products can I track?" but "Which products, if their prices go out of line, actually affect my bottom line or the price image perceived by the customer?" That is the whole purpose of this guide.

The KVI concept: the handful of products that define the price image

Since the 1990s, retail pricing has had a specific term for this small group of products: the KVI, short for Key Value Item —literally, “key value item.” A KVI is a product that customers notice, whose price they effortlessly remember, and which they use—consciously or unconsciously—as an indicator to judge whether a store is “expensive” or “a good deal.” In the food retail sector, these are typically products with high purchase frequency and high brand recognition—a carton of milk, a stick of butter, or a can of soda from a leading brand. In other sectors, the equivalent still exists: a loss leader whose price serves as a mental shortcut for judging the rest of the product lineup.

The key point is that what customers remember about a retailer’s prices is not based on its entire catalog, but on this handful of items. In this regard, McKinsey distinguishes between KVCs (key value categories)—categories whose prices are particularly closely scrutinized—and KVIs, which are the most visible individual items within those categories.

This focus has direct implications for price monitoring: a system that tracks a KPI and a category benchmark with the same reporting frequency and the same alert threshold wastes its data-collection capacity where the stakes are low and underinvests where they are high. The KPI is not just a marketing concept—it is a principle for allocating monitoring resources.

How to Identify Your Own KPIs: A Four-Criterion Method

KVI is neither a fixed nor a universal category: what serves as a benchmark for a discount retailer does not necessarily serve as a benchmark for a premium specialty retailer, and what matters to a grocery chain does not carry the same weight for a home improvement or appliance retailer. There is therefore no pre-established list of KVI metrics to simply copy and paste—but four interrelated criteria allow them to be identified systematically rather than based on instinct.

None of these four criteria, taken in isolation, is sufficient to identify a KVI. An item with a high purchase frequency but that is rarely compared online (such as a convenience item bought on impulse) is not a KVI. A product that is frequently compared but purchased only once every two years (such as a small appliance) is also not a KVI, just as a recurring purchase is not. It is the combination of all four signals—not just one of them—that must guide the selection, category by category.

In practice, a senior pricing team can build this list by combining data already available internally (purchase frequency and turnover from point-of-sale data, elasticity already measured from past campaigns) with external data that is less frequently used (product presence rate on price comparison sites, search volume for the product name). It is precisely the integration of these two types of data that distinguishes an actual KVI list from a hypothetical one—and that subsequently informs a comprehensive competitor price monitoring strategy, going beyond the mere identification of KVIs.

Beyond the KVI: High-Margin Products

Limiting ourselves to KVI would be a mistake just as serious as monitoring everything. A second group of benchmarks deserves equally serious attention, for a different reason: not because customers compare them, but because an uncontrolled price discrepancy in this area has a direct and significant impact on the retailer’s margin—without this ever being reflected in price perception.

This figure illustrates a structural imbalance: the product categories that drive the price image are not the ones that drive profitability. A high-margin product with low customer visibility but significant volume (a technical product line, a high-value-added accessory, or a strategically positioned private-label item) may warrant monitoring as closely as a KPI—not to align with the market, but to detect any deviations that would silently erode profits. This is a common blind spot in monitoring systems built solely around the KPI framework: they protect price image but leave margins unprotected.

The pressure on retailer margins observed in recent years in Europe (Bain & Company) makes this trade-off all the more urgent: when margins are structurally tightening, every high-stakes product line with poor profitability oversight weighs proportionally more heavily on the bottom line. Mindlessly aligning prices with those of a competitor for this type of product—without discernment—can actually undermine the overall price image rather than support it—a risk detailed in “How to Monitor Your Competitors Without Damaging Your Price Image.”

What You Can Leave on Low Power Mode—and Why It's Not Laziness

At the other end of the spectrum, a large portion of the catalog can be monitored less frequently—or even excluded from active automated monitoring—without significant risk. These are items with a low purchase frequency, rarely or never compared with competitors, and with low price elasticity: customers buy them regardless of a price difference of a few percent compared to competitors, because other factors (habit, availability, convenience) drive their decision.

Deciding to keep this long tail on low-priority monitoring is not a failure: it is a strategic choice regarding the allocation of data collection resources and human attention, just as a company chooses to focus its sales efforts on its priority accounts without abandoning the others. The difference between a mature pricing team and a team that is simply at the mercy of its monitoring system lies precisely here: the former explicitly chooses to ignore part of the catalog, while the latter does so by default, simply because it has never asked the question.

This does not mean that no monitoring is needed in this area: an occasional survey, conducted monthly or quarterly, is sufficient to detect a structural deviation without tying up the data collection capacity reserved for priority segments.

Segmenting the catalog into four levels of monitoring

In practice, these three factors—price image, margin considerations, and low stakes—combine to form a four-tier segmentation model that fits on a single page and serves as a common reference point for both the category management and pricing teams.

To put it this way: this segmentation is by no means arbitrary—each level corresponds to a distinct reason for monitoring (or not monitoring). The “showcase” KVI is monitored for price image; the “strategic margin” is monitored for profit; the “standard volume” is monitored to prevent silent deviations on high-traffic SKUs; the long tail is monitored at a minimum to ensure nothing exceptional is overlooked. Once this framework is established, it becomes the direct input for configuring the data collection system—frequency, alert thresholds, level of human verification—rather than a uniform setting blindly applied across the entire catalog.

Reviewing your KVI list: a periodic exercise, not a one-time task

A KVI is not a permanent characteristic of a product. It evolves with changes in consumer behavior, the entry of new competitors into the market, shifts in purchasing habits (the rise of curbside pickup, a shift toward private-label brands), or simply the product’s own life cycle. A product that was a KVI three years ago may have lost that status without anyone in the organization noticing—because the initial list was never revised, but merely copied from one season to the next.

This is one of the most common methodological criticisms leveled at market monitoring systems that are otherwise technically sound: the initial segmentation was accurate, the survey frequency was well calibrated, and the product matching was reliable—but the reference list has not been reviewed since its creation. A best practice is to review the list of KPIs and the associated segmentation at least once a year, and whenever there is a significant market signal (such as the entry of a new, price-aggressive competitor or a change in purchasing behavior detected in internal data).

It is this discipline of prioritization—which is continuously assessed and revised over time rather than set in stone when the system is first implemented—that distinguishes a proactively managed price monitoring system from a reactive one. Learn how Booper structures this approach on our price tracking & web scraping page.

Frequently Asked Questions

Answers to the most frequently asked questions about selecting products to monitor in light of the competition.

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Also in this series

• Web scraping, field audits, consumer panels: what are the differences?
• How to build a competitor price monitoring strategy
• How to Monitor Your Competitors Without Damaging Your Price Image

Sources: McKinsey & Company, “How Retailers Can Improve Price Perception—Profitably,” November 8, 2016 · NielsenIQ, “NielsenIQ Unveils the 2024 Economic Review and 2025 Outlook for Retail and Consumer Goods,” February 11, 2025 · Bain & Company, “Beyond the Tail: How a Strategic Approach to Simplification Fuels Growth.”