Digitalizing merchandising tracking: improving field execution without adding complexity for teams

Digitalizing merchandising is often approached from an aesthetic or conceptual perspective. Major market players highlight visual merchandising, the store experience, or occasional audits, emphasizing the modernization of assets and concepts.

However, these approaches often leave aside a central topic for sales and merchandising departments: the actual monitoring of execution at the point of sale.

A merchandising plan can be perfectly designed, guidelines can be clear and shared, and digital tools may exist. If no one precisely measures what is actually applied in stores, health performance remains theoretical.

The real challenge is therefore not to "digitalize merchandising," but rather to digitalize merchandising monitoring, which means the way field teams observe, structure, and report operational reality.

The question is not a technological one, but a pragmatic one: how can we improve merchandising steering without adding to the daily workload of field teams?

In other words, how can we obtain reliable, usable, and actionable data, while respecting the time constraints and workload of sales representatives and merchandisers?

This article proposes a concrete, usage-oriented approach to understanding why digitalizing merchandising monitoring has become essential and how to succeed without complicating field execution.

Why merchandising monitoring is difficult to manage without digitalization

Merchandising monitoring is one of the most complex topics to manage within a network of points of sale, not because of a lack of methodology or commitment from teams, but because it historically relies on practices that are poorly compatible with field constraints and current management requirements.

In many organizations, merchandising data still comes from several non-homogeneous and uncontextualized data sources (free-text reports, files external to the CRM, photos taken directly on a phone or tablet, verbal feedback, etc.). Each sales representative observes the store's reality through their own lens, using their own words and priorities. The data becomes incomplete, approximate, and sometimes self-reported. This is a challenge affecting many companies: according to wasptech.com, 40% of sales teams state they spend at least one entire day per week manually entering data. It is this lack of a common framework that often prevents everyone's work from being comparable and, therefore, compared.

Added to this heterogeneity is a structural time lag. Merchandising is constantly changing: stockouts, delistings, shelf restructuring, disappearance of POS displays. When information is reported several days, or even weeks, after a visit, it loses much of its operational value. Decisions are then made based on an already obsolete snapshot of the point of sale, which heavily restricts the ability to act quickly.

These various reasons, combined with large territories, complicate the task and make sales steering difficult. Merchandising is then no longer managed based on facts, but on estimations.

Without digitalization, merchandising monitoring remains fragmented, slow, and hard to act upon.

What digitalizing merchandising monitoring actually means

Speaking about the digitalization of merchandising monitoring is not about modernizing assets or transforming the store experience. It is about neither 3D visual merchandising, interactive devices, nor digitalized marketing concepts. These approaches, widely promoted by dominant market players, primarily deal with brand image and store window displays. According to Easypicky, nearly 78% of retail companies are considering or have already adopted "merchandising 4.0" practices, integrating digital, data, and automation into their processes.

Digitalizing merchandising monitoring means tackling a much more operational issue: the way point-of-sale reality is observed, structured, and leveraged. The goal is not to "do digital," but to transform a subjective field observation into reliable, comparable, and instantly useful data.

Concretely, this means framing data collection starting from the visit. Teams no longer face open text fields or reports to write, but guided check-ins, contextualized according to the banner, store type, or the mission of the day. We no longer ask for everything, all the time, but only what is relevant in the given situation. This logic naturally reduces the workload in the field and improves the quality of the collected information.

Digitalization also allows companies to standardize without rigidifying practices. Presence, linear share, or compliance are no longer open to interpretation, but are metrics measured according to common rules.

Finally, digitalizing merchandising monitoring means automating tasks that add no value for the teams. Calculations are made in real time, store information is pre-filled, and visit summaries are automatically generated. Sales reps can focus on action and customer relations, while data becomes usable without further processing.

How to digitalize merchandising monitoring without increasing the workload in the field

Digitalizing merchandising monitoring only has value if it simplifies store visits. Whenever digitalization adds a layer of data entry, control, or reporting, it is rejected by field teams. The methodology must therefore start from the actual practices of the teams, not the theoretical needs of headquarters.

Contextualizing data collection from the moment of the visit

Not all stores, banners, and missions require the same level of monitoring. Trying to track everything, all the time, mechanically leads to field fatigue and a drop in data quality.

Effective monitoring relies on contextualized check-ins: presence checks limited only to priority products, display material control only during promotional periods, and display rack tracking only when actually installed. By tailoring questions to the context of the visit, unnecessary data entry is eliminated, and effort is focused on what truly has an operational impact.

Structuring data right from entry

Digitalization should not be limited to replacing paper with a screen. It must establish a common collection framework that is understandable and shared by all.

Presence, linear share, or compliance can no longer be subjective concepts. They are defined key performance indicators, measured according to identical rules, regardless of the sales rep or region. This structure makes data comparable without requiring extra effort from field teams.

Automating what has no added value

It is on automation that digitalization truly makes a difference. Calculations for share of shelf, presence rates, or numeric distribution must be performed automatically based on the entered data. Known store information must be pre-filled. Visit summaries must be generated without manual re-entry.

The more technology handles these repetitive acts, the more sales representatives can focus on in-store execution and relationship-building with department managers. Digitalization then becomes a time-saver, not an additional constraint.

Providing immediate feedback to field teams

A digitalized merchandising tracking system cannot be designed solely for central management. To encourage adoption, the field must experience a direct benefit.

When sales reps can instantly visualize gaps to correct, visit history, or action priorities, the data starts to make sense. Merchandising monitoring becomes a decision-support tool, naturally integrated into the visit, rather than a mere reporting exercise.

Moving forward in a progressive and pragmatic way

Finally, successful digitalization is built in phases. It is better to start with a few well-mastered indicators on a limited scope. Adjustments can then be made based on field feedback before expanding the approach to other categories or networks.

The goal is not to measure everything, but to measure what really matters for field execution.

When designed this way, digitalizing merchandising monitoring does not complicate the work of the teams. It makes it clearer, more structured, and more useful, both for the field and for commercial management.