The 5 Mistakes Retailers Should Avoid When Tracking Plant-Based and Animal-Protein Sales

Introduction

This is a useful step. It means the protein transition is moving from broad sustainability language into measurable business practice.

But measurement can create false confidence if the methodology is weak.

A retailer may believe it is tracking progress because plant-based sales are growing. It may publish a target without fully understanding its baseline. It may compare categories that are not comparable. Or it may underestimate the work required to classify thousands of products.

For ESG, data, and category teams, the challenge is not only to calculate a number. The challenge is to calculate a number that is useful, repeatable, and credible.

Here are five common mistakes retailers should avoid when tracking plant-based and animal-protein sales.

Mistake 1: Confusing Plant-Based Growth With Protein Shift

This is probably the most common mistake.

A retailer sees that plant-based sales are growing and concludes that the protein transition is moving in the right direction.

But plant-based growth and protein shift are not the same thing.

A plant-based category can grow while animal-protein sales remain stable or continue to grow. In that case, the retailer is selling more plant-based products, but the overall protein balance may not be changing much.

This distinction matters.

If a shopper buys a plant-based burger instead of a beef burger, that can contribute to substitution. But if the same shopper buys plant-based products in addition to animal-based products, the effect on the protein ratio is different.

The strategic question is not only whether plant-based sales are increasing. It is whether plant-based products are replacing animal-based protein in the basket.

This is why retailers need to track the full plant-animal protein split, not only the performance of the plant-based category.

A category manager may be happy to see double-digit growth in plant-based alternatives. But an ESG team needs to know whether this growth is large enough to affect the retailer's total protein sales.

The difference matters for climate, health, and commercial strategy. Plant-based sales growth shows category momentum. Protein-ratio movement shows whether the retailer's overall food sales are shifting.

Retailers should measure both, but they should not confuse one for the other.

Mistake 2: Measuring Assortment Instead of Sales

Another common mistake is to focus too much on the number of plant-based products listed.

Assortment matters. A retailer cannot grow plant-based sales if the offer is too narrow, hard to find, or poorly adapted to consumer needs.

But assortment is not the same as sales.

A supermarket may have many plant-based SKUs, but if those products sell in low volumes, their effect on the protein ratio will be limited. Another supermarket may have fewer products, but stronger sales in key categories such as legumes, dairy alternatives, ready meals, meat alternatives, or food-to-go.

The same logic applies to animal-based products. One meat category can represent a much larger share of protein sales than dozens of small plant-based references. A few high-volume animal-protein categories can dominate the total ratio.

This is why the strongest protein-ratio methodologies are usually sales-based.

A useful calculation should consider how much of each product was sold, the weight or volume of the product, its protein content, and whether that protein comes from plant-based or animal-based sources.

This gives a more accurate view of what customers actually buy.

For retailers, this distinction is essential. A target based only on assortment can create the illusion of progress. It may encourage teams to list more plant-based products without changing the sales mix.

A sales-based metric is more demanding. It is also more useful. It shows whether the retailer is changing consumption patterns, not only shelf availability.

Mistake 3: Underestimating Product Categorisation

The formula for a protein ratio can look simple.

Sales volume multiplied by protein content gives total protein sold. Then the retailer separates plant-based and animal-based proteins.

In practice, the difficult part is product categorisation.

Retailers sell thousands of products. Many are easy to classify. A chicken breast is animal-based. Lentils are plant-based. Tofu is plant-based. Eggs are animal-based.

Many products are more complicated.

A retailer needs clear rules for products such as beef lasagne, chicken-and-lentil salad, cheese-and-vegetable quiche, vegetarian products containing egg or milk protein, pizzas with meat and vegetables, plant-based burgers with added pea protein, biscuits containing milk powder, and ready meals with several ingredients.

These cases matter because they can influence the final result.

If a retailer classifies mixed products too broadly, the ratio can become distorted. If it ignores composite products, it may miss important parts of the food basket. If it treats all "plant-based" labelled products as fully plant-based, it may overlook animal-derived ingredients.

This is why methodologies such as the Protein Tracker and WWF's Basket Diets Metric give detailed attention to product groups, composite products, and reporting levels.

WWF's guidance, for example, distinguishes between whole food level, composite product level, and composite ingredient level. The composite ingredient level is more precise because it looks at the weight of the relevant ingredients inside the product, rather than treating the whole product as one category.

The Protein Tracker also recognises composite products as a specific challenge. Earlier versions of the methodology used grouped assumptions where product-level information was not available, while more recent updates encourage more precise product-level data where possible.

For retailers, the lesson is clear. A credible protein-ratio project needs more than data extraction. It needs a classification logic.

That means clear rules, documented assumptions, a process for edge cases, and quality control.

Without this, the final number may look precise, but the underlying classification may be weak.

Mistake 4: Ignoring Data Quality and Methodological Consistency

Protein-ratio measurement depends on data.

That sounds obvious, but it is often underestimated.

Retailers may have strong sales data, but weaker product data. Product weights may be missing. Nutrition information may be inconsistent. Ingredient lists may be hard to process. Fresh products may not follow the same data structure as packaged goods. Private-label products may be easier to analyse than national-brand products.

These issues do not make measurement impossible. But they must be documented.

A retailer should know which parts of the calculation are robust and which parts rely on assumptions.

The team should be able to answer practical questions. Was the calculation based on a full year of sales? Were online and physical-store sales both included? Were fresh products included? Were foodservice or food-to-go products included? Was protein content available at product level? How were missing values handled? How were mixed products treated? Did the scope change compared with the previous year?

These questions are technical, but they are not secondary. They determine whether the metric can be trusted.

Consistency is especially important for year-on-year reporting.

If a retailer uses one methodology in year one and another in year two, progress may become impossible to interpret. The ratio may change because sales changed. But it may also change because the classification rules, product scope, or data sources changed.

That is a serious problem if the metric is used for public commitments.

Retailers should avoid changing methodology without explanation. When a change is necessary, they should document it clearly and, where possible, restate previous results using the new method.

A protein ratio should not be treated as a one-off calculation. It should become a repeatable process.

Mistake 5: Treating Measurement as Reporting, Not Action

The final mistake is to stop at the number.

A retailer calculates its protein ratio, includes it in a sustainability report, and considers the work done.

But measurement is only useful if it leads to decisions.

A protein ratio should help retailers understand where to act. It should show which categories drive the current balance. It should help identify where plant-based or plant-forward options could realistically grow. It should support commercial tests and internal accountability.

Once the baseline is known, a retailer can ask better questions. Which categories contribute most to animal-protein sales? Where are plant-based alternatives already performing well? Where is the price gap too high? Where are promotions reinforcing animal-based purchases? Are plant-based products visible enough online? Are they placed where customers can compare them with animal-based equivalents?

These questions connect sustainability to category management.

That is where the protein ratio becomes valuable.

It can inform assortment decisions. It can guide promotional strategy. It can support private-label innovation. It can help e-commerce teams test recommendations. It can help leadership understand whether the company's sustainability commitments are translating into sales movement.

The goal is not to produce a polished metric. The goal is to change the business in a way that is measurable, commercially realistic, and repeatable.

What Good Measurement Looks Like

Avoiding these five mistakes does not mean retailers need a perfect system from day one.

Most retailers will need to start with imperfect data. That is normal.

The important thing is to build a method that can improve over time.

A strong first protein-ratio calculation should include a clear scope, a documented methodology, sales-based data, explicit product-categorisation rules, a treatment for composite products, a view of data quality, category-level results, and a plan to improve the calculation next year.

This gives ESG teams a credible baseline. It gives data teams a clear improvement roadmap. It gives category teams a practical starting point. And it gives leadership a better understanding of what the protein transition means for the business.

The first calculation does not need to answer every question. But it should create a foundation for better decisions.

Conclusion

Tracking plant-based and animal-protein sales is becoming an important part of retailer sustainability strategy.

But the metric is only useful if it is built carefully.

Retailers should avoid confusing plant-based growth with real protein shift. They should measure sales, not only assortment. They should take product categorisation seriously. They should document data quality and keep the methodology consistent. And they should use the results to guide action, not only reporting.

The protein transition will not be delivered by broad ambition alone. It will be delivered by retailers that can measure where they are, understand what drives the ratio, test interventions, and improve year after year.

For supermarkets, the message is simple: a credible protein ratio is not just a sustainability metric. It is a management tool.

Sources

Green Protein Alliance & ProVeg Netherlands, The Protein Tracker methodology update https://theproteintracker.com/wp-content/uploads/2026/01/2025_The-Protein-Tracker-Update-Oct-2025-Green-Protein-Alliance-Proveg.pdf

Green Protein Alliance & ProVeg Netherlands, The Protein Tracker 2023 https://theproteintracker.com/wp-content/uploads/2024/03/2023-The-Protein-Tracker-Green-Protein-Alliance-Proveg.pdf

WWF UK, WWF Basket Diets Metric Guide https://www.wwf.org.uk/sites/default/files/2024-12/diets-metric-guide.pdf

ProVeg International, Retailers urged to shift to 60% plant / 40% animal protein https://proveg.org/press-release/retailers-urged-to-shift-to-60-plant-40-animal-protein/

ProVeg International, Why protein diversification belongs on every retailer's agenda https://proveg.org/article/why-protein-diversification-belongs-on-every-retailers-agenda/