An analysis of the top 100 performers in each stage of the funnel, based on real data from stores on Tiendanube, Shopify, and VTEX.
Ecommerce conversion doesn't depend on a single factor. It depends on three critical stages — discovery, intent, and decision — being precisely aligned. When all three work well at the same time, the results become extraordinary.
We analyzed the behavior of the top 100 performers in each stage of the purchasing funnel, within a base of thousands of stores operating on the main platforms in Latin America and Brazil. The result is an x-ray of what an ecommerce funnel looks like when it truly works.
There are no shortcuts. But there is a pattern.
Most ecommerce analyses focus on the final conversion rate: how many of those who entered ended up buying? It's a useful metric, but misleading if looked at on its own.
A purchasing funnel has three moments of tension that matter equally:
Each stage has its own logic, its own frictions, and its own performance ceiling. Understanding them separately — and together — is what distinguishes stores that grow from those that stagnate.
These numbers correspond to the average of the top 100 in each metric. They are not generic benchmarks taken from a global report: they are data from real stores, operating in the Latin American and Brazilian market today.
The first question any ecommerce should ask is simple: do my visitors find what they are looking for?
Among the top 100 in this metric, the average rate of users who go from the site to view a product is 88.2%. The best performer recorded reaches 94.9%.
What these numbers reveal is that, in high-performance stores, the catalog is well structured, navigation generates no friction, and the traffic that arrives is qualified. There are no major leaks at the front door.
The 25th percentile of this group is at 84.6% and the median at 87.8%. The distribution is compact: among the best, there are almost no negative outliers. Whoever enters this top group already has basic navigability figured out.
This is where the real game begins.
If the first stage depends on architecture, the second depends on persuasion. Does the product page manage to convince the visitor that it is worth moving forward?
Among the top 100 in the product→cart rate, the average is 34.3%. This means that more than 1 out of 3 people who get to see a product add it to their cart. The best case recorded is 75%.
This is the stage with the most variance. The median is 30.6%, but the 75th percentile jumps to 37.2%. There are stores that clearly dominate this stage — and the gap between them and the rest of the market is huge.
The factors that drive this rate are well known but frequently poorly executed: high-quality images with multiple angles, descriptions that talk about benefits and not just features, visible social proof (reviews, ratings, units sold), real urgency (available stock, accurate shipping times), and a buy button that does not compete visually with anything else on the page.
The conversion rate is the star metric of ecommerce, and also the most misunderstood. A global average of 3% sounds low until you understand that the best in the market are at a 3.1% average within their top 100, with the best performer recording a 7.1%.
To contextualize: the average conversion of the ecommerce market in Latin America is around 1% or less. Stores in this analysis triple that number. What do they do differently?
The answer is not a single thing. It is that they have the two previous stages well resolved. A healthy funnel at the entrance (high site→product rate) plus a persuasive product page (high product→cart rate) generate a flow of qualified users who arrive at the checkout with real intent to buy.
This analysis has a deliberate limitation: it is anonymous. It is impossible to know if a jewelry store converts the same as a clothing store, or if one category is naturally easier to sell online than another. Averages collapse that heterogeneity.
But there is something the numbers do allow us to infer safely:
The funnel has physical laws. A store cannot have an exceptional final conversion if most of its visitors never get to see a product. A high product→cart rate does not make up for broken navigation. Each stage is a necessary condition for the next.
Size is not the factor. In the top 100 conversion list, stores with 10,000 visitors coexist with stores with 60,000. Scale does not guarantee efficiency: the architecture of the funnel does.
The room for improvement is huge. If the median conversion of the top 100 is 2.7%, and most of the market is below 1%, the growth space for the average store is not 10% or 20%: it is in multiples.
Before investing in traffic, ad creatives, or any type of channel, it is worth answering these questions with real data:
1. What percentage of your visitors gets to see a product? If you are below 80%, the problem is navigation or a mismatch between the traffic you bring and the catalog you show.
2. How many of those who see a product add it to the cart? If you are below 20%, the product page is the bottleneck. More traffic won't solve that problem; it will only amplify it.
3. How many of all your visitors end up buying? If this number is below 1.5%, you probably have leaks in more than one stage simultaneously.
Diagnosing the funnel is not a one-time activity. It is a continuous practice. The best ecommerce stores didn't reach those rates by accident: they got there because they measured, iterated, and optimized each stage with the same discipline.
The analysis of these 100 top performers in each stage shows something that goes against common intuition: high performance in ecommerce is not the result of an advantage in a single metric. It is the result of having no systemic weaknesses in any of them.
A site→product rate of 94% with a conversion of 0.8% is a store with very well-segmented traffic but a failing purchase process. A product→cart rate of 60% with a site→product rate of 50% is a store with an excellent product page but an impossible-to-navigate catalog.
The ecommerce that grows sustainably is the one that understands its funnel as a system — where each stage feeds the next and where weakness at any point limits the potential of all the others.
The data speaks for itself: a well-built funnel converts between 2% and 7% of total visits. The average market converts less than 1%. The difference is not in the ad budget. It is in the engineering of the purchasing process.