In recent years, Kiwify<\/strong> has become one of the leading platforms for those who want to sell infoproducts<\/a> in Brazil, as it brings together in one place resources for hosting, payments, membership area, and affiliate management.<\/p>\n However, as sales increase, a common challenge arises: how to scale results without solely relying on investing more in ads.<\/p>\n The answer lies in data analysis. After all, sustainable growth means understanding not only how many sales occurred but also which campaigns attract the best customers, where users abandon the funnel, and which stages limit business growth.<\/p>\n Therefore, throughout this article, you will understand how Kiwify works, what metrics it offers, and how to connect traffic and sales funnel data to make more strategic decisions.<\/strong> Stay tuned.<\/p>\n But before understanding how to use data to scale sales, it’s worth knowing more about Kiwify’s role in this operation.<\/p>\n The platform was developed to centralize the commercialization of digital products,<\/a> allowing the sale of online courses, mentoring, ebooks, paid communities, and subscriptions without the need to create a proprietary payment or content delivery structure.<\/p>\n Moreover, it brings together resources such as<\/p>\n In practice, this centralization simplifies the routine of those who work with infoproducts <\/strong>and reduces the need to use multiple tools daily.<\/strong><\/p>\n However, when the goal is to scale the operation, just tracking the data available on the platform is no longer enough.<\/p>\n In reality, it’s necessary to broaden the analysis to understand how traffic and the entire sales funnel influence these results.<\/p>\n As part of its management process, the platform provides various Kiwify metrics that help track sales performance. Among the main ones are:<\/p>\n\n On their own, these data provide a good overview of operating results and allow tracking of their evolution over time.<\/p>\n However, they mainly show what happened after the sale.<\/p>\n In other words, they help understand how much was sold but still leave some important questions unanswered, as we will see next.<\/p>\n Despite offering a good view of commercial operations, Kiwify still does not provide a complete analysis of the sales funnel.<\/p>\n For example, with the data available on the dashboard, it is not always possible to identify<\/p>\n This makes it more difficult to know if poor performance is related to ad segmentation, sales page, checkout, or traffic quality.<\/p>\n In other words, the platform shows the final result of sales but does not reveal the entire journey taken by the client.<\/strong><\/p>\n Therefore, to gain this insight, it is necessary to integrate information from other tools and analyze the journey from the first click to the conversion.<\/p>\n As previously mentioned, analyzing only the sales volume or visitors can lead to incorrect conclusions.<\/p>\n After all, increasing media investment does not always result in more clients.<\/strong><\/p>\n For example, imagine a campaign that doubles the number of accesses to the sales page but attracts a poorly qualified audience.<\/p>\n Even with more visitors, the conversion rate may drop, and the revenue may grow much less than expected.<\/p>\n Now consider the opposite scenario: maintaining practically the same traffic volume, the company optimizes the sales page, reduces abandonment at checkout, and improves conversion.<\/p>\n In this case, it is possible to increase revenue without necessarily increasing the advertising budget.<\/p>\n This happens because growth depends not only on the number of visitors but also on the quality of traffic and the efficiency of each stage of the sales funnel.<\/strong><\/p>\n And it is precisely in this context that funnel analysis makes all the difference.<\/p>\n\n Although the customer journey can vary from one business to another, it typically goes through stages such as clicking on the ad, accessing the sales page, entering the checkout, and completing the purchase.<\/p>\n In some cases, there are still later stages such as upsells and recurrence.<\/p>\n Thus, tracking the performance of each of these stages makes it much easier to identify which points truly limit sales growth, as we will see next.<\/p>\n To begin with, if a campaign generates many clicks but few visitors truly interested in advancing in the journey, it is a sign that there is a misalignment right at the beginning of the funnel.<\/strong><\/p>\n For example, the problem may lie in factors such as audience segmentation or the message used in the ads.<\/p>\n As a consequence, the investment increases, but only a small portion of users arrive at the page with real purchase intent.<\/p>\n On the other hand, when the sales page receives a good volume of accesses, but few users proceed to checkout, the bottleneck probably lies in the offer itself.<\/strong><\/p>\n In these cases, it is worth evaluating aspects such as the clarity of the value proposition, copy, social proofs,<\/a> page structure, and navigation experience.<\/p>\n Finally, even when sales increase, this does not mean that the operation is actually more profitable.<\/strong><\/p>\n After all, a low average ticket, the absence of upsells, high refund rates, or low profitability campaigns can compromise financial results.<\/p>\n Therefore, analyzing only the number of sales can lead to incorrect conclusions about the business’s performance.<\/p>\n After identifying possible funnel bottlenecks, the next step is to connect the different data sources to understand what really happens at each stage of the journey.<\/p>\n After all, a more strategic digital sales analysis depends on the integration of this information.<\/p>\n For example, while Meta Ads shows the performance of campaigns and audiences, Google Ads<\/a> helps understand users’ search intent.<\/p>\n Kiwify records who effectively completed the purchase, while Analytics tools complement the analysis of behavior within the pages.<\/p>\n Individually, each platform offers only part of the story.<\/p>\n However, when these data are brought together, it becomes possible to visualize the entire customer journey, identify which campaigns generate more results, channels that convert better, and where there are opportunities to optimize the funnel.<\/p>\n Even with data from different platforms gathered, it is important to track the most relevant indicators at each stage of the journey.<\/p>\n\n This is because each phase requires different metrics to show where optimization opportunities lie, as we will see below.<\/p>\n When these metrics are analyzed together, it becomes much easier to understand which adjustments can create more impact and direct investments towards actions that truly drive growth.<\/p>\n However, for all these indicators to be truly useful, reliable tracking is indispensable.<\/p>\n After all, the quality of the analysis directly depends on the quality of the data collected.<\/p>\n In this context, UTMs<\/a> play a fundamental role, as they are parameters added to campaign links to identify exactly where the accesses came from.<\/p>\n This allows them to relate each visit and sale to the responsible ad, campaign, or channel.<\/strong><\/p>\n On the other hand, errors like launching campaigns without UTMs, using inconsistent names, or not following a tracking standard compromise the attribution of results.<\/p>\n Thus, even the most complete dashboards start to present a partial view of the operation.<\/p>\n Therefore, before analyzing any metric, it is essential to ensure that data collection is carried out consistently and organized.<\/p>\n Finally, after structuring a good tracking process, the challenge becomes transforming all these data into information that is easy to analyze.<\/p>\n\n This is because as the operation grows, switching between Meta Ads, Google Ads, Kiwify, and other platforms becomes increasingly laborious, besides making it difficult to identify trends and bottlenecks.<\/p>\nExecutive Summary<\/h3>\n
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What is Kiwify and how does it work for infoproduct creators?<\/h2>\n
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What data does Kiwify offer to track sales?<\/h3>\n
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What Kiwify doesn’t show about the funnel’s performance<\/h3>\n
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Why increasing traffic doesn’t always mean selling more<\/h2>\n
How the funnel reveals where money is being lost<\/h3>\n
1. Many clicks and few qualified visits<\/h4>\n
2. Many visits and few checkouts<\/h4>\n
3. Many sales and little revenue<\/h4>\n
How to connect traffic data with Kiwify’s results<\/h2>\n
Which metrics to track at each stage of the funnel<\/h3>\n
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\n Funnel Stage<\/strong><\/td>\n What to analyze<\/strong><\/td>\n Key metrics<\/strong><\/td>\n<\/tr>\n \n Acquisition<\/strong><\/td>\n Evaluate the efficiency of the campaigns and the ability to attract the right audience.<\/td>\n CPC, CPM, CTR, reach, and frequency<\/td>\n<\/tr>\n \n Sales page<\/strong><\/td>\n Understand if the offer generates enough interest to lead the visitor to checkout.<\/td>\n Access rate, dwell time, and conversion to checkout<\/td>\n<\/tr>\n \n Checkout<\/strong><\/td>\n Identify potential barriers preventing purchase completion.<\/td>\n Abandonment rate, conversion rate, and approved payments<\/td>\n<\/tr>\n \n Sale<\/strong><\/td>\n Analyze the profitability and sustainability of the operation’s growth.<\/td>\n ROAS, CAC, average ticket, revenue, profit, and LTV when applicable<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n UTMs and tracking as the basis for reliable decisions<\/h3>\n
How Reportei helps analyze traffic and sales in one place<\/h3>\n