This step-by-step breakdown enables precise dissection of key metrics into sub-metrics, helping identify which funnel stages are driving performance changes. This article explores the waterfall approach in 3 steps: performance decomposition, the market equation, and leveraging the cascade to track performance variations.
Performance decomposition
Coming back to eCommerce funnel, let’s break down the funnel into three key stages: acquisition, conversion, and average price. The acquisition stage typically falls under the responsibility of the digital marketing team, tasked with bringing in new users. The product and experimentation teams focus on improving user conversion rates, while the product management or strategy teams oversee the average price to ensure it aligns with business objectives.
Let’s deep dive into the user acquisition to see how we can explain the origin of the variation. the User acquisition can be split by volume of user x consent rate x Engagement rate (unbounce).
To better understand variations, deeper exploration of these metrics is necessary. Each metric has its unique characteristics—dimensions—that can explain performance changes.
A drop in sessions, for instance, might be driven by changes in a specific segment, such as a decline in French users, while lower engagement rates could caused by underperformance on a platform like Facebook.
However, visualizing all dimensions simultaneously is often impractical. Traditional dashboards require either multiple tables or dropdown menus, which fail to highlight the most critical dimensions.
This is why linking the steps of a funnel together—using a structured framework—is essential. Let’s explore how the market equation can help. This method will enable us to prioritize the steps and the dimension that should be considered when you want to focus on the step that best explain your variation.
Modeling performance with the market equation
This approach provides a detailed, interconnected view of performance, enabling you to trace changes at any stage of the funnel to their overall business impact. By decomposing KPIs into smaller, actionable components, the market equation helps identify performance drivers and prioritize improvements aligned with strategic objectives.
Example Funnel: Linking KPIs to Transition Rates
Example funnel linking KPIs to transition rates
The decomposition outlined above can also be expressed mathematically, tying the main KPI to its sub-metrics. For instance, total revenue can be broken down into its contributing components, such as session count, add-to-cart rate, conversion rate, and average basket value. Each stage in this funnel integrates seamlessly into the equation, offering clarity on how shifts in one metric cascade through to the final KPI.
- A drop of 2% in the add-to-cart rate can be directly quantified in terms of its impact on total revenue, helping teams focus on specific interventions to mitigate losses.
Using this structured framework, businesses can answer critical questions like:
- What is the revenue impact of a drop in session count or conversion rate?
- How do improvements in basket value affect total sales?
Visualizing Insights with the Waterfall Chart
Once the funnel has been mathematically modeled, the results come to life through visual tools like the waterfall chart. This visualization enables teams to understand step-by-step contributions to the final KPI, providing an intuitive way to communicate findings and drive data-driven decisions.Performance variation and waterfall visualization
Understanding performance decomposition is a critical first step, but the true value lies in analyzing variations over time. While absolute performance measures provide context, tracking changes in metrics is what drives actionable insights for daily monitoring and strategic decision-making. The market equation plays a pivotal role here by precisely identifying the funnel stage where a significant variation occurred, pinpointing the root cause of performance shifts.
To bring these variations to life, the waterfall chart is an indispensable visualization tool. It combines the market equation’s decomposition with the evolution of metrics between two periods, offering a detailed, step-by-step breakdown of how sub-metrics contribute to overall performance changes. By visualizing the chain of impacts, the waterfall chart makes it easier to trace performance fluctuations back to specific metrics, uncovering actionable insights.
To build an effective waterfall chart, it is essential to integrate the right data:
- Primary KPIs: High-level metrics such as revenue, conversions, or leads that reflect overall business performance.
- Sub-metrics: Granular metrics like average price, margin rate, or click-through rate, which explain fluctuations in the primary KPIs.
- Explanatory Dimensions: Contextual factors such as country, customer type, or acquisition channel that provide deeper insights into the variations.
The power of the waterfall chart lies in its ability to simplify complexity. By automating the identification of metric variations across periods, it highlights which changes have the most significant impact on performance. This visualization not only reveals where performance gains or losses occurred but also prioritizes areas requiring immediate attention. For example:
- A sudden drop in conversions might be linked to a specific acquisition channel.
- An increase in revenue could be driven by a rise in average price within a particular customer segment.
By clearly illustrating the progression from sub-metrics to the overall KPI, the waterfall chart ensures teams focus their efforts on the most impactful levers. This results in a more targeted approach to performance management, enabling rapid responses to negative trends and strategic reinforcement of positive ones.
Ultimately, the combination of the market equation and the waterfall chart empowers decision-makers to not only measure what has changed but to understand why it changed—bridging the gap between data and action.
Deep-Dive into Waterfall Dimensions
Beyond providing a high-level view of performance changes, the waterfall chart allows for a deep-dive analysis into the performance of explanatory dimensions. By recalculating the impact of each element within a given dimension (e.g., countries, customer types, or acquisition channels), it becomes possible to identify the dimension with the most significant contribution to the variation. This analysis pinpoints specific elements within the dimension that have experienced notable changes, guiding where to focus corrective or optimization efforts.
For instance, if a decline in revenue is traced back to a drop in the “add-to-cart” rate, a deeper analysis might reveal that the “country” dimension is particularly relevant. Within this dimension, the data could show that France experienced a stronger decline than other countries, suggesting this specific market is driving the trend. By identifying the dimension and elements that deviate most significantly, you can focus your efforts where they are most likely to get impactful results.
Conclusion: Waterfall & market equation are essential tools for decision-making and optimization
The combination of the waterfall chart, the market equation, and the advanced waterfall features creates a robust framework for performance analysis. By systematically breaking down variations at each stage and linking them to strategic objectives, this approach transforms data into actionable insights. It not only highlights where and why variations occur but also identifies the most impactful levers to drive optimization, empowering you to make smarter, faster decisions.
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