Skip to content

4 Ecommerce KPI's You Probably Aren’t Tracking Correctly


DALL·E 2024-02-22 21.54.48 - Create a 3D vector-style horizontal image representing ecommerce analytics, featuring analytics symbols like graphs, charts, and numerical data promin


In the constantly changing ecommerce landscape understanding and leveraging the right Key Performance Indicators (KPIs) can be the difference between being a market leader or simply surviving. 

For scaling brands, the complexity of operations requires a nuanced approach to analytics. One that goes beyond the standard metrics that many businesses track. These overlooked metrics provide much needed insights into profitability, customer value, operational efficiency and marketing effectiveness. 

This articles explores four such KPIs, shedding light on their importance and utility for high-achieving ecommerce brands.

Percentage (%) of Unprofitable Orders

A common oversight in the ecommerce sphere is the failure to accurately assess the profitability of individual orders, especially when it comes to factoring in the nuances of geography and product characteristics. 

Most retailers rely on SKU-level profitability analysis, which can mask the reality that a significant portion of orders may actually be unprofitable. This is particularly true for orders fulfilled from distribution centers located near coastlines or for items that are bulky and heavy, where shipping costs can drastically erode margins.

The issue isn’t just identifying these unprofitable orders but understanding the systemic patterns that contribute to this lack of profitability. For example, if a retailer ships out of a distribution center close to the coast, they might find that orders to remote inland areas are consistently unprofitable due to higher shipping costs. Similarly, selling bulky items might seem profitable on a per-SKU basis, but when shipping costs are factored in, the overall order might result in a loss.

Addressing this requires a strategic approach to logistics and pricing. Retailers need to utilise advanced analytics to dissect their order data, identifying not just which SKUs are profitable, but which orders as a whole contribute positively to the bottom line. 

This might involve reevaluating shipping strategies, such as considering distributed warehousing to reduce shipping distances and costs or adjusting pricing models for certain geographies / product categories to better reflect the true cost of fulfillment.

Leveraging technology solutions can automate most of this analysis, allowing retailers to adjust their strategies based on real-time data. Tools that integrate with ecommerce platforms and logistics providers can offer insights into the profitability of orders at the point of sale, allowing for immediate adjustments to shipping options or pricing as necessary.

By shifting focus from SKU-level profitability to a more holistic view of order profitability, ecommerce brands can significantly enhance their financial health. This approach not only identifies areas of loss but also opens opportunities for optimization, whether through operational adjustments, pricing strategies, or targeted marketing efforts to promote more profitable products or regions.

Lifetime Value (LTV)

The concept of Lifetime Value (LTV) is essential in ecommerce, yet its potential is often not fully realized due to static and outdated measurement practices. While numerous tools and applications offer sophisticated calculations of LTV, the real challenge lies in capturing its dynamism and the evolving nature of customer value. 

A static snapshot of LTV, such as an 18-month look-back period, often fails to reveal shifting trends in customer behavior, especially in scenarios where recent acquisition strategies have heavily leaned on promotions, inadvertently attracting lower-value customers.

The essence of LTV goes beyond calculation, it requires an agile and detailed approach to analysis. For instance, brands that measure LTV based on recent 90-day cohorts gain the agility to detect and respond to adverse trends before they inflict long-term damage. This real-time insight into LTV allows brands to pivot away from strategies that erode value, such as unsustainable discounting practices, and toward initiatives that enhance customer satisfaction and retention.

Implementing a more dynamic approach to LTV involves leveraging advanced analytical tools that can dissect data at a granular cohort level, providing a clear view of how customer value shifts over time. Brands should focus on integrating systems that allow for the segmentation of customers based on their acquisition source, purchase behavior, and engagement patterns, enabling a more targeted and effective optimization strategy.

Optimizing LTV isn’t just about adjusting marketing tactics, it encompasses the entire customer experience - from personalized product recommendations to tailored communication and loyalty programs, every touchpoint with the customer is an opportunity to enhance value. 

Tools like stand out in this domain, offering the ability to market to each customer on an individual basis via email or sms, taking into account their individual locations, needs, purchase history and prior feedback. This helps brands not only understand but also actively influence the factors that drive LTV.

Contribution Margin

The ecommerce landscape is constantly discussing Gross Margin Percentage (GM%) but a deeper, more telling metric isn't as often mentioned - Contribution Margin. A relatively newer insight in the Direct-to-Consumer (DTC) Twitter sphere, this metric shows the true health of a brand beyond the veil of traditional gross margins. 

The analogy is stark yet fitting - for an omnichannel retailer, leaning on EBITDAR (Earnings Before Interest, Taxes, Depreciation, Amortization, and Rent) neglects the weight of rent, similar to an ecommerce brand overlooking marketing costs in its profit calculations. These costs, similar to rent for a brick-and-mortar store, are indispensable as without them sales channels dry up.

The fact of the matter is that reporting on GM% without accounting for the cost of customer acquisition paints an incomplete picture of brand vitality. Optimizing for GM% alone is like navigating with a compass that points to true north only in theory - in practice, it disregards the unstable seas of marketing expenses that can swiftly erode profitability.

Brands going from $5M to $50M in revenue are now pivoting towards a more holistic view, integrating Contribution Margin into their financial playbook. This metric deducts variable costs directly related to product production and sales (including marketing spend) from revenue, offering a clear view of each dollar's journey through the business. 

Yet, acknowledging the importance of Contribution Margin is only the first step. The real challenge (and opportunity) is in leveraging this for strategic decision making. Tools that offer granular data on marketing spend effectiveness, product cost breakdowns and operational expenses become invaluable, allowing brands to identify not just profitable products but profitable practices, shifting the focus from top-line growth to sustainable profitability.

Given the constraints and the nature of the previous requests, I'll proceed with crafting content for the fourth point based on the established guidelines and sophistication level.

Cost per Incremental Customer

In digital marketing, Return On Ad Spend (ROAS) is often held as the gold standard for measuring campaign success. However, this metric can sometimes hide more than it reveals, especially for ecommerce brands in the $5M+ revenue bracket aiming for precision in their growth strategies. 

The heart of the issue lies in ROAS's tendency to aggregate data, potentially masking the true efficiency of incremental ad spend. For example, while a campaign might boast an overall ROAS of 4x, the return on incremental spend (an important measure of marginal efficiency) might remain at just 2x.

This discrepancy underscores the necessity for a more nuanced approach to evaluating marketing investments. The Cost per Incremental Customer metric stands out as a sophisticated alternative, focusing on the additional cost incurred to acquire each new customer beyond the existing base. This lens offers a clearer view of the marginal effectiveness of marketing efforts, distinguishing between the sustenance of current customer engagement levels and the genuine expansion of the customer base.

To navigate this, brands need to adopt analytical tools capable of dissecting campaign performance with detailed precision and analytics. Platforms like Measured provide useful insights into the incremental impact of advertising spend, allowing brands to differentiate between maintenance of the status quo and true growth activities. Furthermore, integrating customer relationship management (CRM) systems with advanced analytics can enhance this differentiation, enabling brands to monitor new customer acquisitions in real-time and adjust their strategies accordingly.

However, the analysis shouldn't just stop at a macro level. A strong approach to tracking the Cost per Incremental Customer also involves a micro-level examination - assessing daily new customer acquisitions relative to ad spend. 

This ground-level view, complemented by more sophisticated analytical tools, equip brands with the insights that are needed to fine-tune their marketing approaches, make sure that each dollar spent is an investment toward profitable growth, not just an expense against existing revenues.