Traditional Analytics Tools for eCommerce can’t include Each and Every Metric
Number of sessions, total sales, number of transactions, competitor pricing, clicks by search query, cart abandonment rate, total cart value…the analytics tools commonly used by eCommerce companies for performance monitoring can’t include every metric, and even if they did the analysts using them wouldn’t be able to keep up with the amounts of changing data. This of course, inevitably leads to overlooked business incidents and lost revenue whenever these tools are used in the fast-paced world of eCommerce.
In eCommerce, minutes matter. Your infrastructure and your competitors’ ad bidding strategies can change in an instant. Any metric can signal an important business incident. When these tools are the foundation of your performance monitoring and business, incident detection doesn’t occur anywhere near the speed of business, so your analysts can spend less time analyzing and more time head-scratching.
The need to go granular with performance monitoring
Traditional analytics tools like KPI dashboards and lists fall flat on their face when it comes to performance monitoring in the fast-paced, multi-faceted world of eCommerce. These tools take a high-level approach that tries to simplify the complex through generalization, causing BI teams to overlook plenty of metrics for eCommerce analytics. This is a design flaw since even though those tools may automate reporting and visualization, they still require humans to manually monitor the visualized data and spot the anomalies which point to business incidents. Many interesting things can happen in the metrics you’re not monitoring, leading you to miss things completely or discover them too late after the financial and reputation damage is already done. Also, missing just one of a metric’s many dimensions can cause you to miss significant business incidents.
Think of metrics as the general kind of quantity and dimensions as the specific slices of that data (e.g. daily sales per brand, daily sales per browser). In effect, monitoring each dimension multiplies the number of metrics that could be monitored, easily resulting in far too many ecommerce analytics metrics for a single person, or even a team, to constantly monitor.
A performance monitoring horror story
To illustrate why etailers need to take this granular approach to performance monitoring, consider an eCommerce company that sells physical goods in the US. Like many online retailers, this one accepts a wide variety of payment options, from PayPal and credit cards to e-wallets like Google Wallet and Apple Pay. The etailer’s BI team notices on their dashboard that the total daily revenue dropped very slightly. The almost imperceptible dip in this high-level KPI gets passed over by the analysts because they have about five other dashboards to monitor anyway, so they attribute it to statistical noise.
Meanwhile, a crucial payment processor has changed their API, breaking the etailer’s ability to process orders made with American Express cards, resulting in those customers abandoning their carts. Since orders with AMEX cards make up such a small portion of the total order volume for this merchant, the total daily revenue barely budges, glossing over the frustration of those AMEX cardholders.
Had this company been monitoring daily revenue, not as a single KPI, but broken out across each payment option (daily revenue from AMEX orders, daily revenue from Apple Pay orders, etc.), the sudden drastic drop in successful AMEX orders would have been obvious. Even if this team was using a reasonable static threshold on this metric (an approach which doesn’t scale, as we’ve discussed before), they would have been alerted and the team could contact the payment provider to fix their broken API or implement a workaround in their own code.
Problems like these, which impact a small subset of your target market or existing customer base occur quite often in eCommerce, and can paralyze a company’s growth.
And what if the company in our hypothetical scenario had just launched a line of premium smartphone accessories for international business travelers – the exact demographic most likely to shop with an American Express card? Good luck recovering from that misstep.
The value of real-time monitoring of every eCommerce metric
With every passing day that the problem goes undetected, lost revenue piles up and this merchant’s success in breaking into that wealthier clientele is less and less likely. Missed problems lurking in overlooked eCommerce analytics metrics can stop growth in its tracks. The only performance monitoring solution which is adequate for eCommerce is one that can monitor all the dimensions of a given metric in real-time.
By missing the crucial business incidents that can make or break eCommerce success, analytics tools that overlook many vertical-specific metrics imperil the merchants who use them. As we’ll see in the next article of this series, this is just as true in fintech as it is in eCommerce.