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Top 5 Questions to Ask Yourself after Cyber Monday - Part 2

In our last blog post, we discussed aesthetics, and online and mobile merchant site responsiveness. Here is the second and final half of our installment:

Did the site make as much revenue as it could have?
For many retailers, the last two months of the year are the most profitable, with a combined gross of more than nearly all the months before it. Moreover, some retailers are not profitable until the last two months of the year, hence the term "Black Friday", the day a retailer goes from red ink to black ink in their revenue ledgers. Clearly, the site needs to make as much money as possible because it had the best user experience, products, product richness, and perceived response time. How do you know if the site made as much as it could have? Do you say that it made as much as possible because there were no site outages? The old adage "you can't manage what you don't measure" applies here. You need to measure all of the key performance indicators of the web site, especially those relating to the customer. Even then, unless you know what to do with the data, you still may not know. Fortunately there are tools available, such as Blue Triangle's eRevenueView, which allow you to measure and scientifically analyze the effect of web site speed on site revenue metrics. Unless you were a statistics wizard at university, it's better to have the right tool to figure this out for you.

Did the site leak revenue for some reason? Even if it did, how would you know?

If there was additional revenue that the site could have made, but did not, it's called revenue leakage. Imagine water leaking from a pipe under a building. Unless you are looking in the right place, you may not even know it is happening. To determine if your site is leaking revenue, you must first know how much revenue the site could have made under the best possible conditions. Knowing that, you subtract actual site revenue from maximum site revenue and the delta is your revenue leakage. Sounds simple, right? Ok, ok, I agree, it actually doesn't sound simple.

To determine the maximum revenue the site could have made if it performed well and met customer expectations, you'll need to know the optimum page speed that customers want. Ignoring my personal expectations, the page speed that maximized revenue and web site cost is available. Industry analysts, as well as Google and Microsoft, will tell you that faster is better and even give examples where 100 milliseconds made a difference. It is generally true that faster is better, but only to the point of diminishing returns. If the site is any faster than necessary, you are incurring unnecessary expenses.

As an example, let's examine the graph below:

Blue Triangle Blog Post Img 1.png
Source: Blue Triangle Technologies (2014)

The violet line shown represents the conversion rates of a real-life example of an online store. The blue shaded area is the population of visitors to this merchant's site. The horizontal X-axis shows response time of shoppers. It tells us that the optimum page speed needed to support maximum revenue earned from shoppers is 2.5 seconds. It also establishes that making the site faster than 2.5 seconds will not yield additional revenue.

Since we now know the optimum page response time, we can look at the actual response time, as experienced by the example site's customers. Any shopper experiencing page load times of more than 2.1 seconds is less likely to purchase items on this shopping site than those at 2.1 seconds or faster.

Looking further, the 35th percentile of shopper performance experience is 4.1 seconds. The revenue that leaked (was lost) from this eCommerce site between 2.1 seconds and 4.1 seconds is calculated at $359,000 USD per month. What's more alarming is that, 2/3rds of this site's customers experienced page response times slower than 4.1 seconds. Imagine how much more revenue could be recovered if a higher percentage of shoppers experienced at least 4.1 seconds, even if they did not get to the 2.1 seconds target.

The goal of any business is to maximize revenue: microeconomics 101! By not calculating and ensuring optimum page response times, merchants are not realizing maximum revenue, and consequently leave lots of money on the table.

The figure below shows how Advanced Analytics (found in eRevenueView) can be used to address the problem of lost revenue as described above.

First, merchants must have the correct data paired together. (If all data points do not match the same customer, then you cannot use that data in any useful analysis of customer experience.) As it shows, one must first look at page speed and revenue metrics historically to build a baseline. Next, it's critical to examine the reasons that certain pages were slow. Based on the historical analysis of a large sample of the site's customers, a trained data engineer or a SaaS product like eRevenueView can provide the predictive analytics to demonstrate optimum page response time to maximize revenue.

Blue Triangle Blog Post Img 2.png
Source: Gartner (October 2014)

Great! Now you have the target. Plan and execute the projects to improve speed, including things like front end optimization services like Aqua Ion.

You have now moved some of the population to faster response times. Fantastic! You will now make more revenue on your online stores than you did previously, and if you used eRevenueView, you know in advance how much of that revenue you were likely to recover. What's more, you can verify that by looking at the eRevenueView dashboard on a regular basis.

The fourth area of the figure above reads, "Prescriptive." What does that mean? You should continue to measure customer experience and site revenue metrics all of the time, 24x7x365 so that you can make adjustments, tune the site as various things change; based on the ongoing predictions that eRevenueView shows you. And also implement the best, most effective infrastructure enhancements like those offered by Akamai.

The next step? Boldly tell your CIO or board that you are maximizing the web sites revenue, that it is no longer losing money-making opportunities from customers, and that you are using the best, most accurate tools to manage revenue and user expectations on a continual basis.

About Blue Triangle Technologies: The Company equips online and mobile retailers with the correlation of site abandonment rates and actual dollars lost. By analyzing variations in customer behavior with site performance, and comparing them to actual sales revenue, Blue Triangle Technologies provides critical insight into how they impact Average Sale Size and Conversions for individual eCommerce site buying events. For more information, visit www.bluetriangletech.com.

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