In order to achieve consistent growth in ecommerce you must employ a system which consistently determines the opportunities which are MOST effective at increasing revenues or reducing costs at any one point in time. This will be unique for every business and related to such areas as your development stage, expertise, available human resources, available budget for development work/marketing and so on. On the face of it this looks like a highly complex problem which is hard to juggle when working in a busy ecommerce environment. This is where the concept of a hierarchy of ecommerce metrics comes in. It serves as an indicator of performance across all zones of your business, but most importantly it shows you how all these cogs in the ecommerce machine are interrelated. This enables you to use a top down approach to find the metric which currently offers the largest opportunity for growth.
I’m going to show an example of a hierarchy I typically use when consulting for ecommerce companies.It uses a top down approach, starting with ecommerce revenue. We start with revenue because typically this is the metric ecommerce teams have easy access to through their analytics and ecommerce platforms and therefore are most focused on influencing in order to achieve growth and profitability.
We start the hierarchy by breaking down online revenue into a function of its core parts:
As you can see above, revenue is a function of Visits, Conversion Rate and Average Order Value or the total transactions multiplied by the mean of the total quantity spent on goods. These three inputs to revenue represent the only values you can influence in order to increase total online revenue gained over a specific period of time. By analysing these core inputs to revenue based on the relevant values for these metrics in your company, you can identify the best opportunities to improve performance. In order to accurately determine which metric offers the best opportunity, you must compare metrics against relevant benchmarks, brainstorm solutions to improve a particular metric, and subsequently compare the cost of implementing these solutions against the potential uplift.
Simple Metric Hierarchy for Revenue
Let me give you an example using values for a fictitious ecommerce company:
An improvement on any one of these inputs, keeping all others equal, will have a positive effect on revenue. I’ll go into more detail on each of these three inputs to show you the process I take in order to deduce which metric to target first. Increasing repeat visits from individuals who have previously visited your site can be a very cost effective way at increasing visits if you, for example, utilise email marketing effectively. However, typically, increasing visits is an expensive metric to influence, especially if you want to increase new visits as opposed to returning. For this reason I tend to analyse CR and AOV first. I compare CR against a benchmark which is related to the average price of goods on your site which rests in the 2-3% range. Generally the lower the value of your goods compared to market average for the same product, the higher your conversion rate should be because of the reduced barrier to purchase. This isn’t always the case, however it is a good guideline. AOV is a tricky metric to benchmark - I usually compare this metric against the average value of an item at a store. Let’s assume this store has an average item value of £60. Anything more than 1.5x the average item of a good I rate as performing particularly well, and anything towards 2x is exceptionally good.
As we can see from the diagram above, AOV is performing well, however CR is significantly below a stretch target of 2.5% which is appropriate for the average value of an item at this store. The potential revenue increase from improving CR to 2.5% is £18,000. Alternatively increasing AOV by 30% to £117 would only increase revenue by approximately £8,000. After bringing conversion rate up to our benchmark, it then makes sense to focus on improving visits by optimising your marketing in order to achieve ongoing growth.
Now you know which metric to focus your efforts on, you can brainstorm ways to influence that metric. To do this you expand the hierarchy from the metric that provides the biggest opportunity. Let me give an example for conversion rate.
Expanded Hierarchy for CR
This is just an example, however you can break down these individual components into metrics to analyse performance. For example for Onsite usability you would analyse metrics such as the passthrough performance on each stage of your conversion funnel. Again you should analyse all components, judge which is the best component to focus on based on the cost vs. potential reward, followed by a brainstorm of ideas to improve that metric/component.
This is a very effective way for continually finding the biggest growth opportunities for an ecommerce store. If you have any questions please feel free to comment below and I'll get back to you.