Website conversion rates are some of the most important Key Performance Indicators (KPIs) for measuring how well your internet marketing works. However, measuring conversion is daunting task, since conversion rates themselves do not tell us enough to really asses our performance adequately or benchmark our website against industry averages.
One of such problems, covered in the previous example, is that a higher conversion rate may actually be costing you money. We took a look at a real DVD sales example where 2 price points were tested. The higher price point generated a lower conversion rate (CR), but greater overall profits due to a higher margin.
In this case, looking at the CR, but not looking at overall project profitability, would lead us to making the wrong decision.
Today I want to cover one last example of CR measurement problems, before we move into actually using CR to measure and optimize your performance.
For this example, let’s take a look at a single website that’s testing two different elements to see which one generates a higher conversion rate.
|   | Element #1 | Element #2 |
| CR | 5% | 7% |
With the above numbers, we’re looking at the aggregate CR data for each element, trying to asses the one we should go with to reach the best possible results.
Not looking at any additional data, Element #2 would be the clear winner.
But in this case, the website did the test using two different traffic sources. Today we won’t look at all of the traffic source specifics, such as costs, sales, CPO or profits, but just at the implications of what using different traffic sources means for your CR.
|   | Element #1 | Element #2 |
| Total CR | 5% | 7% |
| Traffic Source #1 CR | 8% | 4% |
| Traffic Source #2 CR | 2% | 10% |
When evaluating these numbers let’s presume that both the traffic sources:
- generated an equal amount of traffic in total,
- generated an equal amount of traffic per test element,
- cost the same,
- generate the same value per converted customer.
This would of course never be the case, but adding additional data would just further complicate things at this point.
So, looking at the data, it’s clearly evident that Traffic Source #1 generates a high conversion rate for Element #1 and a lower conversion rate for Element #2, and vica verca.
When doing your online advertising, this is a very realistic scenario. Each traffic source caters to different audiences, who will react differently to your marketing messages.
In this case, each traffic source’s audience responds better to an individual test element.
Everything else being equal, this means that determining any of the two test elements in the test as a clear winner would be a big mistake, wasting you customers and money.
What’s the solution?
Quite simply, if and when your tests prove that different traffic source audiences respond differently to your different test elements, the only solution is to implement a solution that allows you to display the winning element for that traffic source to the audience that comes through the source.
Essentially, both of the test elements are winners. You need to select both.
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