The conversion rate is one of the key indicators in e-commerce. You can calculate the conversion rate correctly by observing important distinctions and special features, which are presented in this article. First, the data required to calculate the conversion rate is named and discussed. Then, some empirical empirical results on the conversion rate are presented. Finally, you will find hints on how to achieve higher revenues with higher conversion rates.
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Contents
- Things to know about the conversion rate
- Calculating the conversion rate
- Interpret conversion rate results
- Higher earnings through higher conversion rates
- Conclusion
Things to know about the conversion rate
The conversion rate is generally defined as the proportion of page visitors who become buyers, i.e. “convert”. The background to this is a role model that assigns roles such as interested parties, users, buyers and customers for the customer journey. The conversion rate can be seen as a benchmark for the performance of the online store and onsite marketing. The conversion rate provides information on how relevant the offer in the online store is for the acquired site visitors and how effective the online store is in marketing the offer.
Conversion is the penultimate stage in the online sales funnel, it can be revised at the last stage by a return. Conversions also have a legal implication: when the customer clicks on the “Buy Now” button, he offers to conclude a contract with the seller. This is finally concluded when the seller confirms the order.
Calculate the conversion rate – the data
Since the conversion rate is a composite variable, you need two data series if you want to calculate the conversion rate. These must be defined or delimited, and a time period must be defined for which the conversion rate is to be calculated.
The denominator of the conversion rate is the number of visits that a page can have in a given period of time. In the numerator, the number of conversions is set in relation to the visits if you want to calculate the conversion rate. So you calculate the conversion rate with the following expression:
Both data series can lead to distortions in the reporting of the conversion rate due to accruals, which should definitely be taken into account.
When is a conversion recorded – and when is it not?
You face far greater challenges when you want to determine the number of conversions using an analytics tool such as Google Analytics. The following shortcomings regularly exist when you calculate the conversion rate:
- Analytics does not capture all sales channels
- Analytics does not capture returns
- Analytics does not capture partial returns
- The user has JavaScript turned off, so Analytics tracking does not work*.
Conversions in non-recorded channels
Analytics tracking also leads to a lower recorded conversion rate if conversions also occur outside the online store. In this case, the conversions are not counted because the e-commerce tracking is only set up for the online store. This could be, for example, sales on amazon marketplace or conversions made via a telephone channel.
The recording of returns
The much bigger problem, however, is likely to be returns, which are usually also taken into account in e-commerce tracking. Partial returns or even price reductions are particularly difficult, where a rule must be defined as to whether they are taken into account as a proportional conversion reduction, as an integer conversion reduction above a certain threshold, or not at all. In the case of only very small partial returns, it may be possible to disregard them, but in the case of products with a high likelihood of returns, partial returns must be taken into account if the conversion rate is to be calculated.
Calculating the conversion rate – the results
If you calculate the conversion rate and you have previously clarified all delimitations and definition questions, you will receive a ratio for a given period. The conversion rate, like most e-commerce ratios, usually fluctuates considerably, so that a single daily value is usually not very meaningful. Weekly or seasonal averages are more relevant when calculating the conversion rate.
Average conversion rate values also differ significantly between individual online stores or product categories. A survey conducted by iFH and ECC Cologne in 2013 came to the sobering conclusion that
- 43% of the companies surveyed achieve a conversion rate of less than 2%.
- only 26% of the respondents have a conversion rate of more than 2% and
- 23% of respondents do not know their conversion rate at all.
The conversion rate is a key success factor for the contribution margin, as the key figure model “The E-commerce Code” shows:
DB II = I x CTR [CR (VK – EK) – CPC]. A numerical example illustrates the leverage that exists with an improved conversion rate:
I x CTR = page visit = 10,000
VK – EK = DB I = 50 €
CPC = 0,75 €
CR1 = 3 %
CR2 = 6 %
DB II1 = 10.000 x (3 % x 50 € – 0,75 €) = 7.500 €
DB II2 = 10,000 x (6 % x 50 € – 0.75 €) = 22,500 €
With a conversion rate that is twice as high in the second scenario, contribution margin II as gross profit from e-commerce can therefore be more than doubled, since significantly higher level I contribution margins are achieved with constant marketing costs. This is a compelling reason to focus on optimizing the conversion rate.
Calculate the conversion rate – higher revenues through higher conversion rates
The economic success of an increase in the conversion rate arises from the fact that a higher number of conversions can be achieved with existing numbers of visitors or an existing number of conversions can be achieved with a lower number of visitors. However, an increase in the conversion rate alone is no guarantee for higher profits: if, on the one hand, the conversions are increased by discounts and other price reductions, but on the other hand the order values achieved – i.e. shopping baskets – are reduced, this can, under unfavorable circumstances, also lead to a reduction in the contribution margins. Conversion optimization should therefore focus primarily on increasing usability and improving the user experience. These lead to page visitors assessing the relevance of an online store more positively, being able to orient themselves better and having more trust in a retailer’s online offering.
Above all, the increasing and now dominant importance of smartphone use for e-commerce is leading to new challenges in conversion optimization. High loading times, usability problems and regular sideline use reduce conversion rates in mobile use and thus sales for retailers. A proactive approach to mobile online store processes is required. These require rethinking and building skills in user experience design. Fortunately, there are already many best practices.
Conclusion
The conversion rate is not only an important but also a complex key figure in e-commerce. In WebAnalysis, a large number of specifics have to be taken into account when calculating the conversion rate. Even increasing the conversion rate does not always lead to success. Therefore, an intensive examination not only of the conversion rate as a key figure but also and above all of the conversion process is an important prerequisite for success in e-commerce.
Author: Dominik Große Holtforth
* see also:www.121watt.de