The conversion rate is one of the most common metrics that companies rely on when they optimize their business. But how do you actually measure it; can you trust your numbers?
We all have our own set of favorite metrics that we set targets for and try to optimize along the way. In general, the most important metrics that can directly be tied to increasing revenue and margin or reducing costs are often called KPIs.
What are your KPIs? I bet a metric closely related to conversion rate or conversion rate itself is on your list.
In this article I will explore the conversion rate metric and uncover why it is fundamentally wrong and what to do about it. As most of you will be familiar with Google Analytics, I will use this tool and the Google Analytics Demo Account to illustrate things in more depth.
Default Goal Conversion RateWhen asking people about their conversion rate, they often refer me to this report: (Conversions >> Goals >> Overview) The overall goal conversion rate number is based on:
- All different goals that are set up in your Google Analytics account.
- All sessions that drove traffic to your website.
Overall Goal Conversion RateIn every Google Analytics view you have the option to set up twenty different goals divided in four goal sets. Here is a simple rule to keep in mind: “The more different and easy to achieve goals you set up in your view, the more skewed your overall conversion rate metric will be.” Google Analytics allows you to set up four different goal types: You have to be very cautious when implementing duration and pages per session goals. These type of goals can skyrocket your overall goal conversion rate and make it a useless metric. In my opinion you should only set up goals for micro and macro conversions that are closely related to your bottom line. Keep a separate view if you want to measure easy-to-achieve goals as well.
Fix #1: Apply Segments Instead of Engagement GoalsContext is key so I understand when you still want to examine the effect of a higher or lower duration and pages per session on your most important conversions. This is where segments become your best friend. Segments allow you to exactly replicate the effect of the implementation of engagement goals. It might be a bit more difficult to work with them at first, but it’s definitely worth it.
Duration SegmentHere is an example setup of an engagement goal: session duration is longer than 60 seconds. You can apply this segment to your data view to find out whether people that spend an x amount of time on your site convert better or worse than others. Be cautious because time based metrics are easily misunderstood.
Pages/Session SegmentWithin the advanced section of segmentation you can apply pages per session segments as well. Here is an example: In addition you can apply multiple conditions to set up a segment.
Segment with Multiple ConditionsLet’s assume you want to segment on sessions with a duration time of longer than three minutes and more than five pages seen. Here is the outcome of this multi-conditional segment : Segments are very powerful and really come in handy when analyzing conversion rate metrics. Make sure to leverage them for your business.
Fix #2: Exclude Known TrafficYou want to filter out your own traffic in addition to only setting up goals for your most important conversions. You conversion rate metrics will remain skewed if you refrain from doing so. The larger your portion of traffic relatively is, the more skewed your data will become. Setting up IP address filters can easily be done. Here is an example (based on regular expression): There is a great tool that might come in handy if you need to filter a range of IP addresses instead. In some cases you have to deal with a dynamic IP address which can’t (easily) be filtered in Google Analytics. Two suggested workarounds for dealing with dynamic IP address filters:
- Filter your behavior on a unique dimension; in many cases city might do. (preferably set as a filter instead of segment)
- Block Google Analytics cookies via Ghostery.
Fix #3: Include Only Your Target MarketMany companies do only business in specific areas in the world. Here is a good example of the Google Analytics Demo Account: 42% of the sessions reside from Northern America. This region is responsible for 96% of the revenue and 98% of the transactions. I can definitely conclude here that the United States (and Canada) is their main target market. In this case you should set up a separate view for your target countries. Here is an example of a country filter in Google Analytics: I recommend to first set up a segment before applying a filter to your view. Experimenting with segments allows you to determine the effects without permanently affecting your data set. Another option would be to apply your filters to a testing view first.
Fix #4: Exclude Specific CustomersThis fix only applies if you have one unique offer (product or service) that people can only buy once. You might want to exclude this group in one of your views to get the most accurate goal conversion rate. You could work with custom dimensions to identify and exclude this group. However, make sure to experiment with segments instead of filters if you aren’t 100% convinced about how to set this up. It can be really complicated for sure!
Fix #5: User Level Conversion RateThere is no right or wrong here. Conversions can be measured based on a user or session level in Google Analytics. Some analysts argue that a session based metric is better because a session represents a unique opportunity to convert, where the user based metric could include more than one session. Others (including me) strongly believe in user based metrics, because it often takes more than one session to convert a user on her journey and you will get a more accurate picture of what’s going on if you analyze them both. Calculated metrics can help you to set up a user based conversion metric in Google Analytics. In this example we examine the Google Analytics Demo Account. This is how to set up the E-commerce conversion rate per user metric: The next step could be to use this new metric (Conv Rate Per User) in a custom report. For demonstration purposes I have modified the channel report to include this new metric: So now you have access to both metrics in one report. The user level conversion rate is usually 20 to 25% higher than the session level conversion rate. However, this is just a simple benchmark based on my experience, but it might greatly differ in your situation. Note: calculated metrics work retroactively on your data set. This allows you to discover some great insights on historical and future data! Keep in mind that cookie deletion, multi-platform and browser experiences can greatly influence the user level conversion rate metric.
Fix #6: Segment on Specific SourcesIn order to make any metric really useful, you need to segment it. An average conversion rate of 2% doesn’t tell much. The real insights are hidden in the differences between each of your segments. This could be new vs. returning visitors or mobile vs. desktop visitors. One of the other very useful cases is segmenting on the channel level. You will often find that a few of your channels bring in almost all conversions. You should either concentrate on your most important sources or improve the least performing onces. Read this article about segmentation tips to get started right away! Just always segment your data to answer important business questions in your organization.
- The conversion rate metric is one of the metrics to keep an eye on, but there are other important ones for your business.
- Only set up goals for your most important metrics if you want to use the overall goal conversion rate metric for optimization purposes.
- Apply the suggested fixes in this article to make the most sense of this metric.
- Supplement these ideas so that it best reflects your unique situation.
- Use both a session based metric and calculated user based conversion rate metric to learn the most about visitor behavior.