Landing Page Benchmarks - Introduction
Landing page benchmarks is an important part of achieving and maintaining successful landing pages. Benchmarking involve the identifying of key metrics to measure and compare on a continuous bases. These benchmark metrics can and are used to track your landing pages performance over time, and assist you in identifying your failures and success. Benchmark metric also provide critical information that can be used in your continues improvements to long lasting pages or to improve the design and effect of future landing pages.
There are many tool available online to assist you in tracking your metrics and benchmarks. These tools range from free to high cost that offer very granular and traffic specific data points that can offer incredible value if used correctly. But for even the smallest team or lone marketeer that has access to a small budget, having access to free tools such as Google Analytics and Google tag manager provides a fantastic starting point. With an addition of a few lines of code, all readily available to just copy and paste online, and the creation of an online account in minutes your landing page will be setup to track many metrics discussed below. The value that you can gain for using an analytics tool is really indispensable. As a marketer, you truly can not live without it. Some of the best metrics to use when benchmarking performance of landing pages are:
Tracking the number of unique visitors by itself does not give you much information other than to inform you of the number of visitors on your landing pages. The true value of this metric come when used in conjunction with other metrics. New information can be determined such as conversion rates and visitor per source of traffic. These metrics will help you answer the question of:
- What is your most valuable source?
- Which sources lead to the highest conversions?
- What percentage of visitors are converting from a particular source?
- How many times collectively do visitors visit the website per period?
A conversion can be state as getting the visitor of the landing page to complete or interact with the desired purpose of the page, i.e. get the user to act. The conversion rate uses the unique visitors to the landing page and compares it to the number of successful conversion. So if your site has 100 unique visitors and 10 of them submit a form to convert. Then that landing page has a conversion rate of 10%. High conversion rates show that you are reaching the intended audience and offering value to your visitors.
The bounce rate is the number of visitor who land on your landing page but leave before the have taken any action. This metric is often shown as a percentage of total unique visitors versus converted visitors, i.e. of the 100 visitor on your landing page 20 converted, (provided the landing page has no other action available), then the bounce rate is 80%. Bounce rate is one of the most important metrics to get right, as a high bounce rate show that the landing page is not offering the visitor the value they intended to receive.
There are many things that influence a higher bounce rate. The number one issue is lack of a congruent message to match the users thought sequence. Users decide what they are looking for once they type it. The results of what was typed normally matches what they are searching for. The user then clicks on the search add, may it be organic or paid, to what best matches what they are looking for. Then they get redirected from Google to a landing page. This landing page needs to match what the user is expecting. It has to follow the users thought sequence.
High bounce rates are usually bad but aren't necessarily bad it really depends on what the intended purpose of the page is and if the user is fulfilling it properly. An example of a high bounce rate not necessarily being bad would be if the page has a specific, niche, DIY content like, “how to screw in a lightbulb”. The user would read the content and get the value from the website and leave without taking any additional action.
In this case the users have gotten the exact value they came for, without distraction and frustration. One way to be sure that this is the case is to observe average time on page. If it is far less than to be expected then the bounce rate could possibly be a bad thing.
Sources of traffic
Visitor that land on your landing page can come from many different sources, such as search (paid or organic), social media, email, display ads or direct link. Source can be broken down even further to more granular levels. For example search could be analysed at which search provider the visitor had originated from example Google or Bing. Going even more granular you could investigate which search terms lead visitors to your landing page. Much like unique visitors sources of traffics true value is shown when used in conjunction with other metrics to show trends of sources.
Cost per acquisition (Campaign)
Cost per acquisition works well with campaign based landing pages that often include some advertising cost. When comparing the cost associated with the campaign against the source where the costs were sent and the resulting conversion rate, you can determine if the price return adequate value for number of conversions received.
Using free or inexpensive analytics tools can aid you in future success. CPA is definitely a very important landing page benchmarks. Once you have gotten to grips with the basic metrics offer by these analytics tools it maybe time to drive deeper into the rich feature sets and try to extract more value. By making use of the tooling you can extract more granular information. Using this information you can disseminate patterns and behaviors of your visitors. Couple the use of a good analytics tool and a continues testing implementation like A/B testing or multivariate testing and you can determine what works best to entice visitors to convert.
An important note when dealing with landing page benchmarks and metrics is the illusion of averages. Average numbers can hide a lot of detail about the underlying metric, often depicting a skew view on things. It is important to use your discretion when interpreting the meaning of an average metric. In statistics additional metrics are often used to help give meaning to the shape of the data set you are analyzing, such as:
- Standard deviation: A figure used to show the dispersion in a data set.
- Mode: The most common occurring value in the data set.
- Range (Min/Max): The lowest and the highest value in the data set.
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