Your website is the signboard for your organization.
You set this up to help a visitor on his way to making choices and to proceed to, for example, a purchase.
Unfortunately, setting up a website properly is often a big challenge.
Elements are regularly added to the website with the idea of being able to help the user better, but this has a counterproductive effect.
By applying conversion optimization, it is possible to better understand website behavior.
As an organization, you can then respond well to this!
Conversion optimization is the scientific validation of adjustments on a website. This way you test whether an adjustment is actually an improvement or whether it is based on chance.
That way you ensure that your organization only makes pre-validated adjustments that actually have a positive impact.
This is an essential part of growing as an organization and thus better serve your users.
Loss-making adjustments are avoided in this way. Risk management of the highest order.
Yet there is also a caveat to conversion optimization.
In order to be able to make a scientific judgment, there are requirements for the number of visitors and transactions.
That can be difficult, especially if you have too few visitors. Because what does this mean if you only have a handful of website visitors per day?
Fortunately, there are still opportunities to improve your website data-driven if you have little traffic.
Analyzing the users on your website is essential to see where users drop out and how you can serve them better.
In addition, you can see what has a positive effect and what does not in a data-driven way.
In this blog, we’ll discuss how to improve a website for your users when you don’t have enough traffic to actually test for conversion.
Let’s go!
What steps can you take to improve low-traffic websites?
Low website traffic is a problem for organizations of all sizes.
As mentioned earlier, a certain group size is needed to validate whether an effect is due to chance or not.
Nevertheless, data-driven work is always better than making changes indiscriminately. Having insight into website behavior helps your organization in setting priorities.
Data-driven work is split into two phases. Research your users and actually validate your solutions to user problems.
1. Research your users
There are all kinds of studies that can help your organization understand how users use the site, where they drop out, and what objections they have to not making a purchase.
Gaining insight into these bottlenecks is the starting point of your website optimization. If you do not know what is happening and for what reason this is happening, achieving more transactions is quite difficult.
Web analysis/quantitative research provides insight into what is happening on your website. Which pages do your users come to, on which device do they visit your website and where do they drop out?
The possibilities are endless and this is an essential part of any analysis.
Surveys (questionnaires) offer you the opportunity to ask questions directly to your users. This can be done in all kinds of ways. Think of showing a questionnaire to users who want to leave the website or asking questions to users who have made a purchase.
This way, you can ask specific questions about a user’s reasons for making or not making a purchase.
Customer service research is also an easy way to find out about customer problems.
Customer service employees are in daily contact with your customers and know exactly what is going on and what customers encounter.
Session recordings and heat maps provide insight into how users actually navigate through your website. By viewing session recordings, you can immediately see what users are up against.
Heatmaps also provide insight into which part of a page is being viewed and to what extent important elements on your page receive sufficient attention.
User testing or usability research gives the possibility to let users carry out an assignment on your website. You can directly ask the user about the motivation behind all the actions he or she performs on your website.
This gives a lot of insight into the user-friendliness of the website and whether it meets the expectations of the user.
Something can be designed in a certain way, but visitors get in the way of finding what they are looking for.
Competitive analysis provides insight into how other organizations have set up their website to help users make a purchase.
This way you can immediately find out differences and you also get direct insight into how you can distinguish yourself from the competition.
You have to take into account that competitors may implement things without testing. Copying competitors does not necessarily increase your chances of success.
2. Validating your solutions
Now that you as an organization have a good insight into the bottlenecks of your user, it is time to actually implement improvements.
You do this by converting your ideas to improve these into hypotheses. We do this on the basis of the so-called ABC principle: assumption + proof + control.
Supposition: Based on [data], we expect that [adaptation] for [user group] motivates them to [behavior] for this [reason].
Proof: This assumption is correct if we measure an [effect] on [growth metric].
Control: The assumption appears to be [(in)correct]. We’ve learned that [lessons]. The next step is [follow-up action].
By performing a duration calculation, you know exactly how long your test must run and what the impact must be on your metric to achieve significance.
Significance is the scientific basis that determines the probability that your adaptation is based on chance or not.
Your term calculation depends on two factors:
- How much traffic will get on the page you want to customize?
- And how many people convert on the goal you want to influence?
There are a lot of tools that can help you make a term calculation. An example is this tool.
Although this tool can be very useful to help you gain more insights into your optimizations, we strongly advise you to apply one of the strategies below.
The reason for this is that the calculator may be able to display unrealistic numbers when entered. This can give a wrong picture on which you may want to base your approach.
Example: you will achieve a 30% conversion uplift to be able to measure a significant difference in four weeks. Such a large improvement does not often occur in practice.
But how do you deal with low-traffic pages that do not come out of the duration calculation?
Unfortunately, there is no standard answer to this. Nevertheless, there are ways to gain insight into this.
Combine similar pages
If you have pages with a similar layout such as product detail pages or category pages, combining these pages in an experiment can provide enough traffic to get a significant result.
Use a micro conversion as a goal
Transactions and leads are the clearest metrics to hang results on.
These are very tangible and can be calculated directly in expected extra turnover. If these metrics do not take place sufficiently to experiment, it can be very relevant to measure micro conversions.
For example, you can think of the number of users who click through or the number of users who add something to the shopping cart or come to a product page.
When using micro conversions, it is essential that there is a logical link with your end goal. And that you also take the impact on your end goal into account when analysing the results.
Lowering your significance limit
As indicated earlier, the significance determines the extent to which an improvement is based on chance.
You often see that a limit of 95% certainty is used. That would mean that out of every 20 winners, 1 experiment is not an actual winner.
By lowering this limit to, for example, 80%, you can test more things, but the risk that something is based on chance is also greater.
And therefore also the risk that you implement a change with a negative effect.
If you choose to do so, always include other insights outside of your most important metric to get a good overall picture of your experiment.
At low numbers, this method is the least advisable, so let’s quickly move on to the next method.
Make adjustments and monitor them in the long term
If there is really very little traffic, it can be an option to simply implement changes and use quantitative analyses (web analysis) to monitor what happens to your metrics from the moment it is implemented.
Also, add an annotation to Google Analytics right away.
Do you see a structurally positive effect on your conversion metric?
Then at least your adjustment doesn’t seem to hurt. If it shows a negative effect from that moment on, you can therefore consider reversing your adjustment.
Be aware that you are now looking at correlation instead of causation.
In other words: you can never prove afterward that an improvement or deterioration in your conversion rate is the result of your change.
Usertesting / usability research
For larger re-designs or adjustments, a user survey is recommended.
This gives you direct insight into the reactions to adjustments you want to make.
The disadvantage here is that there are often only a handful of users participating in the survey who may not be representative of all users of your website.
In addition, the users will go through your site more consciously because they have to give feedback. This can cause different behavior than when they actually visit your website themselves.
Stay practical
It is now clear that data-driven working is of great importance. Even if your website does not directly lend itself to A/ B testing, there are still many possibilities.
All in all, it’s essential to know what helps your users and what doesn’t. If you don’t work data-driven, you won’t be any the wiser.
So it may just be that you make the wrong adjustments.
Of course, you don’t want that for your organization. So try to use the most practical way for your organization and learn what works and what doesn’t. Also in your approach.
Good luck with actually improving your website and helping your users!
