Let’s say you have a figured out a killer SEO strategy, and users are flooding in for free. Or maybe you managed to partner up with today’s hottest Instagram Influencer, and there’s a million people on your site. Your servers are a few seconds away from crashing, but that is perfectly fine as long as they are browsing your site long enough to convert. But on the internet is is hard to build trust as a startup. The lowest hanging fruit for anyone, technical or not, is right in front of you. Look into your page load speed performance.
Increasing page speed performance will make people will decrease bounce rates and drive up revenue. Users can often make a decision on whether or not to trust your site before they consciously realize it. That is why the speed of a visual first impression can drastically affect their purchasing decisions, and your top line growth.
When bounce rates go down, your conversion rates will go up. The relationship will usually come in cycles. However you can always go back and see they will always be inversely correlated. You will almost never make more money when the number of people leave your site immediately goes up.
Bounce rates and provide an objective measure of a site’s first impression. It is the number of people that leave your site before converting, or viewing another page. A low bounce rate shows you effectively build up trust and relevance. If you go into your Google Analytics dashboard, you will see evidence of this.
The requirements for this demonstration that you will need to have a Google Analytics account, and conversion tracking already set up.
Page Speed vs. Bounce Rates
- Go to sidebar and select Behavior
- Open the Site Speed menu
- Select Page Timings
4. At the top — change the “All Users” segment to “Bounced Sessions”
5. Select one more segment for the conversions you set up ex.
“Made a Purchase”
6. Below the segments bar, go to the “Distribution” tab. This is in between “Explorer” and “Map Overlay.”
7. You will see a chart like this:
You will likely see that the Bounced Sessions will have a significantly higher average Page Load Time than your Converted segment.
How to Analyze Your Conversion Rates
Now let’s analyze your conversion rates based on Document Interactive Time (DCI). Go back to the top, and add All Users as a segment. You should be able to see three rows of data now. (Converted, Bounced Sessions, All Users).
Look right below the chart type nav selector. Click on Document Interactive Time Bucket (sec). This is how long your user has to wait before they can interact with your website. The timer starts when their browser starts to load the page, to when it is possible to take an action.
Take a look at the top right, and look for how many people are in your Page Load Sample, and keep that in mind.
Now let’s look at the graph of buckets below that chart.
Your bucket ranges may vary, but take a look at the fourth row down. For our example it will be
3–5 seconds.
3–5 Seconds (Row 4)
Look at the number of Bounced Sessions, divide it by the number of All Users. That is your bounce rate for this bucket.
Look at the number of Converted users, and divide it by the number of All Users. That is your conversion rate for this bucket.
Were they more likely to bounce, or make a purchase? By what multiple?
1–3 Seconds (row 3)
Repeat what we did for the 3–5 second bucket. Where they roughly twice as likely to bounce, than to convert?
0.50–1 Seconds (row 2)
Repeat what we did for the previous 2 steps. Was your bounce rate less than your conversion rate?
0–0.50 Seconds (row 1)
Were users more likely to convert, than to bounce? Imagine if everyone in was here! It is clear that reducing page load speed time drives up revenues.
How to Measure Potential Revenue Increase
Imagine if your conversion rates at these buckets looked like this. Plug in your own numbers from above if you have them!
Document Interactive Time
< 0.5 seconds | 100 people | 12% | 12 converters
1–3 seconds | 3000 | 4% | 120 converters
3–5 seconds | 500 | 2% | 10 converters
Total: 142 converters / 3600 people
And your average profit on every item was $20. Based on this model you would derive $2840 in profit. Now imagine if everyone was brought up to that first bucket.
Document Interactive Time
< 0.5 seconds | 3600 people | 12% | 432 converters
Total: 432 converters / 3600 people
Based on this model you would derive $8640 in profit. An increase of $5800, or 204% increase in profits. You could buy a castle with that. Back when they were still being made.
Next time: How do you start moving people into the first and second rows?
