Page 217 - DCAP109_GRAPHIC_TOOLS

Graphic Tools

Notes

I’m including this next graph to reinforce the connection between load time and user
behavior.

Over the 12 weeks, you can see that, while the HTML delays were constant — 500 ms and
1000 ms — users’ reaction to these delays fluctuated. The drop in bounce rate ranged from
around –2% and –12% for users who experienced a 1000 ms delay, and 0% and –6% for
those who experienced a 500 ms delay. While the bounce rate may have varied, the one
thing that was constant was the fact that the behavior trends are strongly linear for both
groups, and the bounce rate for the 1000 ms group was consistently worse.
Finally, and most interestingly to me, we wanted to look beyond just the effect of delay in
the timeframe of the experiment. We know that slower pages have an immediate impact
on user behavior and customer satisfaction. We wanted to find out if there was any long-
term impact on customer satisfaction.
So we looked at our traffic data for the 6 weeks immediately after the experiment —
specifically at the behavior of returning visitors. As any site owner will tell you, repeat
customers are the bread and butter of an e-commerce vendor. These are the people you
need to keep happy. If you look at the graph below, you can see that, even after the
experiment was over and the shoppers in the 500 ms and 1000 ms group started to be
served the same accelerated site as the baseline group, they were significantly less likely
to return to the site. By the end of the 6-week period, you can see that return traffic is
slowly improving as visitors seem to finally be recovering from their poor experience.
Contd...

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