3 Metrics for Buff Analysis of Landing Page Optimization

Data keeps your landing page optimization strong. The trouble is that some marketers are lazy with data. They get a report every month. They look at cost. They look at revenue. They throw it away and charge forward.

We want you to be the other marketers – the ones who understand “no pain, no gain.” You have to dig into data to maximize revenue, and testing is only the beginning.

Here are three metrics to start your optimization-fitness program and what to do with them:

Metric #1. Bounce rate

You know this nasty little critter. The bounce rate tells you one of two things:

  1. The percentage of visitors who saw your page and immediately left
  2. The percentage of visitors who hit your page and did not clickthrough

In either case, it’s an ugly metric that you want to keep as small as possible. When it starts to grow, here’s what it might be telling you:

  • Your page stinks – people who arrive on a landing page need to immediately understand where they are, what they can do, and why they should do it. If your page buries the message, then it feeds bounce rate. You can either throw out the page or tweak and test improvements.
  • Your offer stinks – people may understand where they are, what they can do, and why you think they should do it. The trouble is that they don’t think they should do it. Your offer is not compelling enough, or its value is not clearly demonstrated.
  • You look sketchy – a webpage that looks like it was designed in 1995, or one claims “you’ve won $10,000!” will drive people away. If you’re asking for credit card information, make sure you’re on a secure checkout and that your customer knows it’s safe.
  • Your traffic stinks – you might have the right page and the right offer but the wrong people. The traffic source might be out of line with the page, or the offer you’re making might not be right for the visitor’s stage of the buying cycle.

Metric #2. ROI by source

Combining return-on-investment and traffic yields a powerful measurement: ROI by source. This can help you uncover the best sources traffic to your landing pages and show you were to invest.

Example:

You have an additional $5,000 to spend in your ad budget and plan to use it for a specific campaign. If you look at the sources of traffic to the campaign’s landing pages and sort them by ROI in descending order, then the top of the list has the channels that will give you the most bang for the buck (if more volume is available).

Metric #3. Average order value

Conversions and revenue get all the attention, but when you’re looking for good opportunities, you might want to check AOV.

Example:

You find that 500 out of 10,000 people purchased from one landing page with an average order size of $20. That’s $10,000 in revenue and a 5.0% conversion rate.

A month later, you notice that 200 out of 20,000 people purchase from a second landing page for the same offer. Their average order size was $35. That’s $7,000 in revenue and a 1.0% conversion rate.

Had you only looked at conversion rate and revenue, you might not have realized that the customers in the second group are much more valuable on average.

  • Increasing the conversion rate on the second page just 0.2% would earn an additional $1,400.
  • Increasing the conversion rate of the first page by the same amount would earn another $400.

Which page would you choose for landing page optimization?

The same is true in B2B lead generation. Two pages may yield a similar number of leads, but the quality of those leads, how likely they are to convert, and how much they’re willing to spend, can be vastly different.

Do you have a metric you use to find good opportunities? Let us know in the comments!

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One thought on “3 Metrics for Buff Analysis of Landing Page Optimization

  1. You should mention in the bounce rate portion of this article that it’s important to look at bounce rate on a per-page basis and not on a site-wide basis. article-heavy sites will naturally have high site-wide bounce rates because people are consuming information then leaving which is perfectly normal for article-heavy sites.

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