Email: What’s Your Real Open Rate?

Many email service providers admit that there has been a gradual decline in open rates over the past few years. While the open rate doesn’t tell the whole story on on email success, it is still vital to measure. After all, if your audience doesn’t open up your email, they have no chance to read it and respond to it.

One of the primary reasons cited for the decline is inbox clutter. According to Forrester Research, 60% of consumers believe they receive too much email. In another study, Customer Knowledge is Marketer Power, Forrester found that the chief reason that marketers who believe email will be less effective in 2 years  is “too much clutter in consumer inboxes.” A belief that “SPAM” will drive the decline was cited by only 59%.

Clearly, we are all becoming increasingly numb to the steady stream of email arriving in our inboxes. A second, related reason often given for the decline in open rates is the increasing effectiveness of spam filters that help manage this flood of email.

A third reason, and a significant one, is technological. The way that opens are measured is by including a tiny image (usually a 1 pixel by 1 pixel gif or jpeg) within the email. Once the images that are embedded in the email are served, the email is recorded as opened. The problem is that there are a lot of email readers don’t automatically serve the images in an email. In fact, ExactTarget estimates that 50% of all email is now delivered to email readers that either don’t automatically render images or are unable to render images, such as Outlook, Gmail, AOL, and handheld devices such as Blackberries. Thus, there is an inherent bias in not detecting all of the opens.

If you’re running an email campaign, it’s important to know the true open rate, so you can gauge the true reach of your email message. There’s an easy way to do this. It’s based on the insight that click-throughs are always measured, even if opens aren’t. Even though the email reader may not be indicating  an open, because it hasn’t rendered the images, the recipient of the email can still click on the links. That means that some recipients will be tracked as clicking through, but not opening an email. Let’s walk through an example.

Here’s the initial tracking information for an email:

Here’s how to estimate the true open rate:

1. Download the list of the email addresses that have opened the email from your email service provider.
2. Download the list of the email addresses that have clicked on a link in the email. Now match up the list of those who have clicked through, to see if they were tracked as opening the email. In the case above, it turns out that 105 recipients clicked a link in the email, but only 75 of them were tracked as having opened the email.
3. Multiply the open rate above by the ratio 105/75. This gives an estimate of the true open rate, assuming the same click through to open ratio for the group that clicked on a link in the email, but was not tracked as having opened the email. The revised tracking information is as follows:

As you can see, because not all of the email reader render images, the estimated open rate in this case was actually 40% higher than reported. Here’s how you can use this information:

• In order to maximize your click through rates, make sure that message in your emails does not rely on images. That way, if the recipient of your email doesn’t see the images, they can still respond to your message. As demonstrated above, this can help increase your open rates by 40% – or more.
• It’s vital to know what the real underlying trends are for your email campaigns, so you can make adjustments as necessary. You’re in a better position to know that if you monitor the estimated open rate, as described above, because it eliminates quirks in the tracking system. You need to make adjustments in your strategy based on real changes in customer behavior, rather than changes in the way email readers render images.
• With the estimated open rate, you now have a better estimate of the cumulative penetration of your message to your target audience. For example, if the reported rate shows a cumulative penetration of 33% after several emails, and you actually have a 40% higher open rate, a better estimate of your penetration is 1.4 x 33% or roughly 46%. You can then make better decisions about how to most effectively reach the rest of your target audience.

SEO: Predicting the Payoff

SEO Strategy – The Landscape

SEO is a critical component of marketing for every website. There are many tips and techniques that are widely available that can help you increase the chances of getting a high ranking for the search keywords and phrases that are central to your marketing strategy. Everyone knows that a higher ranking is better, but exactly how high does your ranking have to be to generate significant traffic for your website? Is it possible to predict how much traffic you can generate for a given search phrase and ranking?

It is well known that you can use a resource such as the Google Keyword Tool to estimate monthly traffic for a keyword. Once you have that number, the question becomes: given a particular ranking, what percentage of those searches will result in a visit to your website? You can’t really create a reliable, comprehensive search phrase strategy without this critical piece of information.

There is a variety of counsel and opinion on this topic, not all of it consistent. For instance, one website, which provides research, training and educational services exclusively for the publishing industry, states the following rule of thumb:

“When your website or landing page turns up on page one in Google, you’re getting 100% visibility..But what happens when your landing page ends up on page two or three? We estimate that you’re getting about 32% Google visibility on page two, meaning only about 32% of users ever click through to page two, and a meager 7% visibility on page three. If you’re on page four or beyond, you simply don’t have a chance of being seen by your potential customers.”

The authors cited no source for this rule of thumb, or explanation of how they developed it. There are a number of other rules of thumb about click distributions floating around on the web, which are entirely inconsistent with the above. I’m not going to dwell on these here; I’d rather get right to the data I believe is the most credible and useful.

SEO Click Disributions – The Best Data Avaliable

There have been several eye-tracking studies that have been done over the past few years, all of which produce consistent results. Perhaps the best-known among them is a study that was performed at Cornell University that showed the following:

Source: SEO Researcher

This data tells a far different tale than the rule of thumb cited above: the first three ranks get 80% of the clicks, and the first page gets 98.9% of the clicks!

You might object, and I would agree, that this data is derived from an eye tracking study, not actual searches, and would thus compel some caution on extrapolating the results. Fortunately, there is some actual data available. In 2006, AOL leaked some data on over 36 million queries. The data was analyzed by Richard Hearne, and the results are as follows:

These results, by and large, are consistent with the Cornell eye-tracking study, in that the first page attracts an extremely high percentage of the clicks. The first three ranks garner 63% of the clicks; the top 10, 90%; the top 20, 94.5%. Here are the percentages for ranks 1-21, 31, and 41:

Viewed another way, an improvement in rank from second to first will almost quadruple the number of clicks. The number one ranking produces as many clicks as ranks two through eight combined. The drop-off in clicks is enormous by the time you get to the second page; a rank off 11 produces only .66% of the clicks; in comparison a rank of 10 produces more than 4 times as many, and the number 1 rank more than 60 times as many!

This click distribution has also been confirmed by an independent set of search data analyzed by Enquisite, a firm that specializes in search optimization software. Based on a proprietary data set of 300 million searches, the first page grabbed 89.71% of the clicks; the second 5.93%; the third, 1.85%, the fourth, .78%; and the fifth, .46%.

Since there are several methods that have produced highly similar results, there is a high degree of confidence that this data provides a reliable foundation on which to base an SEO strategy.

Implications for SEO Strategy

• The ranking you can achieve for any given search phrase depends on a number of factors, including how well you optimize your pages for the search phrase, your page rank, and the amount of competition. If you opt to compete for high volume search phrases with a lot of competition, you have to realistically weigh the chances that you can make the first page.
• A better option may be to pursue a long tail strategy, in which you set your sights on achieving a number one ranking on lower volume search phrases with lower levels of competition. This strategy necessarily involves multiple keywords in order to generate significant volumes of traffic for your website.
• But perhaps the best option of all, made possible by this data, would be to pursue a mixed strategy. The increase in traffic you can expect from improving your ranking for any particular search phrase can now be predicted. You can therefore weigh the incremental increase in your website traffic for an entire portfolio of search phrases, and allocate your efforts in a way that will optimize your ROI.