Clients and friends ask me all the time, “What should my conversion rate be?” Or, “What’s a ‘good’ conversion rate?” Or, my personal favorite, “What’s the ‘industry average’ conversion rate?” As if being “average” is where you should aim. Still, I get where people are coming from with this question. What they really want to know is, “Am I doing well enough?” And, “Am I leaving money on the table?” We’ll come to those. But first, I wanted to take you through why it’s almost impossible to answer the original question.
What is conversion rate? Simple. Conversion rate is:
- The number of people who show up on your site divided into…
- Sales. Or leads. Or email enrollments. Or… waitaminnit.
This isn’t looking so simple, is it?
The variety of conversion goals brings us to the first challenge with benchmarking conversion rates. Every business has different goals, usually more than one per site. You may want your customers to buy something and/or join your loyalty program. Those are two separate conversion actions and would each generate two separate conversion rates. Lead generation produces vastly different rates from e-commerce. And so on.
Of course, in most industries, you’re usually all conducting similar activities, which should make benchmarking conversion rate simpler, right?
Um… not exactly.
Because the second challenge is determining how you’re going to count “the number of people who show up on your site.” Last fall, I took a somewhat exhaustive look at how to count “people” on your site and addressed some of these issues. But, to recap, some businesses count “people” by “visits” and some by “unique visitors.” Visits are fairly straightforward. Unique visitors, less so. Let’s look at them one at a time.
When a web browser requests a page, your tracking tool counts that as the start of one visit. Each subsequent page requested counts as part of the same visit until the consumer closes their browser—ideally after completing a conversion action—or after their session times out. While 30 minutes of inactivity is somewhat, ahem, “standard” for causing session time outs, different settings among analytics tools and their users within a single industry can result in wildly different visit counts. Still visits are simple compared with our next culprit: unique visitors.
At their core, unique visitors seem simple. Most tracking tools count unique visitors via cookies placed in a visitors web browser and treat all visits from that same machine as belonging to a single “unique” visitor. And that’s all well and good. Except that the the lifespan of a given cookie can vary widely among analytics vendors and implementations. Some businesses expect set the cookie lifespan to 30 days. Others may choose 90 days. Or 14. Or 120. And that’s before considering topics such as cookie deletion, customers who use more than one computer or browser, different people in the same household using the same computer and on and on and on. In fact, these reasons are why Google Analytics guru Brian Clifton argues that counting unique visitors is useless. (Incidentally, I disagree with Brian and think that uniques are often better than nothing, but that still doesn’t make them great from a competitive data standpoint(*).
Now, I’ve alluded to this in each of the above sections, but, different analytics tools also compound this competitive data problem. Why? Because no two tools ever count traffic the same way. Google Analytics will report one metric, Omniture SiteCatalyst another and WebTrends a third. I have, on more than one occasion, run websites that contained tracking tags for two (or more) analytics tools simultaneously and found that each tool counted visits and visitors differently. While their movements were highly correlated, their reports were never, and I mean never, the same.
So, putting this all together, the only way to get a true competitive measure of conversion rate is for you and your competition to agree:
- To count the same conversion actions, whether those are sales, leads, enrollments, what-have-you’s;
- To use the same metric for traffic (visits or unique visitors);
- To agree to a common standard for session time outs and cookie lifespan; and,
- To use the same analytics tool configured precisely the same way.
Alternately, you can look at it this way. Take a look at what George Michie over at Rimm-Kaufman Group says about the value—or lack thereof—among competitive data. It’s well worth your time to give it a read. I have long believed that the best way to get the right results is to worry less about your competition and more about your customer.
Yes, a certain amount of competitive data is handy. And it’s frequently interesting. But will knowing your “industry average conversion rate” help your customers any? Probably not. Focus on their needs, their pain points, their cares. Address their concerns. And, then, instead of meeting your “industry average,” you may just lead the pack.
Footnote: Incidentally, I have recently been analyzing data across multiple sites in multiple industries that suggests visits may (and, boy, do I put heavy emphasis on that “may”) be a better leading indicator of conversion activity than unique visitors. Of course, I have to say that this comes with two huge caveats. Caveat #1: I want to run these models with larger and more diverse data sets. The amount of data I’m analyzing, while not trivial, is hardly going to represent every type of website out there. Caveat #2: None of the models I’ve put together accounts for more than 50% of conversion activity. A good number of on-site factors I’ve yet to analyze (price offered, message quality, etc.) also heavily impact conversion, so counting on visits alone as a leading indicator is only going to take you so far. Still, the early results look promising. I’ll keep you posted…
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analytics, Avinash Kaushik, Brian Clifton, continuous improvement, conversion, conversion rate, conversion rate optimization, E-commerce, e-commerce, e-marketing, ecommerce, Google Analytics, internet business, internet marketing, marketing, marketing best practices, measurement, metrics, Rimm-Kaufmann, competitive research, competition