Slice and dice your conversion rate


When I am confronted with a new website, especially an e-commerce site, my first goal (after I do whatever the customer thinks is the most important) is usually to figure out what drives the conversion rate.

If a conversion rate is 2%, that means, some visits are converting at 10% and some visits are converting at .001%. So I attack the problem by slicing and dicing the data to figure out what a 10% conversion rate “looks like.”

It is a backwards problem. The territory would be easier if the questions were, “We made this change, how did it perform?” or, “We’ve started a new campaign, how did it perform?” With the backwards, slicing and dicing problem, the question changes to, “Something performs well here and something performs poorly — what are those ‘somethings?'”

I usually look at a handful of indicators (and always love when I have a powerful package like Omniture to do this with):

Conversion rate by landing page: This is especially helpful when a site is well-optimized for the search engines, because the landing page says a lot about the search terms themselves (and you don’t have to do the analysis for the 800 variations of the search term.) The equation here is orders that started with a visit to a specific page on the site, divided by all visits to that page, all in the same time frame. (And if you are interested in the visits vs. visitors debate, you should read Matt Belkin’s blog.)

Conversion rate by type of visitor (new, returning or loyal): Yes, we know that returning visitors should have a higher conversion rate than new visitors, but how much higher? Today I started working with a new site that had tiny, tiny new customer conversion rates, and returning conversion rates that any catalog company would be proud of. This becomes very interesting when you learn that over 1/4 of the site’s visitors are returning customers — so you’ve got all those new visitors who almost never buy but when they do, they suddenly become really valuable. Equation: New customer orders/Visits from all new visitors.

Conversion rate by organic search engine. You might think this is ho-hum, but all sites are not created equal and all search engines aren’t either. It doesn’t necessarily follow that if organic search results from Yahoo! convert better than those from Google, I should spend pay per click money on Yahoo! but I’m sure going to start there. (I add this last comment because I want to remind everyone, it’s not worth running numbers if you aren’t going to do anything with them. )

I wrote a white paper on this topic some time ago, you can get it here.

Robbin Steif

Our founder, Robbin Steif, started LunaMetrics in 2004. She is a graduate of Harvard College and the Harvard Business School, and has served on the Board of Directors for the Digital Analytics Association. Robbin is a winner of a BusinessWomen First award, as well as a Diamond Award for business leadership. In 2017, Robbin sold her company to HS2 Solutions and has since retired from LunaMetrics.

  • Ohad Gliksman

    I work for a large online marketing company and we track by landing pages and also by referers.
    each affiliate we work with is assigned an affiliate code and is assigend several potential landing pages. Over time, we optimize his landing pages based on performance. What I wanted to add was that we found out that there are no “good” landing pages or “bad” ones, and that it all depends on which customer profile is seeing them.

    That’s my 2 cents.

  • Adrien

    Dear Robbin,

    we know that returning visitors should have a higher conversion rate than new visitors, but how much higher?

    Repeat Visitors 8 Times More Likely To Make A Purchase Online Than New Visitors, According To WebSideStor

    I hope it will help you 🙂

  • Thanks Adrien. I already forwarded that to a different customer who ignores his repeat customers…

    Ohad, I think your comments above are worth more than 2 cents (8 aguroth – and now we know the real meaning of “conversion rate”).


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