Defining a new KPI #1 – New Customer on First Visit Index

Some background information…

Often web analytics data can be extremely revealing – I have seen conversion rates increase ten fold as a result of web site changes brought about by such data. However as the analyst, you will know that interpreting the data is only half the story. You also need to communicate this story effectively across your organisation in order to get the buy-in required for the wholesale changes you may be proposing. You do this by creating internal “stakeholder” reports. The report is a very abridged version of your web analytics reports, usually summarised in Powerpoint and/or Excel and known as a Key Performance Indicator report (KPI Report).

There are literally dozens (if not tens of dozens) of possible KPI values to include in such reports and Eric T. Peterson’s The Big Book of KPIs lists just about all of them. The trick is to only select a handful relevant to each of your particular stakeholders i .e. don’t show all stakholders, all the KPIs – its too much information that will result in a loss of impact.

An example KPI report may include:
• Average conversion rate
• Average order value
• Average per visit value
• Average ROI
• Percentage revenue from new visitors

Note there are only 5 KPIs in this report, which is entirely acceptable and even desirable.

New Customer on First Visit Index KPI

Definition: What is the likelihood of a new visitor becoming a new customer on their first visit?

This is a key question many Marketers and E-commerce Managers (usually the same person!) are asking themselves. For example, should they be investing their time and effort in attempting to get their new visitors to convert first time i.e. emphasizing calls to action in their marketing efforts and page content? Or should more engagement and relationship building methods be employed?

Figure 1 – revenue by visitor type

Figure 1 is an example web site that shows a high proportion of its revenue is generated by first time visitors. But how does that relate to the number of first time visitors to the web site? The New Customer on First Visit Index KPI can tell us this:

New Customer on First Visit Index =

%transactions from new visitors
%visits from new visitors

Figure 2 – %transactions from new visitors
(click for new window)
Figure 3 – %visits from new visitors
(click for new window)
Figure 3 Figure 2

For this web site, the numerator is taken from Figure 2 and denominator from Figure 3, the value is calculated as:

New Customer on First Visit Index = 62.50 / 77.20
New Customer on First Visit Index = 0.81

Interpretation for the New Customer Index KPI

  • A value of 1.0 tells us that a new visitor is equally likely to become a customer as a returning visitor.
  • A value of less than 1.0 indicates a new visitor is less likely to become a customer than a returning visitor.
  • A value of greater than 1.0 indicates a new visitor is more likely to become a customer than a returning visitor.

For the example web site (New Customer on First Visit Index = 0.81), a new visitor is less likely to purchase than a returning visitor. This is not surprising as the average order value KPI is high (£1,315.99). Considering this, it is therefore surprising is that the New Customer on First Visit Index is so high. This indicates that the value proposition and other on-site factors such as trust, page content quality etc. is very high for this web site.


Q: What is the likelihood of a new visitor becoming a new customer on their first visit?
A: For this example web site, a visitor is slightly less likely to purchase on their first visit.

However, the emphasis is on slightly. Conventional thought would be that such a high value item would require multiple visits for the potential customer to be convinced to purchase. In this example, it appears the visitor has already made up their mind they are ready to purchase (perhaps there is a strong brand influence) – they just need a quick, easy and trustful source to purchase from.

So the Marketers and E-commerce Managers should indeed invest their time and efforts in emphasizing calls to action in their marketing efforts and page content.

What do you think? Do you have a KPI for your organisation that has not been documented elsewhere? Please share your thoughts via comments.

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  1. Tanya Barrow

    I work at a non-profit and we are in the process of implementing Omniture. As a former Urchin client, we were limited by the metrics we could support. Now with Omniture, we have the flexibility to define KPIs. Our struggle is that we are not sure which KPIs are relevant for our type of business. What is the decision making process for determining that? Some key points that could frame this is that we are looking to improve our reputation, influence and funding. What KPIs would indicate performance in areas like that? (Obviously funding is obvious as we have donation pages on our site.) Thank you.

  2. Brian Clifton

    Susana: have a look at

    “Search” relates to

    If a search engine is not detected in the list then it will show in the Referrer report. BTW, GA-Experts have some clever ways to enhance the search engine list and have posted one method at:

    Good luck

    Updated: 24-Aug-2007

    Looking at this again in the urchin.js, any referrer with ‘search’ in the domain name will also be displayed as ‘search’ in the reports – for example Clearly this is not intented. I have submited this to the developers for correction.

    Thanks to my colleague Serge for pointing this out.


  3. Susana

    Hi Brian,

    I was just looking at the reports that GA provides under the Search Engines tab. I’ve got the following values:

    1. Google — 67,062 visits
    2. Yahoo — 4,179 visits
    3. Search — 3,269 visits
    4. AOL — 2,825 visits

    My question is if ‘Search’ refers to the search engine, or maybe or is just the value assigned when GA can’t find the referring search engine.

    Your input on this one is very much appreciated

  4. Brian Clifton

    Andrew: Great questions…

    1. Yes, this KPI very sensitive to the market you are analysing. If you have any data on this I would love to see it – either in confidence or on the blog. I would agree, that a web site for completing a tax payment is much more likely to get the conversion on the first visit. It would be great to see how much more likely that is – and perhaps even benchmark against other sectors.

    2. Yes, price comparison means a lot of the qualification criteria (price) has been taken into account before the visitor arrives on your site. So they would be much more likely to convert on their first visit. If the data says not, then it would indicate there are trust factor problems (no or unclear payment encryption, poor design, no testimonials, unknown brand, no returns policy, no privacy policy etc.), or technical problems (slow pages, broken links, site downtime etc.) with your web site.

    Would love to see some data…

  5. Brian Clifton

    Rod: Thanks for your input – and I thought was an acronym for Painleve Analysis…

    I tend to prefer indexes rather than comparing individual conversions, partly because my statistics knowledge is not as good as yours and partly because I have been mixing with a lot of marketing people lately!

    Essentially marketers appear to perfer one number to convey the story rather than two. Having recently written an entire chapter on measuring KPIs using GA (my mind swimming in numbers, ratios and percentages), I tend to agree. Both methods convey the same message, so I guess its just personal choice.

    Eric: Good to see we are on the same page here.

    BTW, I chose %transactions as the numerator as I wanted to specifically emphasize that I was interested in purchasers (customers), not all goal conversions.

  6. Andrew Miles

    Hi Brian,

    Interesting post, I have been thinking about the difference between the new vs returning conversions and it would be great to hear your thoughts on the following and whether they would impact the above KPI:

    1. Do you think the new vs returning conversions is market specific/dependant on your target audience? As the web has become more of a research tool where customers have such a large choice they are comparing prices to find the best deal before committing.

    The target audience comment relates to a product or goal where you are selling/offering a service in a niche market or people have to come to your site to purchase, i.e. purchase car tax online. People are more inclined to convert on their first visit than on say a holiday website where they would see if they could get a better deal elsewhere. With this example though the returning visits will also convert so you may not see that much difference in the numbers.

    2. Do you think the introduction of price comparison tools would also affect the conversion rate? i.e. if a comparison site offered links directly to your site from a search results page on a site like kelkoo or price runner. Once the comparisons had been made and the user is happy with the price, they would navigate to your site and commit payment as the research had already been done for them and they would show as a new visitor (obv depending on whether the user had visited your site before or not and set cookies etc).



  7. Eric T. Peterson


    Brian and I had been going over this via email for a few days and yeah, you’re reporting a typo (pretty substantial one I agree!) The original (and correct) definition of new and returning visitor conversion rate are (as you state):

    New Visitor Conversions/New Visitors
    Repeat Visitor Conversions/Repeat Visitors

    These metrics are defined correctly on page 184 in “Web Analytics Demystified” but will be corrected in the next iteration of my book on KPIs.

    And yeah, cookie deletion happens, nothing you can do about that.

    Thanks for catching the typo (and thanks to Brian as well!)

    Eric T. Peterson
    Web Analytics Demystified

  8. Rod Jacka

    Hi Brian,

    Interesting approach. I personally would use your method but prefer to look at the ratios between the populations rather than to create an index. The reason for this is that it makes it a little easier do a statistical significance test on the difference in means for the ratios.

    I actually disagree with Eric T. Peterson’s original ratios in the Big Book of KPIs. Which is shown as:

    Total New Customers Converted / All Visitors = New Buyer Conversion Rate

    Total Returning Customers Converted / All Visitors = Returning Buyer Conversion Rate

    The use of the demonimator of All Visitors biases the results. I prefer to use the ratio:

    New Visitor Conversions/New Visitors
    Repeat Visitor Conversions/Repeat Visitors

    Otherwise the ratios will be biased towards the group that has the greater representation in the population.

    E.g if we have 5 repeat visitors and 95 new visitors and 2 repeat visitor conversion and 2 new visitor conversions Eric’s ratio would be

    2/100 = 2%
    2/100 = 2%
    = No difference in the population behavior

    However with the denominator changed to match the visitor’s group the results are signficantly different:
    2/5 = 20%
    2/95 = 2.1%
    = Big difference in the population behavior

    In support of Eric’s approach the use of the new visitor or repeat visitor as the denominator may be biased if there is a large percentage of visitors who delete or reject cookies from the site. Cookie leakage is a fact of life and I would recommend trying to determine the percentage of visitors who refuse to accept cookies based on the web server log files should be checked before deciding on which is the better approach. Unfortunately it is difficult to determine whether a visitor has deleted a cookie, but the rejection rate should give some indication.

    Alas it isn’t a perfect world, but I generally prefer this approach over Eric’s T. Peterson’s.

  9. Brian Clifton

    Hi Ermanna – yes of course we had coffee during the break.

    Out of interest, what type of KPIs are you currently using and do they help upper management to derive web strategy or are they just gathering dust?

  10. ermanna

    Hi Brian (we met at SES Milan, do you remember?). A very interesting post for me.


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