Sales Funnels – Optimise or Die

Sales Funnels – Optimise or die!

This has to the be the biggest bain of all web analysts lives?  We are asked questions like where are people dropping out of, why don’t the funnel figures match the management information team’s figures? What is happening on the page to make people exit?

Do you know how to answer the questions?  Do you know why web analytics funnels sometimes don’t agree with other sources of information?

So how do we get over this?  Simple answer is that there is no simple answer.  There is also no short way of describing the situation either.

Step One – Where are people dropping out of?

Check that you’ve configured your funnel correctly.  Have you applied the right filters on the profile? Have you applied the regular expressions?

Google Analytics Sales Funnels

The above image is a simple image of a Google Analytics funnel which shows a 100% click thru – now anyone will tell you that this is very unlikely to get 100% conversion (ok impossible!!).  The red errors show the percentage (and volume) drop out but, also more importantly where they left.  This asks more questions:

  1. If the customers are existing to the contact us page does this mean that they have no confidence in our online purchase process e.g. no Verified by Visa, no Paypal links, no secure server?
  2. If they are exiting to a ‘delivery information’ page then can we assume that they don’t have enough information to make a judgement?
  3. If they are exiting the site – this causes concerns.  Are we looking at tabbed browsing? time outs? or are they going to a page on your site which isn’t tagged?
    • Crawl your site regularly to ensure that all pages are tagged and WORKING!
    • Check time on page against averages to see whether there are issues
    • Check with your IT teams to ensure that there aren’t any issues with server downtime (planned or unplanned).
    • Have you filtered out all UAT and internal traffic?  If your staff are valid customers then you may want to consider only blocking UAT traffic.

Step Two – Analyse Individual Behaviour

Magnify Solution Image

Google Analytics provides us with the ability to segment the information very easily.  Do you know how to do this?  Are you using this on a regular basis?  Well read on and impress your audience with insight that they never knew possible….

So you can not only look at ONLY those customers that came via a online marketing campaign but also those that came via an online marketing campaign but used a mobile device.  Now you are perhaps reading this and saying that you could set up a new profile that filtered out anything but mobile devices.  However, what if hadn’t done that before and your manager asked you that very question…. Do you want to give them a line:

Any new reports need to be planned in advance, the lead time is “x” and this would be increased if additional tagging is required.

Can you imagine how many times you would be able to use that saying before the audience started looking for someone else to do the job?  Not long at all… not long at all…

So why don’t you surprise them and answer the question but, give added value.

    1. Traffic that came via an online campaign
    2. when the customer was using an mobile device
    3. that paid using paypal
    4. compare that against non-mobile devices and their method of payment

Perhaps you will be then credited with bottom-line benefits because you’ve given the management the insight that alternative methods of payment may be cheaper to administer (and who knows create less fraud queries/issues).

 I think that advanced segmentation is something that may be worth a blog post all in its own….

Step Three – Customer Segmentation

Understanding who your customers is like the holy grail of analytics.  To the point that SaaS solutions like and Microsoft Dynamics CRM have arisen and become behemoths in their own rights.  So do you want to analyse every single person and put them into their own segment?

Now I don’t want this blog post to be all about how to segment customers but, if your organisation isn’t aware that customers are individuals and also appreciates that 1-2-1 marketing is incredibly hard to do right.  That is why they spend money (outside of web analytics if you can believe it) trying to understand their customers as groups, and sometimes these groups can be upwards of fifty segments each requiring their own marketing approach.

RBS Black Card - Homepage

Remember that this can sometimes be via a different channel.  If you look at RBS ( they have a variety of products for the ‘average’ individual and gives them the usual channels to communicate – mobile, internet, telephone, branch.  However, if we look at the segmentation of the customers there is a level of individuality…. albeit slightly elitist.

Another benefit of having an effective customer segmentation is that you’re able to plan the life-cycle of your customers.  Are your customers aspirational?  Are your customers borrowers or savers?  What combination would “typically” encourage further product sales or promotion to aspirational products which command a premium fee – ( – £250 annual fee + 19.9% APR).

So bringing the post back “on-point”…. It is these segments that we need to replicate as closely as possible within our Web Analytics solutions.  Now, I hear you’re saying that…

That’s Impossible

Well its not impossible just bloody hard.  Go back to the RBS Black card example.  You could use the microsite (or landing page) as a referrer through the application form.  However, if you’re looking at a product that is aspirational then you’ll want a seperately brand the application form and the microsite.

Now WebTrends had an interesting approach to multi-site tracking.  Simply include both tags (tags identified individual domains – known as DCSIDs) within the profile.  When processed the profile will be analysed taking both tags into account and allowing us to analyse cross-domain traffic.

Is this the best approach?  Answers on a postcard…

Step Four – Qualitative is expensive but, necessary

Now Google Analytics and the other web analytics solutions all provide us with the what (the numbers) but, they don’t always answer for sure the “Why”…. and to be honest you’re never going to get a definitive why because in short…

What works for Person A… doesn’t work for Person B… And what works for Person A on Day 1 may not work for the same person on Day 10.

Passive / Semi Pro Active

Qualitative isn’t about how many people like your site? Its WHAT they like about your site? WHAT they like about the brand? WHAT they like about the products?  (or where we get even more learning and insight …. WHAT THEY DON’T LIKE ABOUT YOU!).  Let us not forget that negative comments are learnings too and if approached in the right way can deliver “ten-fold” in returns.

Online software development has given rise to immediate qualitative solutions.  Companies like iPerceptions, Foresee provide premium services for capturing and analysing customers thoughts and opinions.  However, for the small business there are solutions available.  Kampyle for example.

Kampyle Center Screen Takeover Example

Screen takeovers (same approach taken by Foresee and iPerceptions) present your customers with the above based on logic e.g. time on page without movement or click on a particular element/image etc.  Or you could have a permanent passive request on every page on your site.  As show below:

Kampyle SideBar LogoIt really depends on what you want your customers to do?  Perhaps you only want to get feedback on certain pages?  Perhaps you don’t want your users to be distracted from completing the funnel?  Implementing this type of qualitative study is difficult because it can impact on your site flow.  However, will the results be more valuable in the strategic/long-term?  That’s a decision that each business will need to answer themselves.


Now, the other way would be to using email to gain qualitative information.  Email allows you to tailor the email questionnaire to your individual company defined segments and a lot of organisations will already have an email marketing solution.  However, the analysis may have to be done in-house – we are planning future posts on Excel and Access models to help analyse data so keep reading.


Optimising a sales funnel is something that is on-going issue – I’ve given you all a bunch of ideas of how to start optimising and measuring your funnel.  Looking at both Quantitative and Qualitative solutions.  However, what you must remember is that the over-riding issue of page weight, javascript issues and creating a funnel which is distracting from the ultimate goal.

Points to learn… Listen to your customers… Its their cash you want.

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