Evidence suggests that increasing numbers of people are venturing online to purchase goods particularly within the higher income and “silver surfer” households. So why do so many e-Retailer continue to witness low single digit conversion rates and high cart abandon rates?
In the first of a three-part series, we explore how to re-evaluate eRetail success and identify common points of failure.
Your biggest competitor is you
Segment or repent - Conversion calculation methods used by companies are never identical so, don’t benchmark performance against your neighbour. The best indicator for comparison is historic data from within the business. Instead, start by asking how can we double or, triple our existing conversion rate?
Analysis: It might be fine to use an average site-wide conversion rate for board meetings but, that figure is useless when it comes to finding real insight. As not all visitors are equal, segment the different types to find the dynamite that will lead to an explosion in conversion performance. Start by using the following conversion rate reporting filters:
Of course that doesn’t mean to say, we take our eye off the ball either. Keep tabs on how the competition are doing by reviewing industry trends using free and paid solutions. A comprehensive list of sources is summarised at Smart Insights and a few more include FireClick Index, Alexa, Think and Compete.
Watch out for ROPO cop
Add offline data - If call-center and in-store sales data isn’t integrated with web eCommerce data, any conversion rate number reported to the business is going to under value web influence. Market trends indicate that a significant number of people (+40%) research online and purchase offline (ROPO). Find out more useful stats over at consumer barometer.com
Measuring Call Centre conversion - Visitor transfer from online shop to call-center can be easily monitored using call tracking technologies. Be certain to select a provider that integrates seamlessly with your existing web analytics solution. Here are a few well known providers to consider, Response Tap, Mongoose Metrics, Marchex, IfByPhone and PowerMyAnalytics.
Manually capture offline orders - Use market research and/or
in-store surveys to provide a proxy for the ROPO % in your business. This method requires relatively little
investment and will allow for aggregated offline sales (ePOS) data to be
reports outside of the web analytics tool.
Apply a manual calculation using the proxy to acknowledge web influence
and visualise for business users by combining the data in Microsoft Excel.
Including offline orders automatically - Successful web analytics solutions in the e-Retail sector like IBM Coremetrics have long since provided a means by which offline data integration processing (DIP) can be achieved. However, many platforms now also offer the ability to collect data in an automated way via an Application Programming Interface (API). Leveraging this data transfer technique allows businesses to measure web influence more accurately and reliably. The growth API technology adoption amongst online eCommerce companies has been well documented. However, the benefits of a merged online and offline data ecosystem come with a challenge - additional transaction volumes and the visualisation of new data types.
Enhanced visualisation - Traditional web analytics tools offer standardised web reports that are pre-canned for speed optimisation but, hold limited value when it comes to customised conversion analysis between online and offline data sets. To handle the vast volume and iterative data interrogation an alternative approach is recommended (that is unless you’re prepared to re-mortgage the house for Adobe (Omniture) Insight).
Accounting for change (revenue)
Currency exchange rate conversion - Accounting principles dictate that real-world events like currency fluctuation be incorporated when reporting financial performance so, why not reflect that in the web analytics data too. e-Retailers operating across multiple regions already perform some form of currency conversion. Let’s elaborate on the choices:
Reconciling changes (orders)
Fulfilling orders - When items purchased online are cancelled
or, modified life becomes more problematic for eCommerce site owners that
are purely reliant on site metrics for conversion analysis. Order management systems don’t match web analytics
tools leading to further suspicion about data accuracy of the latter.
Re-open denominator debate - The ‘unique visitors’ metric is far from what many preconceive to be a unique person or, individual and yet it is championed as the denominator metric in every eCommerce conversion beauty pageant. Web analytics solutions were designed to use a combination of visitor device (cookies) and browser (sessions) to determine uniqueness which is fundamentally inaccurate. Fast-forward to today’s online shopping behaviour and that becomes even more obsolete with individuals’ using multiple devices (desktops, laptops, mobiles and tablet) and browsers (Chrome, Firefox, Internet Explorer) to browse and purchase. Even when fingerprint authenticated internet browsing is enforced, tracking individuals’ using web technology will not be accurate and if it’s “all about the trends” as our industry rhetoric would suggest, why not just use ‘visits’ as the denominator for e-commerce conversion measurement?
This idea is certainly not an original one (Belkin) and there is prominent opposition to it too (Kaushik) but, let’s agree to disagree and consider how a business might adapt to using visits. You’ve got a hard sell within the business to change from ‘unique visitors’ as people are familiar with the web terminology, comfortably ignorant about what it actually means and unhappy to see conversion rates plummet from 3% to 0.03%. However, think about how much easier eCommerce conversion investigation would become. Analysis by marketing channel or, visit and device type would reflect tracking technology counting methodology and comparing different tools or time periods would be less problematic (Longden). Change is never easy but, if you built it, they will come.
A measure of honesty - A few years ago, whilst working at
Skype, the metric used to report the health of the business to investors was
the number of ‘registered’ users. A
hollow and vain metric on account of the fact that there were registered users
that never bothered to actually log-in and use the product and also some people
tended created multiple accounts.
Internally however, the use of ‘active users’ was championed to measure
conversion - The number of people who logged in during a given period after all
was a better reflection of the VOIP providers’ peer-to-peer network strength
and community. These days the Skype CEO
talks openly about ‘connected’ (rebranded active) users externally and sure
this metric isn’t bullet-proof either but, is at least an honest account of
performance. At the last count, Skype
has +600 million registered or, +250 connected users and continues to grow at
pace, albeit with a different baseline for conversion. And finally...
Not all new visitors are welcome
Exclude the unwanted - Not everyone that visits your online store wants to buy
something. Visitors may have arrived at your
site by mistake or, might simply be killing time browsing the internet
aimlessly. Don’t beat yourself up too
much and focus on the visitors with the most potential to convert.
How about excluding unwanted visitors from the conversion rate calculation entirely to report a more realistic number back to the business?
Tracking single page visits or, time-on-page metrics can be misleading due to the underlying way that analytics tools track. create a new metric to segment with…
triggered after a visitor has spent a specified amount on time on site. Each web analytics tool captures information
differently and as an example, here’s how Google
Analytics does it:
setTimeout("_gaq.push(['_trackEvent', 'read', 'ten'])",10000);
After the site code is added the “adjusted” conversion rate analysis can begin by excluding sessions by New Visitors that don’t include the timing event.
*Small print - Adjusted tracking involves collecting additional requests or ‘hits’ so it is wise to calculate any increase before implementing. If you’re an Adobe (Omniture) SiteCatalyst user, check the secondary server call quota and for Google Analytics Free users, be sure to come in under 10million/mth.
That completes the first instalment on eCommerce site conversion
success. Pop back again soon to read about tracking enhancements and
lost opportunities in part two.
How are you measuring eCommerce site success?
We would love to hear your opinion in the comments section below so don't be shy.
About the Author
Alex Brown is a Digital Analytics and Site Optimisation expert who works as an independent freelance consultant. The opinions shared in this blog are based on personal experiences gathered over a decade of data crunching and technology evaluation. The author makes no attempt to be grammatically, politically (or otherwise) correct. Spelling was never a strong point and for practical reasons, not all vendors in the market are referenced in the article - no hard feelings.
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|Resources||(In Alphabetical Order)|
|Alexa||Competitor Site Information|
|Avinash Kaushik||Unique Visitor Conversion Rates|
|Brian Clifton||Converting Foreign Currency|
|Engaget||API Growth Infographic|
|European Central Bank||Daily FX feed|
|Fireclick Index||Digital River Conversion Rates Information|
|Google Analytics||Adjusting for Site Bounce|
|Google FX||Ecommerce Currency Conversion|
|Google Research||Consumer Barometer Information
|Google Think||Other Consumer Insights|
|IfbyPhone||Phone Call Tracking|
|iJento||Data Integration and Reporting Services|
|Jonny Longden||Unique Visitor Conversion Issues|
|Marchex||Call Tracking Solution|
|Matt Belkin||Use Visits for Conversion not Unique Visitors|
|Monetate||API Growth Infographic|
|Mongoose Metrics||Call Phone Measurement|
|Open Exchange Rate||FX Currency Conversion Solution
|Power (formerly Pimp) My Analytics||Visit to Call Monitoring Solution|
|Qlikview||Data Management and Visualisation Software|
|Response Tap||Website to Phone Measurement|
|Smart Insights||Useful Sources of Market Statistics|
|Snowplow||Versatile Digital Analytics Solution|
|SumAll||Data Integration and Visualisation Service|
|Sweet Spot||Information Integration SaaS Solution|
|Tableau||Data Visualisation Software|
|Timing Events||HTML School|
|Visokio Omnisciope||Powerful Data ETL and Visualisation|
Ecommerce image courtesy of Digitalart / Freedigitalphotos.net
Reject stamp courtesty of Stuart Miles / Freedigitalphotos.net
Spirit level courtesy of Arvind Balaraman / Freedigitalphotos.net
Alien image courtesy of Simon Howden / Freedigitalphotos.net