AB Analytics : Web Analytics and Optimisation

10 Reasons Why Web Analytics Sucks Big Time

A Guide To Prevent Web Analytics Failure

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Executive sponsors have become increasingly frustrated that web analytics initiatives fail to deliver any real business insight.  

If left unchecked, this sentiment can lead to the reduction or, reallocation of budget and marks the end of hope for a resident web analytics professional. 

So, how does this situation arise and what can be done to prevent it?

Common Web Analytics Pitfalls

1. Top down, not bottom up

More often than not, web analytics failure begins during the adoption process when the initiative is being driven from the bottom up.  Even if deployment is successful, this approach nearly always results in siloed data usage by Marketing, Design or, I.T. departments and culminates with pointless debates during board meetings about conflicting data sources.

  • Get CEO support for Web Analytics from the start and demonstrate continual "value-add" by linking outputs back to company objectives that have a direct commercial benefit.

  • Ensure that an inclusive requirements gathering process is undertaken that allows different stakeholders the opportunity to contribute providing advise and education where appropriate.

Steve Jackson's Cult of Analytics is a great place to start learning more about how to build strong foundations.  

2. Integration across the nation

Just having the “big cheese” buy-in to the web analytics program is not sufficient for the initiative to deliver value.  Instead, the function needs to be integrated across the business to succeed.  However, exercise caution not to align any one business unit too closely as the focus of web analytics resource can become marginalised and narrow in scope. 

  • Set up a data governance team to oversee the direction of web analytics product life cycle.  Safe guard against one department running the show.

  • Position web analytics at the heart of the site by making the team responsible for change accountable for results measurement.

More recommendations on web analytics positioning and governance are available from Adobe Omniture's white paper available to download here!

3. Talent, tools and training (in that order)

"We bought a Ferrari but, only use it to go to the end of the driveway and back,”  remarked one head of marketing for a global clothing manufacturer recently.   After a frustrating nine months in web analytics, the lessons learned were straight forward enough but, ultimately proved quite costly for the business. 

  • Hire talented people to select and use the tools during early adoption and don't be afraid to get outside help provided they accelerate learning and foster long term self-sufficiency.
  • Prove the business case for web analytics investment using “freemium” tools before splashing out on a “best-in-class” product.
  • Ensure internal resources keep up with the ever changing digital measurement landscape. Attending conferences and training courses are mandatory for employee development and retention.  Set aside budget as part of the early scoping business case.

“The human skills needed to bring true value to an enterprise from web analytics are scarce, but they are more important than the technology involved.” Frank Buytendijk & Astrid Van Dorst, Gartner Group, April 2001

4. Measure everything and you wont find out anything

Ask a business starting out in online measurement what they want to track and it's fairly common to get the response, “Everything!” in reply.  Resist the temptation to track everything and instead answer one question to define tracking requirements…

  • Why does the web site exist?

The overly simplistic question usually sparks internal debate about company objectives and helps to build out a measurement framework that can be used to inform tracking implementation.  Create a measurement framework for your business using design principles and kpi definitions from Avinash Kaushik. 

5. Manage ecosystem evolution

Introducing web statistics into an established business data ecosystem is problematic.  The reports seldom match figures from other business intelligence tools and nuances in data collection methodology can easily undermine efforts to establish credibility amongst internal stakeholders. 

To ensure long term web analytics success, follows a few simple steps…

  • Do not circulate reports too widely after initial deployment and instead focus on reconciliation activity for a small number of key metrics.

  • Build a data dictionary to describe each key web metric and highlight the difference in data collection method between other tools using similar metric descriptions (e.g. “orders”).  Use it to educate the business and start in the board room.

  • Restrict access to reporting (at least initially). The number and variety of reports in most web analytics tools is enormous.  Customise reports available in the platform interface to ensure users focus on the important stuff.

  • Target and train web analytics “champions” for each business unit. These people will act as knowledge satellites evangelists and hopefully act as a buffer from requests that come in from around the business.

Start any reconciliation exercise with the six sensible steps suggested by June Dershewitz and when constructing a data dictionary for the business have a look online for examples in your industry sector. 

6. Web analytics just isn't enough

Don't be surprised if using web analytics alone is not enough to produce the step change in performance expected by the business.  Statistics are great at explaining what happened but, crucially not why it happened.  For best results, ccompliment web measurement with customer experience and observational analysis.

  • Seek opinions from a wider audience during initial design phases with focus groups, online user testing services or even eye-tracking (e.g FiveSecondTest, Gazehawk, etc). 
  • Use specialist tools to observe micro conversions, click activity and in-page site interaction  (e.g. ClickTale, CrazyEgg, etc).
  • Add a short site survey to allow visitors to give immediate and unbiased feedback (e.g. Qualaroo, Kampyle, etc)

There are countless methods and tools available to obtain a much more rounded view of new site visitors' and existing customers' behaviour than traditional web analytics data provides alone.  Ask us for a recommendation .

7. Avoid the data monkey trap

Shocking news!  Most web analysts don't actually analyse anything.  Instead companies pay these resources to pull reports and troubleshoot technical issues.  So perhaps a change of job description is required.  To avoid the "data monkey" trap try the following approach:

  • Allocate a maximum of 20% bandwidth to ad hoc reporting and have this agreed by the boss - And yes, that's just one day a week.

  • Setup a ticketing system and to prioritise incoming requests, monitor service levels and track how much resource is spent reporting.  Jira is a popular approach for many businesses

  • Identify the root cause behind reporting requests and don't blindly agree to deliver them - Easier said than done.

  • Automate at least 80% of standard reports using the web analytics email scheduling tools or, by building pre-populated reports using API's.  Most vendors have their own solution and their are really good third party ones like Omniscope and Excellent Analytics

  • Write a business case and secure budget to help support reporting activities using graduates or, outsourcing companies - Don't wait until it get overwhelmed

  • Train people on how to pull reports themselves - Its all about self-service these days

Interested in learning how other companies use web analytics resources? Visit Econsultancy who in partnership with Lynchpin published some interesting recent survey results

8. Don't expect return-on-investment without change

The ultimate acid test and competitive advantage for a data driven company is generated by their ability to implement change based on insights generated from web analysis.  Therefore, it goes without saying that return-on-investment can never be achieved until the development road map allows for sufficient resource to deploy code changes and implement recommendations in a timely fashion.

  • Build robust financial business cases to support web analytics code development

  • Promote findings internal and petition stakeholders to support further development resource to implement recommendations

  • Consider tag management solutions as a flexible alternative for web analytics code development

9. Crash test, dummies

Never release web analytics code changes onto Live site without thoroughly testing it first on a Test environment.  Failure to adhere to basic quality assurance procedures can have devastating short term effects on data quality and generate longer term trust issues with internal stakeholders.  Each Site or situation may require a slightly different approach. We perform the majority of single page audits with Charles and undertake large automated Site-wide audits using ObservePoint.  For cookie specific audits and competitor technology information we recommend Pikslme.

10. Responsive isn't just about web design

The internet is constantly changing and measurement techniques used to track it continually evolve at the same lightning pace.  Stay sharp and find out how the latest technological development can help improve the existing web analytics program. Put sufficient time and resource into keeping on top of industry developments and in practical terms this means:

  • Budget for at least two of the main web analytics conferences a year. Semphonic’s Xchange and Adobe-Omniture's Summit come highly recommended.

  • Reserve thirty minutes each day to read blogs, articles and other technology news.  To save time, set up RSS feeds and have content delivered directly and don't forget there are also great pod casts so that you can learn while you listen.  A favourite of ours is found at Beyond Web Analytics

So that completes the top ten gotcha's to avoid when managing a web analytics initiative.  Thanks for reading this article and now it's your turn to share.

Web Analytics Sucks: Who's to blame? 

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.

Related Products & Services

With in-depth knowledge of both the market place and major technology vendors, allow us to help select, negotiate, support and manage web analytics implementation for your business.  Contact Us for a confidential and informal discussion to see how our solutions can improve your business today.

Resources(In Alphabetical Order)
Adobe Summit
Web Analytics Conference
Audit software
Automated ReportingExcellent Analytics
Automated Reporting
Cookie Auditing
Click AnalyticsCrazyEgg
Cult of Analytics
Steve Jackson
Customer Experience AnalyticsClickTale
Customer FeedbackKampyle
Customer FeedbackQualroo
Data Dictionary Example
Office of Disability and Adjudication Review
Data GovernanceOmniture White Paper
Defining KPI's
Avinash Kausik
Eye Tracking
Measurement ModelAvinash Kausik
Online Usability Testing
Preferred debugging tool
PodcastsBeyond Web Analytics
Reconciliation how to guide
June Dershewitz
Survey ResultsEconsultancy
TestingVisual Website Optimiser
Ticketing SystemsJira
Xchange Analytics ConferenceSemphonics

Like this article?  a) tell us  b) share it c) download it and d) keep updated

Image courtesy of M Bartosch / Freedigitalphotos.net

Comments: 6

  • Lee Cowles Aug 14

    Some wise words in there, Alex :-)
  • Frank Walter Aug 14

    Awesome post, full of useful resources and watch outs. Thanks Alex!
  • Jim Sterne Aug 14

    Very good Alex! Now, if only the eMetrics Summit and the Digital Analytics Association were in the Resources section....
  • Alex Aug 15

    @Lee @Frank - Thanks for reading and the valuable feedback. Much appreciated! @Jim - Look out for future posts and you'll be pleasantly surprised. See you in Stockholm, hopefully.
  • Lars Aug 15

    Happy to hear that you like Excellent Analytics. Our other project now is to perfect the Pro version of it available at ampliofy.com.
  • Alex Aug 16

    @Lars - EA is an awesome product that is always happily recommended. The "update all queries" on the Pro version is worth upgrading for too - Great time saver!

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