Web Analytics - A Medical Emergency

One of my favourite TV programmes at the moment is Casualty.  Or perhaps it's Holby City (they're both the same, really).  A typical episode unfolds with all the drama and angst between the main characters, which is suddenly broken up by the paramedics unloading a patient from an ambulance.  Perhaps the patient is the victim of a fire, or a road traffic accident, or another emergency.  Whatever it is, the paramedics come in, wheeling the patient along, giving a brief description of who they've got, the main symptoms, and start rattling off a list of numbers.  "Patient is RTA victim, aged 56, BP is 100 over 50, pulse is 58 and weak, 100 mls of adrenaline given..." the list goes on.  The senior consultant who is receiving the patient hasn't really got time to be asking questions like, "Is that bad?" and certainly not, "Is this important?"  The questions he's already asking himself are, "What can we do to help this patient?" and "What's been done already?"

Regular readers will already know where I'm going with this analogy, so I'll try to keep it brief.  In a life-or-death situation (and no, web analysts are hardly ever going to have that degree of responsiblity) there isn't really time to start asking and answering the trivial questions.  The executive dashboard, the report or the update need to state what the results are at the moment, and how this looks against target, normal or threshold.  The executive, in a similar way to the Formula 1 driver I mentioned last time, hasn't got time to look through all the data, decide what's important and what isn't, and what needs to be looked at.




As an aside, I should comment that reporting dying figures to an executive is likely to lead to a series of questions back to the analyst, so be ready to answer them.  Better still, including a commentary that states the reasons for a change in the figures and the action that's being taken to address them.  Otherwise, all you'll achieve is an unfortunate way of generating action from the content team, who probably won't be too pleased to receive a call from a member of the executive team, asking why their figures are dying, and will want to know why you didn't tell them first.


Another skill comes in determining the key figures to report - the vital statistics.  The paramedics know that time is of the essence and keep it deliberately brief and to the point.  No waffle.  Clear.  The thresholds for each KPI are already understood - after all, they have the advantage that all medical staff know what typical temperature, pulse, blood pressure and blood sugar levels are.  As a web analyst (or a business analyst), you'll need to gain agreement from your stakeholders on what these are.  Otherwise you may find yourself reporting the height and weight of a patient who has severe blood loss, where the metrics are meaningless and don't reflect the current situation.  


Now, all I've covered so far is the reporting - the paramedics' role.  If we were (or are) web reporters, then that would be the sum of our role: to look at the site, take the measurements, blurt out all the relevant figures and then go back to our desks.  However, as web analysts, we now need to take on the role of the medical consultant, and start looking at the stats - the raw data - and working out why they're too high (or too low), and most importantly, what to do about them.  Could you imagine the situation where the consultant identifies the cause of the problem - say an infection in the lungs - and goes over to the patient, saying, "That's fine Mr Smith, we have found the cause of your breathlessness.  It's just a bacterial infection in your left lung."  There would then be a hesitant pause, until the patient says something like, "Can you treat it?" or "What can you do for me?".  


Good web analysts go beyond the reporting, through to identifying the cause of any problems (or, if your patient is in good health, the potential for improvements) and then working out what can be done to improve them.  This takes time, and skill, and a good grasp of the web analytics tool you're using.  You may have to look at your website too - actually look at the pages and see what's going on.  Look at the link text; the calls to action; read the copy, and study the images.  Compare this with the data you've obtained from your analytics tools.  This may not provide all the answers, so you may have to persevere.  Go on to look at traffic sources - the referrers, the keywords, the campaign codes.  Track down the source of the problem - or the likely causes - and follow the data to its conclusion, even if it takes you outside your site to a search engine and you start trying various keywords in Google to see how your site ranks, and what your PPC actually looks like.


Checking pages on a site is just the equivalent of a doctor actually looking at his patient.  He may study the screens and take a pulse and measure blood pressure or take the patient's temperature, but unless he actually looks at the patient - the patient's general appearance, any wounds, scars, marks, rashes or whatever else - he'll be guessing in the dark.  This isn't House (another medical drama that I never really took to), this is real medicine.  Similarly, doctors may consider environmental factors - what has the patient eaten, drunk, inhaled, come into contact with?  What's going on outside the body that might affect something inside it?


There's plenty of debate about the difference between reporting and analysis - in fact I've commented on this before - but I think the easiest answer I could give now is the difference between the paramedic and the doctor.  What do you think?