Increasing efficiency and reducing waste in digital analytics

Increasing efficiency and driving better digital performance is the essence of digital analytics. As analysts, that’s what we do: we look at digital data and try to understand where the threats and opportunities are for a business; we do this based on data, experience, judgement, common sense and business acumen. But here is the paradox: we, as an industry, suffer from a lack of efficiency and we produce a lot of waste. So I think that if our aim is to truly drive more efficiency for businesses then we have to look at ourselves and start reducing waste.
There are a few causes of this waste in my opinion. To me, the primary one is the obsession for digital analytics tools and I think we are all guilty of that one by the way. Then the other reason for this is a lack of processes for all the components of digital analytics. Last but not least, the lack of independence for the digital analytics function is also an issue.

1)The obsession for tools: come on vendors, you have to become more involved in the digital analytics journey!
I feel quite passionate about this particular topic which is why I had already written a blog post about this just over a year ago here ; if you have not got the time to go through this then as a summary I talk about some of the key people and process related questions your organisation needs to ask itself before purchasing an expensive digital analytics tool. When a business ends up buying an expensive digital analytics tool without really answering some of the questions I list in my previous article then not only does the business end up wasting money but most crucially there is significant waste driven by implementing a digital analytics solution which is not adapted to the business. There is also time wasted on training everybody up on it…Ultimately, this is time not spent on driving actionable insights.
Now, let’s say you have asked yourself/the organisation the right questions (around people and process) before acquiring a tool and you have decided that such purchase makes sense from a business perspective, great. But that’s when the troubles potentially can start and when more time is going to be wasted, and particularly the digital analysts’ time…
As a digital analyst, how much time have you spent troubleshooting your digital analytics tool? For example how much time have you spent trying to understand how the “Intelligent” marketing attribution filter really worked in Yahoo Web Analytics? How much time have you spent answering questions from the wider business on why, on Site Catalyst, the tracking code report would not match the marketing channel report? How much time have you spent figuring out why the direct traffic source in Tagman is over-inflated? By the way, if you are interested in the answers, then please ask me by posting a comment and I will answer but hopefully you get the idea: too much time trying to figure out discrepancies, oddities and lacks of consistency. Now, I do think these inconsistencies are not a problem in themselves as long as you know why but until you do, you will be spending and wasting a tremendous amount of time and energy finding the answers to all those questions.
I believe that part of the solution needs to come from the vendors themselves.
I do think they need to do more for clients, they have to be present throughout the whole digital analytics journey, not just at the beginning and on an ad hoc basis once the solution has been implemented to answer basic questions. I really think that a very good way for them to help us succeed consistently is to provide collaboration platforms where clients can share pains and eureka moments with each other and with the vendors themselves obviously. And guess what? Vendors would hugely benefit from this because that would free up some of their support staff. The other advantage of bringing in more collaboration is that this would enable vendors to create a co-creation environment between clients and themselves. Of course, we know there are digital analytics forums and knowledge bases dedicated to specific digital analytics tools and sometimes these have the answers to your questions but this is far too ad-hoc and inconsistent in my opinion.

2)The lack of processes in the digital analytics journey: a focus on the tagging “nightmare” we have all experienced.
I won’t go through the lack of processes throughout each of the digital analytics components here; instead, I will focus on tagging: the start of the data collection process, a key step, often neglected. Part of the reason for this can be down to high expectations coming from the wider business which wants to start seeing data ASAP after signing a big cheque to a digital analytics vendor. But that’s not the main point I want to make here. The point I am on about here is the lack of ownership around tagging. It does not mean that tagging does not get done, it means there is no process and no accountability for it; a tagging task is just another IT task amongst hundreds of other IT and digital development tasks. Even worse that that, it also means there is no tagging knowledge collected, documented or shared. And what’s wrong with this? A huge amount of waste once again as tagging tasks need to be re-done, re-taught multiple times.
It is not uncommon for the digital analyst to end up owning tagging for at least 50% of it. Personally, I have spent a huge amount of my digital analytics career looking after the tagging side of things: investigating digital analytics code, writing technical specs for developers, as well as testing their implementation. Not coming from a web development background I have learnt a lot during that process but I also had to go through huge pains and it meant that during that time I was not driving better digital performance, I was only making sure we were collecting data and the right data.
So, how do we make sure that tagging is finally 100% owned and managed in a business? This leads to my third point on why there is still too much waste in digital analytics: we have got to become more independent.

3)Digital analytics suffers from a lack of independence and needs to be a department in its own right.
Yes, this is high time for digital analytics to become its own department, not part of Marketing or IT or Operations (or even Finance…) Why is it so important? Because by operating independently from the other key business functions, digital analytics will become less ad hoc, more strategic and more visible. Let me explain…When digital analytics is part of Marketing, what type of analysis do you think the digital analysts will perform? Marketing analysis, that’s right. When digital analytics is part of Operations? Probably internal promotions type analysis or time series analysis after a new digital platform implementation (but not Marketing analysis). It does not mean that the digital analyses performed from within a department are not relevant and useful, they are but they are dictated by where you are in the organisation so they are bound to be focusing on one aspect of the organisation and one aspect only. And by the way, I think by being a function in its own right then a lot of the tagging challenges will disappear.
The other significant benefit that would be achieved would be the ability to create and manage your own digital analytics processes which would be the pillars of the digital analytics department. By processes here, I mean processes around the 6 pillars Stephane Hamel is describing in his great Econsultancy article .
As always, thank you for reading and I am always interested in hearing your views so do comment and let’s get chatting!

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