A member of your IT team comes to you and says, “I think we need to build a system that collects detailed data to the level of the individual interaction, from all our digital channels, to feed our customer analytics and personalisation systems”. You might think it feasible and probably the correct thing to do, as todays Web Analytics systems could do a better job of providing you with the data you need, in the format you need and when you need it. So surely it can’t be that hard?!
It was perhaps a perfectly reasonable statement a decade ago, in the heady days of web 1.0 when there was a single digital channel – i.e. a website. With those HTML sites it was pretty easy to pop in a few pixel gifs and receive an insight on page hits, user journeys and which page people dropped off the website, etc. all with a view to building a better website and driving up conversion rates.
Today however, the world is a very different place and we are now in the age of web 2.0 – or even 3.0 – and there is an absolute plethora of digital channels with which to engage with your audience. The data collection mechanisms that served so well in the early days – single pixel gifs, JavaScript tagging and packet sniffing – are now seriously devoid of the required functions to enable you to keep up with your data collection needs for this ever changing medium. But it is not as simple as instructing your IT team to build a digital channel data collection system that has to cater for all your digital data streaming needs. To deliver the level of detailed individual data that businesses of today require in order to make informed decisions is a serious challenge. Over the years data collection technology providers have had to constantly adapt to each and every platform they found themselves dealing with, in order to be in a position now that enables the delivery of interaction behaviour data to customers in real-time, regardless of channel, technology or platform.
Ask yourself this question – if the development teams of these multi-million dollar Web Analytics corporations are struggling to build technology that gathers data across multiple channels, what chance do the majority of organisations have?
In the old days of web 1.0, you placed a single pixel gif’s on a page and built yourself a set of page view stats and some user journey information. The value of this was always limited; however, this of course led to a clamour for more information on the visitor. To achieve access to this data, 99.9% of web analytics companies devised a method of client-side data collection, commonly known as JavaScript tagging, which was designed to try to help you understand in-page activity as well as the traditional page to page tracking. Fast forward a few years and web analytics was big business with consulting organisations earning hundreds of thousands (if not millions) of dollars from their customers, assisting them in conceiving and implementing a tag strategy to extract website visitor data.
Then we saw the introduction of Tag Management Systems (TMS), originally to assist with the proliferation of marketing affiliate tags, but latterly for Web Analytics systems to try to overcome the tagging burden which all of the additional JavaScript solutions bring. In a blog by Gary Angel, the award winning DAA contributor and CEO of digital measurement and data analytics consultancy Semphonic, he described a TMS as a fix for the governance issue. It doesn’t however, deal with the underlying issue, i.e. that of needing to know what data you want in the first place, which is nigh on impossible, and then having to code for it, albeit in a separate GUI rather than the website itself.
Nowadays websites are different beasts. We are not talking about a single website built in HTML any longer. Over recent years, we have seen the introduction of Web 2.0 in the guise of Flash, Flex, AJAX, Silverlight, all of which brought a new level of flexibility for the development of websites, but also huge challenges for the data collection companies.
Skip to today and we are confronted with even more complexities i.e. mobile customer interaction through the use of apps and interaction with social media in the guise of Facebook, Twitter, Google+, LinkedIn etc, along with individuals using multiple devices to access the internet – each in a different way according to time of day, location, and wireless availability.
Where the real value lies now is in being able to piece together and understand this complex puzzle of individual customer interactions, in order to effectively engage them at each point of the sales cycle. We are in the era of real-time website personalisation and personalised marketing using individual-level data that enables you to link all the devices and histories of interaction together into a single customer view.
Now you might think that I’m living in cuckoo land, but analysts have been preaching the concept of a single customer view for years; and there is no doubt that the explosion in Internet-connected devices and diverse channels is creating a huge challenge for organisations to achieve that vision.
Through having the capability to understand individual customer interactions with an organisation across all devices, and by putting the pieces of the puzzle together to create one real person, you can begin to treat customers as one coherent individual across all the channels used to interact with your organisation. Whilst some of us may enjoy a DIY project – you might be wise to leave this one to the professionals