Share in our experience of customer insight and data management

Back

What does $10M and crying over onions have in common?

Published: Monday, 3 October 2016 by Stewart Hanna, Snr Sales & Business Development
Big Data AnalyticsContextual Marketing

Celebrus Technologies is a patented platform which can capture every interaction individuals perform, and experiences they have, across devices, at scale, in real-time; all tagging-free. Most clients want to have a dialog on how they can improve insights about individuals and how that helps them meet their business objective. As part of these discussions frequently we help clients navigate the layers of tags and the complexities associated with tagging. In this post I'll define what a tag is, peel back the layers of this onion and discuss the ROI associated with their development and deployment.


Let's start with, what is a tag?

In its simplest form, a tag is a piece of code, generally JavaScript (js) that executes in the Web Browser to collect data about current state or an action the user has just performed. Tags commonly collect data from Page Views, Clicks, Fields Interactions, Form submits etc., driven by the user, that deliver data representing interest in a Product, Intent to Buy, a Need or Behavioral trait. Loosely defined, if it happens on your site it’s called 1st Party data and if it happens on someone else’s it’s 3rd Party. So for example, if you need to collect data from a specific form field as soon as it is typed, below is the code you need to add for every field, on every page.

function() {

var field = {{Form Element}}.querySelector('#inputFieldId');

return field ? field.value : undefined; }


The same equally would apply to a Native Mobile App (iOS, Android, Windows), but for Apps you leverage native code or a Software Developer’s Kit (SDK). The concept of tagging still applies, but in order to collect a page view stat or data from a field....developers write native code. The level at which a common model is implemented between JavaScript and SDK collection methods can vary widely.


Not all tags are created equal and it’s difficult to address the span of functionality available in the market within this post. For example, some require zero effort to develop or manage, while others are complete black boxes leaving the enterprise zero visibility into what they collect and how that impacts the website performance.


At this point, you're starting to add up in your head the complexity of this onion and rough costs associated with your own tagging efforts. Many of our clients have already done the math and they quote hours, days, even weeks "per tag", counting them into the hundreds and thousands. Added onto this is the business cost of realizing you’re missing data and cannot analyze what you don't have – feedback from our clients is that this previously missing data is often found to be extremely valuable when made available. Tag planning is no simple task:  solution design for a tag, model data collected, coding, integration, testing, tuning, and finally deployment of said tag to the website all take time. Adding it all up – the number of tags x development time x $$ = your invested sunk costs. Tag Management Systems have a role to play in addressing the complexity and effort of tagging, especially when considering the number of third party tags, for example advertising, also on most websites today.  To prove that point Tealium has done a good job of posting online a ROI calculator to tally up these costs which you can use to perform the analysis yourself.


If you use this tool or ones like it, be careful, however, to understand which layers you’re counting when they ask for the Tag Count. For example, Tealium says count the number of tags on your website via Ghostery, then use an average of 8 hours per month to manage each one of them. Counting tags like this is great from a Tag Management POV, since they are only looking at the aggregate level of each vendor tag, or that some of these tags are simple in nature used for advertising. But to perform this analysis effectively, you need to account for the effort associated with each and every discrete tag, or tag within the tag. What’s the impact of that? Let’s use Tealium's own website as an example.

They have 22 tags deployed, at 8 hours per month and using an average developer cost of $90,000 per annum, the calculator gives a total figure of $456,192 per year for your hidden cost. On face value that makes good sense if you're only accounting for the effort to deploy / manage each tag in your Web environment and Tealium would be a wise investment.

But what happens when you start to peel back the layers of the onion? You realize that Google and Adobe do not collect individual level interaction data across the complete customer journey for every view, click, field, form, gesture etc.; and that they don't handle Single Page Applications / AJAX events well; and that they don't deliver real-time data via a common individual level data model. This means you are responsible for developing new tags, extending the data layer, building out the data integration and many other tasks. On top of this is the frustration of waiting for developers to work through tagging projects, code freeze periods etc.  But putting those additional challenges aside for now, let’s take another look at that ROI Calculator. Instead of 22 tags, it’s more like 500, at 8 hrs a month, and you’re now looking at a hidden cost of $10M a year…let alone all the other costs around employing a team of developers to do this work.


Let me know when you've stopped crying?

The key point I'm making is when an enterprise evolves past standard web analytics and realizes the importance of collecting individual level data at its most granular level in order to get serious about Customer Analytics and Digital Transformation and customer-centric omnichannel customer service, sales and marketing, then they really need to peel back the layers of tagging to understand the true effort required going down that route.

 

 

×

Privacy settings

At D4t4 we are all the about the data. We are serious about data protection and your privacy so we will only collect your personal data and use it with your permission. We use cookies to collect statistics to optimise website functionality and deliver content tailored to your interests.

Our three categories of collection are detailed below.

Essential browsing only We will only collect the essential data required to enable core site functionality. We will not collect any personally identifiable information or behavioural data.
Browse anonymously We will only collect your browsing behaviour on the website to help understand our customers' needs and improve the experience for everyone. We will not collect any personally identifiable information so we won't know who you are.
Personalised experience We will only collect information that allows us to identify you and make your browsing experience as smooth as possible by remembering your log in details and saved items. In the course of dealing with you, we may need to pass your personal data on to third-party service providers contracted to D4t4 Solutions.

You will be able to change your options at any time by clicking the Privacy settings link and our full Privacy Statement can be viewed by clicking the relevant link.

v20180607