More than just a business buzzword, “Agile” methodology and principles have made their way into many companies’ operations, extending beyond the realm of software development and into marketing, sales and business development activities.
Whether you’re a strict practitioner of Agile methods, or are simply inspired to incorporate some agility into your processes for greater flexibility and productivity, you can apply agile principles to your digital analytics initiatives.
The implementation and tagging phase of your digital analytics project can benefit particularly well from an agile approach.
Implementing a digital analytics solution is often long and tedious, due to the sheer volume of elements to be tagged. Add to that the fact that this operation must be repeated for your different platforms and properties. (Congratulations, you’ve tagged your website! But those iOS, Android and Windows apps won’t all tag themselves. Get back to work!) And, of course, as your business needs and KPIs evolve, your digital analytics tagging must adapt as well.
In a nutshell, implementing your analytics tagging is crucial yet time-consuming… and never-ending.
The good news? Agile analytics can help you make tagging quicker and simpler, leaving you more time and flexibility to continuously iterate and improve.
Here are 4 tips on incorporating an agile approach to your analytics implementations:
1. Set a restricted tagging scope
Resist the temptation to tag everything. In agile analytics mode, you should reduce your scope and tag only what really matters to your performance goals. Not only will you lighten your load of tagging work now, you’ll also avoid being inundated later with masses of data you won’t use or need. To know “what really matters”, always refer back to your KPIs and use those as a guide. Decide what must be implemented at the very minimum to obtain this information, and focus on that.
2. Work incrementally
This may sound surprising, but you don’t need to wait to have everything tagged before you can work with your data. In agile analytics, it’s advisable to break your implementation down into several incremental phases, and start exploiting your data right away. Don’t wait until your tagging plan is fully implemented to start analysing your data. If you want to measure page performance, for example, you can start analysing your visit data, even if you haven’t yet tagged clicks or social media shares. Or perhaps you’d prefer to work incrementally by page priority, first focusing on your homepage, and moving on to medium- and lower-priority pages in subsequent phases.
3. Work iteratively
Your tagging is never set in stone. And you wouldn’t want it to be! Just like any other agile project, agile analytics means studying your needs, defining your tagging plan, implementing it, testing it, and deploying the next (improved) iteration. Count on adding, deleting, and changing things in your tagging as you go.
To make this painless, we’ve developed the Data Manager tool, which gives you full control of your tagging rules. With Data Manager, you don’t need to know how to code, and you won’t need to solicit your technical teams in order to correct and optimise your tagging. Create rules on-the-fly to change how your data is calculated and stored.
4. Don’t forget to KISS (Keep It Simple, Stupid)
Why make things more complicated than they need to be? Take the path of least resistance! If you’re facing a big challenge in your implementation phase, consider breaking it down into smaller, simplified and more achievable tasks. This will enable you to focus on quality, while progressively working on quantity.
We’ve applied this simplification to our own analytics tracking code: The SmartTag is a light and fully modular tag that you can customise to your needs. Build your tag in just a few clicks, adding only the elements you want to measure, with nothing superfluous to weigh it down.
Measure less to measure better
When taking an agile approach to analytics, just remember, by restricting your measurements to areas that are high-priority, you’ll have more time to check, test, and get things right. Reliable tagging means reliable data, which translates into reliable business decisions.
>> Want more advice on tagging with agility? Watch the webinar:
Thanks to Florian Rieupet, AT Internet product manager, for providing the basis of this article!