Today, we’ll share 10 tips to help you succeed in digital analytics, each paired with an image to help you comprehend and remember this advice. We hope it will help you go further with your analytics activities!
1. Start with your site’s main goal.
Each website has a goal, and was created for that goal to be reached.
Everyone knows that the aim of E-commerce sites is to sell products. It is sometimes a little more difficult to identify the main goal for other types of sites. Too often people forget that the main goal for a BtoB site is to retrieve professional email addresses.
Before you start analysing your site’s performance, ask yourself the following question: What is your site’s “field goal”?
2. Monitor micro-conversions.
Internet users can perform many different actions during their visit. For example, subscribing to a newsletter, signing up for the next event, downloading a white paper, and watching a product presentation video are all actions showing that a user is interested in the products and services you have to offer.
These are micro-conversions which Internet users go through before the macro-conversion – a purchase or a contact request, for example.
When it comes to analysing customer browsing paths, think of the game of hopscotch. Be sure to analyse all different steps users take before they reach the end square.
3. Measure to improve, not to judge.
Data reflects what is happening on the site. The reflection that we see might be flattering or show signs of underachievement.
It is important to point out that the purpose of measuring is not to find what is wrong, but to find areas where it is possible to improve results.
Don’t use data to show the small bird that it’s far from being a big eagle, but rather to explain how it can become stronger.
4. Ensure data quality.
A tagging or data collection problem may damage the quality of your data.
Poor data quality may lead to an incorrect analysis of the situation. The work of analytics is brought into doubt and the significance of web analytics is disputed.
Any data quality controls must be carried out before any web analytics work starts.
Your data does not have to be as accurate and exact as a Swiss watch, but you should strive for an acceptable and reasonable level of data quality.
5. Define analytics goals.
Exploring data without any real particular objective in mind can sometimes lead to the discovery of very informative information. However, most of the time, this leads to points of no-return where the analyst who no longer knows what is being searched for loses all hope of finding anything.
The question or problem must be accurately expressed. Start analysing once you have a clear view of the question(s) to be answered.
You’ll then know where you want your analysis to go… just like Arthur and Marilyn.