4 quick tips to keep in mind with Analytics
1) Check The Source:
Many times we jump into an Analytics tool or process a little too eager for results. Depending on how often we use our tools, how many projects we have, or who used the tool before us, it can happen that something changed on the previous sources we have been working with, for example. It can also happen that we miss a few sources when setting up the process. So before we get too excited, this quick tip number one is just about that: Check the sources!
2) Check The Period:
It happens often that a conclusion is made based in the wrong period. Because we are doing a lot of correlation even outside the analytics tool itself (with offline events, other data sources, and just general knowledge sometimes), it can happen that our assumptions are not in aligned with the selected period for the data that we are seeing. So the quick tip number two is just that, check the period! throughout all elements used in an analysis.
3) Percentage or Total Numbers?
Percentages are interesting but many times they will not give us a true sense of meaning to what we are working with. A small total number can reflect a very high percentage depending on the context of the object being analyzed. That kind of reading can easily be in the way of reaching an actionable insight.
In a quick practical example, imagine comparing 2 brands and their total conversions in comparison to the previous month.
- Brand A: 37% more conversions
- Brand B: 10% less conversions
Now let’s reveal the total numbers to see how it could affect our judgment of what we have seen so far:
- Brand A: 100 conversions last month, and 137 conversions this month.
- Brand B: 1000 conversions last month, and 900 conversions this month.
Clearly Brand B is not doing so bad in comparison to Brand A, is it?
Now, if our analysis aims to understand other aspects of each brand’s strategy, maybe it will find that Brand A has indeed a better strategy and is likely to keep growing and maybe even become bigger than Brand B very soon. The point here is, the percentage alone would not really tell us the entire story. So that is quick tip number 3, check total numbers as well, not only percentages!
4) Indexes, Formulas and Calculations – what’s behind them?
Everyone loves a fancy formula. Yes, “fancy” is the word of choice here. It is “fancy” because it will enhance our initial perception that such number is of higher importance than any other. This is not quite true most of the times.
It can happen often that pre-made formulas found within many analytics applications will be useful in certain cases but maybe not useful at all for our specific case. Formulas can become old and obsolete, and may reflect something that was interesting years ago. Yes, you could get to a point where you will say “that formula is so 1999…” The world changes, the key metrics change, the goals change.
It is key to really understand what is behind a formula when working with it.
A very quick example can be seen in an obsolete formula where brands were checking for “interactions” to their assets against “followers.” So the idea behind the formula was to detect if there was a good amount of interactions compared to the follower base. Then brands started reaching out to a huge amount of people outside of their established follower base, but some of these brands continued using such formulas. Why? how hard is it to simply stop using certain metrics and turn a page into the present moment?
Don’t be afraid to leave obsolete formulas and metrics behind.
Our quick tip number four is then just that – make sure you understand what is behind a formula and that you understand how relevant it is to your analysis!