What goes into your performance marketing dashboard?
“You need to know pronunciation to search the right word in the dictionary”. I heard this once from someone and since then I can totally relate to it whenever someone discusses the marketing dashboard.
After having used the best of the tools such as Tableau, QlikView, Klipfolio and many more custom-developed BI tools, the holy grail to find the right dashboard is still on. What I realized that dashboard becomes better and better only if we input what we want to look at clearly otherwise it becomes a fancy exercise with expensive affairs to manage.
To simplify, one should look at fewer and independent metrics and not too many dependent metrics which might make the numbers look very confusing and clumsy. One should be very clear about what do they want to achieve from these dashboards. Many a times, what I have seen is that it starts with few snapshots and later on more and more team members across different functions keep on adding multiple metrics to the extent that it becomes too complex to even make any sense out of dashboard.
Having gone through the cycle many times, I see a classic mistake is that generally, dashboard creations are on the go exercise and usually starts with analysts trying their hands without much inputs on what is the end outcome? This results in input based dashboard which ends up showing information which most of the time you are already aware of.
Since you are already aware of the content, the end-user loses interests over time and start exploring new tools with better UI usually. The cycle continues and analysts keep on learning new tools at the expense of productive time that they can put into insight generation.
I struggled with this in early days of my career my couple of major E-commerce companies in India. The organizations were using more than three-four visualization tools, however, KPI reviews were still happening over excel and there was another classic discussion that one team’s data would not match with another team’s data leading to different goal tracking and discussion usually shift as to how do we correct this data rather than discussing the output.
The solution to this lies in changing the dashboard to Output driven dashboard and the rest all can be derived from these outputs. E.g., one of the metrics that the market development team would track is that how many active sellers do they have on the eCommerce marketplace? This I believe is just a vanity metric as this would change every day depending on how do you define active sellers? some would define active as 7 days, 15 days or 30 days.
I would approach this little differently as to what is that % of sellers getting orders in a certain period among all the sellers registered? This will tell me what is the health of marketplace and if enough % of sellers are getting orders or not or contributing to overall order count.
Similarly, on customer side metrics, one should definitely look at customer cohort to get an insight on overall business health. Just by looking at new customer acquisition or retention in isolation will not give a true picture of seasonality driven business. If sales team is looking at GMV data, one should definitely look at percentile distribution to understand what categories or set of customers are contributing to sales.
There are several such examples that we can go through and most of them will point towards how to look at data differently or in a simple yet effective manner. There are multiple ways to look at same data set and generating real insight depends on right set of metrics and not just by picking generic metrics without understanding them how and which one to use?
We have helped many startups and mid-size companies in the past to simplify complex looking dashboard into simple clipboard which multiple teams can refer to and have a symmetry on their understanding.
If you have any opinion or want to discuss this further, you can write to us – Virtualcoffee@unravel.media