But I actually think we should turn the focus around. By definition, digital analytics is a business tool. It represents the eyes and ears of marketing strategy, and therefore should be defined by the business and not by the analytics department (with their help, but not led by them).
To explain it, I leave you a korean girl whatsapp number summary of my presentation at the first digital marketing conference held in Pontevedra (Flúor Conference).
Fluor Congress - Pontevedra - Tristan ElóseguiTo correctly define a dashboard, we must start from the digital marketing strategy and select the data sources and metrics that best represent it. Those that best describe the context of our marketing activity, and allow us to make the best decisions.
To understand the role of a dashboard in a strategy, let's look at five points :
I like to approach the definition of dashboard in two ways, or rather in a way that concludes with the key to everything:
It is a graphical representation of the main business metrics, and its objective is to facilitate decision-making to optimize the company's strategy.
An indicator dashboard must transform data into information and this into knowledge for the business.
This transformation of data should lead us to better decision-making. This is the main objective that we must not lose sight of. Something that often happens in this process. We focus so much on the process of creating the marketing dashboard that we tend to forget that its objective is decision-making and not the accumulation of data. But that is another story.
To all this we have to add one more element, since the basis for decision-making is in a good analysis of the data.
What do we need to do a good analysis of a control dashboard?
Well, basically two things:
Correct definition of marketing and business objectives : this is what will mark the path to follow, what will define the success of our marketing.
Definition of macro and micro conversions : we must translate our goals into objective, measurable facts on our website, and also be able to assign them to each of the stages of our audience's purchasing process.
Knowing the context : our results include many variables: market, competition, regulations, etc. Sometimes there are so many that we stop looking. But a good starting point to understand the reasons for many of the variations in the data is in the marketing strategy and its planned actions.
Pillars of data analysis:
Qualified personnel : we must be able to overcome the temptation to think that a measurement tool will solve the problem. The key to good analysis lies in the people who carry it out. They are the ones who transform the data into information and this into knowledge for the company.
To keep the proportions clear, it is estimated that of every €100 invested in measurement, €90 should go to people and €10 to tools.
Data quality : We need to make sure that the data we are analyzing is as close to reality as possible. I say as close to reality as possible because it is normal to see variations in some metrics between the data provided by the analytics tool and internal systems.
In addition to having the peace of mind that we are using the correct data to make decisions, we will eliminate internal discussions about what is the real data and what is not.