The web is full of data, a lot of data. Thus, event measurement for the same user or group of users requires data from different sources to be analyzed correctly. For example, the analysis of a marketing campaign for an online retailer should be able to rely on data from:
- advertising platforms to know the costs of a campaign;
- DCM type conversion platforms, i.e., web analytics platforms (Google Analytics, Adobe Analytics);
- email platforms;
- customer relationship management (CRM) platforms, to confirm the proportion of prospects that have converted;
- any other sources of data, whether directly related (via any key) or indirectly related, in which case trends and variations will be observed.
What do the data actually reveal?
To make these data speak, figures relating to performance indicators, such as the ROI (return on investment), the cost per acquisition, or the margin released, are extracted. But to have the complete history of the data, it is necessary to link this data between them: we will be able to know that the results of the campaign X in Facebook correspond to X sessions in Google Analytics, and generated X dollars of sale via the internal information system.
Since the 2010s, the emergence of data visualization and unification platforms (thanks to connectors making links with other platforms) such as Datorama, Tableau or Power BI greatly democratize the use of dashboards. Admittedly, their use is now open to a much larger pool of users than before. However, it would be wrong to claim that anyone can correctly use these tools without having any notion of data modelling. Making effective dashboards requires thinking and planning before they are created. Here is an overview of the major issues in the practice of dashboards.
What are the benefits of data visualization and unification platforms?
Mainly to save time! Doing campaign reporting is tedious because a lot of manual tasks are involved. In addition, the collection is to be repeated each report because the data are fixed in time. For example, creating a report once in a visualization platform can automate this task, and thus spend more time analyzing the results.
But beware, these benefits have some pitfalls. The main risk would be to waste your time in “plumbing” technique rather than analysis results. Like an automobile, the costs associated with a dashboard are not limited to just creating it. Maintenance costs are to be expected because the raw material, the data, evolve, and therefore periodic adjustments are necessary. Adjusting the names of campaigns, reviewing the formulas that manage data groupings (channel, tactics, segment…) are all tasks that can encroach on the analysis time.
The data structure and processes in place are of paramount importance to the success of a dashboard. On the one hand, they enable operational efficiency that makes the dashboard credible: display accurate data. Without maintenance, a dashboard simply becomes obsolete. On the other hand, maintenance costs can be very high if no governance framework is defined.
Issues of use: define the framework of your reporting
The following two points are important in order to maintain the effectiveness of your reporting.
1. Automating reporting is not enough to automate data analysis
A major misunderstanding on the subject of data analysis and representation is that the confusion on two tasks, reporting and analytics, which do not have the same goal at all.
A reporting platform is used to automate a company’s reporting, that is, to make data easily accessible, in the form of consistent sets; whereas the analytics consists in the fact to explore the data and to extract insights.
Most organizations want dashboards to extract insights. So it’s analytics they need and not reporting. Your KPIs must measure the health of your business goals, not spread your data. A dashboard too detailed and without KPI, with only metrics, will be more related to reporting than to analytics, and will be useless to extract insights because they will be hidden behind the tide of figures put forward.
2. These platforms should save you time, not the other way around: the variables and processes to consider
Your KPIs are chosen based on your business objectives? Now it’s time to segment them. But beware! How far do you need to go? Always keep in mind that doing a dashboard has two purposes:
- Show the right questions – A dashboard rarely gives answers, a good dashboard raises relevant questions that will help you better understand your performance.
- Save you time – The danger here is to want to do something too complex, which in the end will be too granular to bring real added value and possibly drain all your time in maintenance, to the detriment of the analysis.
What are the best practices to follow?
It is important to think about the basics of performance measurement: what do you really need to evaluate your performance? We are talking here about KPIs and not about metrics, which you should choose in the number of 2 or 3. Then, segment these metrics by some main segments, and the architecture of your dashboard is made. This exercise is usually done during your KPI framework.
Once you have chosen your KPIs, you have to select the metrics that will cut them out and explain them. Here are some ways to choose them:
- Always keep a link with business purpose;
- Stay simple;
- Choose metrics that push for action;
Being transparent: a report whose methodology is specified is never wrong
Finally, it is necessary to choose the right type of dashboard according to the public to whom it is addressed, because the dashboard which answers all the questions of everyone does not exist. Your dashboard will be very different depending on whether it is used by your management (strategic dashboard), whether it is used by your managers to evaluate your campaigns (tactical dashboard) or to monitor your operations (operational dashboard).
The democratization of the tools used to produce these dashboards now makes the practice accessible to all. By following the preceding advice, any organization, from small business to large group, can effectively evaluate its performance against the set objectives, and thus take actions to improve.