Anyone who ever analyzed data from digital events knows about the problem: regardless of using an in-house platform, solutions from market leaders or a niche vendor – data management and reporting are not in the focus of the respective providers. This is why teams often struggle with their own analysis right at the beginning of the project when they open the data export.
In many cases they see tons of raw data, spread across multiple table tabs with a multitude of implausible or missing values. This is more reminding of a data chaos than a structured data set that can be worked with in a meaningful way
But those who manage to fight their way through also know that there is a lot of useful information hidden in this data – it’s just that the effort to get to it is very high. Data formats have to be formatted, values in cells have to be corrected, replaced or split, columns and rows have to be partially transformed – even before a single analysis can be run. With larger data pools, data preparation can take hours and even days – for just one single event. If events are run on different platforms, the effort starts each time again. Because every data export has its own pitfalls. Therefore the learnings from platform A can only to a very limited extent be transferred to platform B. So what can you do?
Excel is a powerful tool for data analysis. Macros can be used to automate most of the data preparation and analytical tasks. However, programming macros requires in-depth user knowledge and is time-consuming. This can be solved by numerous analytics platforms and tools. They have the central advantage that many data preparation tasks are already functionally available. Data, times, user IDs? Are reliably recognized and directly formatted by most solutions. Creating new variables, merging cells, replacing values? Can be done by drag & drop. User structure by country, region or business unit? Works almost automatically. Once familiarized with the software, users save an enormous amount of time and nerves. Another advantage: the moment you analyze the data, you create appealing charts that you can immediately share as reports. By means of visual analytics, insights are quickly and easily made available to stakeholders.
In the digital environment, pretty much everything can be captured: every click, every interaction, every download. The data volumes thus become complex very quickly and complicate the view of the essential. Especially for events with a lot of content. Therefore, consider in advance which data is important to you and, above all, why – and not just for a single event, but preferably holistically for your entire Engagement Marketing.
Which objectives do you pursue with your events (virtual, physical and hybrid)? Which results do you need to achieve in order to reach your objectives? And what data do you need for this?
Once you have identified KPIs for Engagement Marketing, there are a number of key benefits:
Data from virtual events has a high informative value. Analyzed in a meaningful way, it provides you with great transparency about the behavior of your target group.
However, what data from platforms cannot tell you are the reasons, motivations and needs behind the behavior. For example, you know that users have clicked on videos, loaded documents and participated in discussions (always anonymously, of course). Or how long the sessions of individual users were, whether there was more interest in live or on-demand content.
But what you don’t know: Was the event worth the time invested by your target groups? Did they learn something new? Were you able to evoke emotions?
To be able to answer these in-depth insight interests, it is essential to also collect participant feedback using smart surveys. This enrichment of digital behavioral data enables you to assess the success of your virtual events holistically.
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