Free your Dev team by embedding Self-Service Dashboarding

Your customers want to access their data to drive decisions. This means you’ll need to add dashboards to your product, and you might have already done so. However, analytics can be a never ending story, customers keep asking for more charts and insights. This is a lot of development work – manually adding more dashboards, some even for just a single customer. 

This is a problem of resource allocation. Who is going to build the dashboards? There are two solutions: 1) you hire a data developer to work full time on the dashboard request; or 2) you add self service dashboards to your product so customers can do it themselves. In this article, we’ll go over the advantages and disadvantages of the second option, adding self service. 

Self service Dashboards Pros and Cons

This is how adding self service BI stacks up against other approaches.

Advantages: 

• It is scalable.
• Customers know their own data and specific setup.
• You can have different models or custom fields per customer.
• You can view what dashboards customers build and ship them in the standard set.
• Customers can build dashboards to their specification, no need to discuss with your dev team each time.

Disadvantages:

• There is a learning curve for your users to start building dashboards.
• Your users can break the production database with a heavy dashboard or a large query.
• If you have a complex data model, then your users get lost in what columns to use in charts and tables.
• Your customers start asking for data fields that you haven’t properly modeled yet, causing yet again an overflow of support tickets. 

Adding self service dashboarding to your SaaS product allows your users to build their own dashboard. However, as we’ve seen above, this comes with some disadvantages. The solution to these is to have an easy-to-use, intuitive self service product. This has two parts. First, you want the product to guide and help your users to build their dashboards. Secondly, you want to have a robust data model. This data model should be easy to understand, preferably a dimensional model. Also, it should be complete, correct and fast. This way, your users will be happily building dashboards and not ask too many support questions about it.

Conclusion

In this article we’ve shown that adding self service to your embedded dashboards is a good approach to solving the inflow of custom dashboard requests. Most importantly, it is scalable. However, self service can be difficult for your users depending on how good your data model is and how data-savvy they are. This means that the fundamentals should be good: having a pleasant dashboard-editing experience and a robust model.