Analytics is the basis of all product decisions. However, the data must be tailored to specific business needs and reflect real metrics that can be confidently relied upon.
In this article for GoPractice, Denis Elkin, CMO of Alps2Alps, highlights what truly matters in marketing analytics, what’s not worth your resources, and how to design dashboards that benefit your team at every stage of your product journey.
Different stages of a company require different analytics
Pre-PMF (Before product/market fit)
At this stage, your focus should be on discovering your audience and experimenting with acquisition channels. Optimizing marketing spend isn’t critical here, so the analytics can remain relatively simple.
Post-PMF (Scaling up)
As the company scales, analytics must meet more complex requirements—such as leveraging A/B tests and expanding business intelligence (BI) functionality. These tools are crucial for managing growth and optimizing marketing expenses.
As your company grows, data engineering talent and report automation capabilities become increasingly crucial.
Core principles for building useful dashboards
Fast loading
Dashboards must load quickly, or people will avoid them.
Real-life example:
If a dashboard takes over a minute to load, and every filter adjustment triggers another lengthy wait, users will find workarounds. For example, frustrated managers will spend hours each week exporting raw data to Google Spreadsheets to create pivot tables. While the dashboard exists, no one can use it effectively.
Clear purpose
Each dashboard should answer specific business-related questions. Don’t cram too much information into one dashboard—it becomes cumbersome to use and slow to load.
Ideally, users should only see the columns and data relevant to their purpose at any given moment. A skilled BI engineer can configure this in tools like Tableau.
Tailored dashboards for different users
Marketers, managers, and executives have different needs, and their dashboards should reflect that.
