Manual reporting set the pace
Major.app collected Spotify playlist data by hand, moved it into spreadsheets, and emailed reports to clients. Each client took 40 hours of reporting work per month. Data entry used 80% of the team’s time. Adding a client meant adding more collection work, which left less time for analysis.
The core choice was to collect data on a daily schedule, then let people read it when they needed it. If the team waited until report time to gather each playlist’s numbers, the manual work would remain. We built a backend that gathers playlist rankings and follower counts each day, with country tracking, keyword analysis, and competitor monitoring. It handled millions of Spotify data points per day.
Collection and reporting had separate jobs
The system used a Xano backend, third-party APIs, and a WeWeb frontend. The backend gathered and organized the data. The dashboards gave Major’s team and clients a way to see it. This split meant a client could use the reporting view without asking the team to rebuild the data by hand for every report.
Users can choose a playlist and target countries. The platform then collects daily rankings across those markets, plus follower and campaign data. Major expanded country coverage from 6 to 186 without adding staff. That growth came from automating repeated collection, while keeping the selected countries as a clear part of each tracking request.
Daily collection also set the freshness of the data. It fits a workflow based on daily rankings and reports, while a continuous feed would require more requests and processing. The collection schedule is part of the product promise. A dashboard must be useful at the frequency the underlying data can support.
Change history helped the team investigate results
The team also needed to understand what changed around a playlist’s performance. Staff can record changes to ads or keywords, and the system shows those notes on ranking charts. A note gives the client a timeline to compare with performance data. It cannot show on its own that an event caused a change.
Keeping that distinction in the product leaves the interpretation with the team. A ranking can move after a keyword change while other factors change at the same time. The history gives an analyst a concrete starting point for investigation without turning the order of events into a causal claim.
More coverage still needs an operating plan
Reporting and analysis fell from 40 hours to 2 hours per client each month. The system reduced the manual work and let the team serve more markets without adding staff. Staff count is one part of operating cost. Broader coverage means more data to collect, so country and playlist scope should follow client needs. API use also belongs in the operating plan as coverage grows.