Data Analysis Case Study: How I Built a Custom Reporting System for Smarter Content Strategy

Data tells a story. But sometimes, the most important parts of that story are the hardest to see.

Over the years, I’ve had plenty of opportunities to work with both quantitative and qualitative data to identify what is working, what is not, and where improvement is needed. But I’ve also run into situations where the data I needed simply was not easy to access. In those moments, I’ve never been content to just work with partial visibility and hope for the best. If the data is buried, I dig.

One of the clearest examples of that mindset came while I was managing social media accounts for Conservice. At the time, we had access to the usual platform metrics like views, reactions, and comments, but I needed a deeper level of insight to make better decisions. We were communicating with nine different audiences, and I wanted to understand which types of content were resonating with which markets, when those audiences were most responsive, and how we could become more strategic over time. The problem was that our social media management platform did not give us the data we needed, and the tools that did were outside our budget.

So I built my own solution.

I used Monday.com and a dedicated social media project board to manually track platform performance and organize the data in a more useful way. I added custom fields for market, day of week, time of day, and content type. I built formulas to calculate average performance across key metrics. Then I created two reporting dashboards that pulled in the data and made it easier to analyze patterns, compare results, and identify opportunities for improvement.

That work gave me far more than a spreadsheet or dashboard. It gave me visibility. With those systems in place, I could establish clearer performance baselines, identify ideal posting times for different audiences and content types, compare what was working across markets, and learn from both high- and low-performing content. Just as importantly, it helped me create content more strategically rather than relying on instinct alone.

The effort was intensive, but it paid off. Over time, we increased our average monthly posting volume from 20 posts in 2019 to just under 40 in 2021, with some months approaching 60. On LinkedIn, our primary platform, followers grew from 3,302 to 4,398. In 2021 alone, average monthly impressions increased from 27,490 in Q1 to 79,018 in Q4. Average monthly interactions rose from 1,261 to 6,409, and average monthly clicks increased from 531 to 4,550. For a niche B2B market, that kind of growth was meaningful.

What I like most about this project is that it reflects how I think about problem-solving. When the information I need does not exist in a usable format, I look for a way to create clarity. In this case, data analysis was not just about reporting results. It was about building a system that made better decisions possible. Once I had that visibility, I could develop the right content, for the right people, at the right time.

Post Time Stats Dashboard Sample