The construction industry has long been viewed as traditional, with many companies still relying on paper ledgers and fax machines to run their operations.
As someone who grew up around trades and construction, with family members in the industry, I’ve always been fascinated by the intersection of technology and construction.
This is where I’ve found my niche as a data analyst at a construction tech startup, working to bring modern solutions to an industry ripe for innovation.
Why Construction Needs a Tech Revolution
I believe bringing new technology to the construction industry is one of the most exciting opportunities in tech today.
While we’ve seen incredible innovation in building physical infrastructure, the industry’s digital infrastructure often lags behind.
You’d be surprised how many construction professionals still use paper-based systems and outdated technology for critical business processes.
This resistance to change isn’t without reason. Construction professionals are practical people who rely on proven methods—they do things because “that’s what they’ve always done.”
This creates both a challenge and an opportunity. The challenge lies in convincing industry veterans to adopt new systems.
The opportunity is in creating solutions that are so intuitive and valuable that even the most tech-resistant professionals can see the benefits.
What excites me most is building something for the construction industry that makes operations more efficient.
While the world probably doesn’t need another AI-powered CRM, construction companies desperately need tools that can streamline their workflows and bring them into the digital age.
It’s about bridging that gap between traditional practices and modern technology.
Data Challenges in an Early-Stage Construction Tech Startup
Running analytics at an early-stage startup comes with unique challenges, especially when you’re targeting an industry that’s not traditionally tech-savvy.
One of the biggest hurdles we face is working with limited data sets.
When you’re just gaining traction in a market, the numbers can be misleading.
For example, if we haven’t fully launched in Iowa but see engagement increase from one view last week to three views this week for a facility listing, that’s technically a 200% increase—but the volume is so low that it doesn’t necessarily indicate a trend.
This makes it challenging to be a truly data-driven company in the early stages.
Unlike established tech companies analyzing millions of rows of data, we often need to take a more granular approach.
Sometimes this means doing a row-by-row breakdown of our data, which isn’t as scalable as creating automated dashboards but gives us more accurate insights at our current stage.
Another challenge is finding construction companies online. Many don’t have a strong web presence—they’re not on Google, and their digital footprint is minimal.
This requires creative approaches to data collection, like scraping industry association member lists or joining organizations to gain access to potential clients who aren’t easily found through conventional digital marketing channels.
Despite these challenges, we’ve found that LinkedIn is where many construction business owners are active, alongside Google Maps (for local searches) and Instagram.
We’ve experimented with various content types, from blog posts to podcasts and videos, measuring engagement across platforms to optimize our approach.
A Day in My Life as a Construction Tech Data Analyst
My typical day spans a variety of responsibilities—far beyond what you might expect from a traditional data analyst role.
This diversity is common in early-stage startups, where everyone wears multiple hats.
Most days involve building and maintaining dashboards that track our key metrics. I handle numerous ad hoc data requests, like pulling engagement numbers for a particular vendor or measuring the impact of a recent conference appearance on our metrics.
A significant portion of my time goes to operations support, helping team members with our internal systems and working on automation.
Rather than having people manually input data, I create automated workflows that save time and reduce errors.
For instance, today I’m cleaning up our HubSpot CRM, ensuring that when someone registers on our website, a record is automatically created in HubSpot.
I’m also reconciling data to eliminate duplicates and standardize vendor names in our system, making sure each company is properly linked with all their facilities.
Data cleanup is a constant task—whether it’s merging similar entries, standardizing naming conventions, or ensuring data integrity across systems.
While not the most glamorous aspect of data analysis, this foundational work enables more accurate reporting and insights.
I also use tools like BigQuery for data analysis, Looker (though we’re transitioning to Metabase for better accessibility to non-technical team members), and various Python libraries for tasks like web scraping and PDF parsing.
We’ve even started leveraging OpenAI’s developer API to augment some of our data work.
Creating a Data-Driven Culture
One advantage of working at a startup is that everyone is generally open to using data to make decisions.
If our metrics show a marketing campaign isn’t performing well, we quickly pivot to A/B testing different headers, content copy, or calls to action.
This data-driven culture means I don’t have to convince people to trust the numbers—they already do.
The challenge is ensuring the data we present is accurate and actionable, especially given our small data sets.
When you’re working with limited data, context becomes even more important.
It’s my responsibility to provide not just the numbers but the story behind them, helping the team understand what actions we should take based on what we’re seeing.
Conclusion
The future of construction technology is bright.
As more companies recognize the efficiency gains and competitive advantages that come with digital transformation, adoption will increase.
My goal is to be at the forefront of this change, creating data solutions that aren’t just innovative but practical for the real-world needs of construction professionals.
By bridging the gap between traditional construction practices and modern technology, we can help this vital industry become more efficient, safer, and more profitable.
And for a data analyst who grew up around construction, there’s nothing more satisfying than seeing that transformation happen one data point at a time.