Context 

In just under 12 months, we turned fragmented data into $10M in revenue.

We worked with a company called DealFuel are tech marketplace company that went from chaos to clarity—generating $10M in sales and growing MRR from a few thousand to $800K.

Here is what we have done so you can apply it to your business as well asap.

The challenges:

→ Dispersed data across platforms made it impossible to get a full picture of operations.
→ Sitting on loads amount of data but didn't know how to utilize to it's full effectiveness to gain actionable insights.
→ Slow decision-making gut feeling process.
→ Over 100 hours a week wasted on manual tasks like searching, analyzing, and presenting data.
→ Bottlenecks in the all over the company process went undetected, dragging down team performance.
→ An unscalable infrastructure caused distrust in data and poor decision-making.

The Solution:

We first conducted a deep data strategy assessment interview with stakeholders and end users.

This is one of the most important parts as we dig deep into their decision-making process and align data with key business objectives.

We uncover key business questions, remove surface-level questions and metrics, utilize a prioritization matrix to start with lowest hanging fruits first.

Centralized Data:
→ Built a robust data warehouse with Google BigQuery to unify insights.
→ Used Python scripts for custom ETL to extract data from CRMs, finance systems, and more.

Automated Workflows:
→ Leveraged Airflow to manage data pipelines seamlessly.
→ Automated reporting with Looker, eliminating manual Excel reports.

Actionable Insights:
→ Mapped clear metrics and KPIs aligned with business goals.
→ Applied governance practices to build trust in the data.

The Results:
→ Boosted sales revenue to over $10M.
→ Saved 100+ hours per week for executives by automating tedious reporting tasks.
→ Increased team productivity and achieved consistent quota attainment.
→ Built a data-first culture with clearly defined metrics and reliable insights.

Why It Worked:

The transformation didn’t happen because of the tools, technology, or any specific silver bullet.

It was about redefining how data supports business strategy and turning data into actionable insights.

There is one rule that we live by here at aztela which allows us to create, and implement analytics and AI solutions that drive clear quantifiable strategic impact which is

The value in data analytics initiatives and AI projects isn’t in:

• What new tools you have used,

• Creating complex Python data pipelines and SQL queries

• Spending hours designing pretty dashboards

Thats all useless

The real value is in

• Deep stakeholder interviews

• Creating data strategy

• Uncovering challenges, goals, and current top priority of the company.

• Asking good thoughtful questions.

• Prioritizing accordingly to business value and feasibility.

• Starting small and working in an iterative approach.

Most analysts, engineers or companies are straight jumping into the solutions.

“We need a dashboard” or “We need AI” which just results in wasting time and money so the initiatives fail because they didn’t generate any ROI.

The value should be determined before development even starts.

Here is a video of the whole demo of one slight part of the analytics end-to-end system we did for them.

If want to gain clarity of your data and utilize data to its full effectiveness to gain actionable insights, and actions and implement advanced solutions such as AI to gain an edge.

Book a call with our team for FREE data & AI assessment