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PGNiG is a Polish company, a part of PKN Orlen, engaged in the exploration and production of natural gas and crude oil, the import of gas, and through key subsidiaries: storage, sales, distribution of gaseous and liquid fuels and the production of heat and electricity.
As a part of their growth strategy in renewable energy sector, PGNiG asked BitPeak to provide a tool to access and manage information about potential leads, as well as augument their infrastructure investment strategy.
Custom web application which, through user friendly interface, provided information about potential investments. The goal was to generate new leads, manage them, as well as augment sales and investment strategy with concrete information about costs, benefits and KPIs. We used AI models to analyze data from multiple registers, such as large scale aerial photos and geolocational data to provide valuable insights.
- New competitors on energy market in Poland, as well as social, political and economic factors forcing new, more proactive sales approach for green energy
- Dynamically changing circumstances on global and European energy market required more efficient lead generation process, with targeted & effective sales for PV installations at lower operational cost.
- Lack for trustworthy forecasts related to efficiency of potential infrastructure investments.
Step 1 – Acquiring broad range of data from various registers at low cost, to fulfill Clients budget expectations. Minimizing the costs of sourcing data and maintaining high quality and depth of insights produced.
Step 2 – Processing acquired data to obtain valuable information about efficiency of potential photovoltaic installation based on shading, roof shape and slope and air pollution in the area. We used parallel machines and multiple AI models to analyze and process the data, ensuring speed and high quality of the results.
Step 3 – Creating an Salesforce integrated Web application with a user-friendly interface. We focused on UX and providing valuable insights such as expected ROI, energy produced, and time of return of investment. Usable with little to no training time and providing insights in clear, concise manner.
To realize our goal we used following techstack:
Databricks – For analysis and calculations
Apache Spark – For distribution of calculations of photovoltaic potential among many parallel machines
Azure – For data structure and database construction.
Python – For logic used for analysis
We provided our client with dominant data-driven information advantage and enabled them to create optimal data-backed sales strategy. Additionally by optimizing ROI through high quality leads and valuable insights into particular customers and regions, we increased the client’s revenue.
Thanks to the application and its user-friendly interface, the data was easily accessible and usable, making sales process easier. The analysis and management of information did not require much time or training which increased the efficiency of the sales department, increased personnel mobility, resulting in lower operating costs.
By providing the salesmen with insights into the risks and potential rewards of each investment, including specific numbers and KPIs the customers’s uncertainty could be significantly reduced increasing leading to more green investments and lower energy costs.