Case study: Data Scientist Improves Lead Generation Efficiency by 13x, Saves 48 Hours per Month

Elle has been working with customer and research study data—thousands of rows of it—for years. Relying on Excel to process that much data would be cumbersome, and BPA Quality encourages staff to research and adopt technical solutions to meet client needs as effectively as possible. Elle started learning Python independently and was delighted to be able to apply it in her work right away. 

As she advanced with Python, Elle knew she would need support and resources to make the most of her new solutions. Based on extensive research of professional courses, BPA have chosen to partner with Cambridge Spark to support skills development in their Data Science and Analytics team. And Elle enrolled in the Data Science and AI apprenticeship.

Elle and her team track call metrics like customer satisfaction, first-call resolution and average handling times. They compare these metrics to a historical dataset to monitor trends and flag any anomalies to investigate with customers. Each such anomaly found through their analysis represents a lead for a customer and a potential opportunity to grow their revenue or improve processes, training, customer journey, etc.

But the team has to clean and prepare the data before they can actually analyse it—a tedious process in Excel. This takes time away from their analysis work and the value they can bring to customers.

The apprenticeship gave Elle a look "under the hood" for a better understanding of how data science works. And from the first learning module about building functions, Elle was translating formulas she had written in Excel into Python code for faster data processing. Within 3 months, this new method helped Elle to include more metrics for comparison in her model, creating additional value for customers while driving a 13x increase in the number of leads generated per hour, saving 48 hours per month across two processes.

Having discovered her passion for data science before choosing to participate in the apprenticeship, Elle says that passion has been a key driver in persevering through the demands of the programme. 

Proper self care and time management have also been crucial to balancing home and work life with her learning. And apart from the generous support she received from her organisation, she says her learning coach and data mentor have been "incredible" in how they've accommodated her needs, encouraged her to explore applying disruptive technologies in her work and more.

Elle's passion and the support she's received have even helped her achieve outside her work. She started a coding club at a local college, became a STEM ambassador and went on to win Cambridge Spark's 2023 AI & Data Science Apprentice of the Year award!