The client, a leading education and research institute in the field of engineering and sciences, was looking to increase its reach to potential candidates for a master’s program in Data Science & Engineering. The client was first keen to understand the various profile drivers that result in higher conversions for applicants to this course and how the same differs across the entire applicant journey. Further, they also wanted to develop the capabilities to be able to proactively identify such leads with a high propensity of conversion and target them to increase campaign effectiveness and reduce average acquisition cost.
Objective
To enhance marketing effectiveness for an executive program in Data Science & Engineering at a leading Education & Research Institute by leveraging machine learning algorithms to identify key factors contributing to lead conversion, create personalized marketing strategies, and reduce acquisition costs
Facilitate higher conversions through enhanced marketing efficiency with the help of machine learning algorithms
R Programming, Excel
Priorise’s analytics team came up with a solution that involved segregating all leads into different audience segments based on profile and behaviour attributes and closely studying the characteristics of each to facilitate more personalized targeting. Employing its expertise in implementing ML-based solutions, Priorise used a combination of classification models to identify the key factors that contribute the highest towards lead conversion and subsequently segregate the incoming leads into different groups of audience personas. Personalized marketing efforts and communication were then formulated to effectively cater to each user persona.
Some key features of this solution:
Data cleaning and classification of each variable into macro-level groups based on calculations and information gathered through secondary research
Binomial classification models like Gradient Boosting and Decision Trees were used to identify the key factors among academic profile, demography, and professional experience, contributing towards the conversion of a lead across the entire admission journey
The models also helped identify the lead sources with the highest propensity of conversion, facilitating better resource allocation
Establishing different audience segments using k-means clustering to understand the profile and behaviour characteristics of potential candidates
• Optimized targeting by developing creative communication based on user personas for in-depth micro-journeys
Data Input
Users provide the required data for analysis to the API, complete with a plan detailing the timeline, resources, budget, and data limitations.
Parameter Selection
Users choose statistical model parameters, including confidence levels and significance thresholds.
Sales Programs
APM's prowess was showcased when it measured the impact of over 900 Sales Programs. The insights revealed a staggering positive impact exceeding 120 million dollars on ACV, reaffirming the value of the tool.Professional Services
Beyond sales, APM was leveraged to gauge the effect of PM certifications on Project Managers. The results informed decisions regarding KPIs related to project management, optimizing processes and enhancing service delivery.Performance
For Account Executives (AEs), APM has been showcasing the impact of a flagship intervention project for our client across eight different KPIs beyond ACV and PG, including several lead quality and call transcript metrics.Project Information
Improved business understanding for stakeholders, more efficient targeting of marketing efforts, and reduced costs through a high-accuracy (85%) classification model
- Business understanding for stakeholders of the critical factors that impact the decision of a potential candidate to convert to the particular program
- A high-impact classification model with 85% accuracy in terms of segregating new leads into different audience segments
- More efficient targeting of marketing efforts leading to a reduction in cost
