Data Sanitization: The task at hand – improving the marketing endeavors and customer acquisition rates was a strategic challenge for Team Stridely at first. After closely analyzing the current promotions and marketing strategies and planning aligned with the same, Stridely team also observed the lead generation and nurturing efforts. Our team decided that an additional layer above their existing CRM system can be developed instead of replacing or revamping the whole system.
Lead scoring matrix: The whole process of transforming existing endeavors was planned and implemented methodologically. Different predictive lead scoring models were designed and integrated in each of the existing product lines to help the client in identifying ‘intent of buying’. Stridely team and client’s business team came up with a matrix to understand lead qualification and nurturing process being taken up internally and parameters they’d want to focus to classify a lead as most potential one
Custom Application: The fully custom solution was built using .NET Framework and several custom APIs to achieve:
- Marketing Indicators (MIs) that serve as valuable data points for tracking user behavior using predictive models to identify positive consumer behavior in relation to purchase decisions.
- Contact information extraction process, for segregating relevant information such as job title, address, etc. to improve qualitative metrics of available demographic data such as industry and company size.
- Predictive scores to analyze how close a potential customer is to the ideal customer profile and what are the chances of buying a particular product.
Robotic Process Automation (RPA): An integrated automation was implemented, using RPA to process approx. 250 to 300 leads being received on daily basis through ‘Contact Form’, ‘Quick Inquiry Form’, ‘Know More’, referral portals/sites and through emails.
Analytics and Business Intelligence: A dynamic predictive analytics system was planned for lead scoring and at the same time, data enrichment efforts were taken to increase demand across multiple channels.