Article’s

Customer Relationship Management (CRM) systems are central to how Education Technology (EdTech) companies manage enquiries, yet the data captured in such systems is not always analysed for its predictive value. This study examines lead conversion at Intellipaat, a Bengaluru-based EdTech company, by combining CRM-related organisational context observed during an internship with a structured questionnaire administered to 103 individuals who had enquired about Intellipaat’s certification programmes, of whom 88 confirmed an actual enquiry. Frequency and percentage analysis, Cronbach’s Alpha, Chi-Square tests, Pearson/Spearman correlation and binary logistic regression were used to examine counsellor-interaction quality, lead source, learner satisfaction/trust, and counselling and decision-factor ratings in relation to conversion. Lead source was significantly associated with enquiry outcome (χ² = 25.287, df = 12, p = 0.014), while overall satisfaction was strongly correlated with trust (r = 0.848) and willingness to enrol again (r = 0.822). Counsellor satisfaction alone was not significant (χ² = 6.745, df = 8, p = 0.564), and the logistic regression model was not significant (p = 0.672). The findings indicate that structured, CRM-recorded behavioural data offers a more promising foundation for predictive lead scoring than survey-based perception composites alone. Key Words: Customer Relationship Management, Lead Conversion, Predictive Analytics, EdTech, Lead Scoring, Logistic Regression.