A nationwide automated platform for auto identifying customer issues, location and root cause. Enabling 10X savings in Opex for a Tier 1 operator.
How we can intelligently tackle customer complaints without continuously throwing bodies / resources at the problem?
How can I reduce the time to identify and resolve customer issues?
Location analysis by analysing CDR data.
Correlation of different KPIs using ML based algorithm.
Identifying Key KPIs impacting customer experience using classification algorithms.
Geo spatial analysis using Call Trace and crowdsourced data.
Automated mechanism for Customer issue location-identification solution deployed nation wide covering ~ 300 million users.
65% of the issue automatically triaged.
10X saving in overall cost for Care operation.
Formulation of a comprehensive user data experience score with a high correlation to the voice of customer used to drive process enhancement and automation in care and network teams.
How do I measure user experience w.r.t data services?
How do I proactively identify genuinely dissatisfied customers?
Mining and combining data from network, probes, CDRs, device SDK, care complaints, surveys, churn etc.
Comprehensive analysis of customer usage patterns: location and type of usage. Live, Work, Commute and other locations.
Modelling User KPIs, Site Kpis from OSS and Customer complaint metrics to identify Key KPIs impacting complaint and churn.
Proactively identifying (and acting on) dissatisfied customers before they silently churn.
Dramatically changed the strategy for network investment based on the Customer Experience metric.