Case Study (A) – Dealer call inbound helpdesk for Telecom client

Key operational challenges were:

1. Sustenance of KPIs such as Service Level & Abandoned Levels due to uneven call volumes & occasional call surge.
2. Dealer satisfaction scores – target >=91%

Key measures taken to resolve the above mentioned challenges were as follows:

Analytical tools & methodologies:

• Cause & Effect analysis to optimize call handing time by reducing redundant steps in the process & wastages
• Erlang Call Centre Calculator to optimize the occupancy levels & meeting Service Levels
• Dynamic roster management for better staffing & scheduling of resources hence better workforce management
• Categorization of front liners in Achievers, Performers & Struggler bands for narrowing the focus areas

Following was the impact of the initiatives taken.

1. Dealer Satisfaction Scores increased to 94% as compared to a target of 91% as their issues were being resolved in the 1st call
2. Service Levels have increased to 94% as compared to a target of 80%.
3. Abandoned rate at less that 2%.
4. Quality Scores increased to 87%.

Case Study (B) – Postpaid acquisition channel, Lead Conversion Team, Telecom

Key operational challenges were:
Client was not converting leads generated from various channels as there was no end- to- end model available.

Sources of the leads that are serviced to sell postpaid connections are as follows:

Key measure taken to resolve the above mentioned challenge for sourcing New Telecom Postpaid Subscribers.

Following measures have supplemented postpaid sales & conversion levels:

1. Activation TAT adherence within 48 hours - greater than 90% Service Level is observed
2. Online pickups - here & now methodology ensured improvement in the conversion percentage
3. Servicing online & SMS leads within 4 hours of receipt to maximize the opportunity of closing the sale
4. Verificaion & confirmation call made on the next day morning to all fixed appointments to prevent redundant effort
5. Setup dedicated inbound helpdesk for resolving complaints / queries
6. Relationship building calls are made for the period of 365 days to control churn

Case Study (C) – Customer Retention, Churn control, Telecom

Key operational challenges were:

1. Client was not able to predict customer churn.
2. With increased competition among telecom companies, client was not able to retain its customers.

Predictive Churn control activities:

The objective Predictive Churn control activities are to predict customer churn & initiate tele-calling activities to address concern & control potential churn. The following are the potential events during the customer life cycle that may influence the customer to churn:

• Drop in usage or no usage for a particular period
• Calling competition customer service IVR numbers
• Repeat calls to customer care
• Unresolved complaints
• Multiple complaints
• Involuntary repeat barred due to non-payment
• Repeat defaulting in making payments
• Discontinuation of services
• Cancellation of auto debit mode of payments
• Payment cheque bounce events
• Non fulfillment of promises made at the sales point

The combination of the above events forms a sizeable "THREAT BASE", which is out-called to gauge the satisfaction levels & resolve concerns, if any. Basically, Relationship Building exercise.

Reactive Churn activities:

This is stage wherein the customer firmly decides to discontinue the telecom services through a written communication. Retaining such customers is like reselling service / product again through a blend of inbound, outbound & E-mail contact centre activities.

Following were the constructive impact on the business results i.e. Churn Control:

1. Predictive churn control activities were instrumental in reducing churn to below 1% in HNI segment
2. 60 days retention bucket improved from 82% to 90%
3. Reactive Retention percentage increased from 38% to over 50% due to the quick response time
4. New retention tools were devised to address the changing market scenarios
5. It was observed churn was substantially less in the contacted base compared to the non-contacted cases