Enabling automated solutions via cause/causality model driven by top call drivers to reduce people dependency
Enabling incident deflection (self help) and first call resolution through guided solutions driven by machine learning
Unearthing optimization opportunities through Intuitive Operations dashboards & dynamic analysis of vital support metrics
Enabling support to scale faster by routing issues of increasing complexity based on skill level and past learning
Organizations are under pressure to consistently improve
customer satisfaction while reducing the support costs.
Brand Equity of any organization is in the hands of a very vocal customer base, who are the best judge of your customer service. Bad news spreads much faster than good news, and organizations often find themselves doing damage control on daily basis.
Budget for support activities and justifying the same is another gray area. Organizations are mostly constrained due to limited budget available for Customer Support operations, but the quality of service delivered is expected to be top-notch.
Person-Dependence has been adversely impacting Support industry more than any other. Investments into building knowledgeable human resources are constantly lost to competitors.
Support Managers have to consistently achieve
SLA Metrics while
managing resource-starved operations.
Effective First Contact is necessary to make a good impression on the customer and any short-comings at this point are difficult to recover from.
Attritionof high quality agents forces the manager into a never-ending process of constantly training and orienting new resources to make them productive as soon as possible.
Cost Per Incident tends to grow when support volume increases; however, Support Managers are tasked with reducing the cost per incident.
Escalation Ratio tends to skew towards the higher support tiers over time and it is a constant struggle to maintain the right balance.
Customers often have poor support experience
and have to
make repeat calls before the problem is resolved.
Inaccurate Solutions cause reopening of supposedly resolved issues and severely affect CSAT.
Inconsistent Service Experience arises
due to non-uniform knowledge levels of agents interacting with the customer.
A positive customer support experience is a must and any slip is magnified in this social era.
Repeat Calls to follow-up on raised issues, sometimes with different departments and different agents, frustrates the Customers and makes them a detractor.
High Resolution Time due to agents taking a long time to understand & diagnose the underlying problem. Customers expect an informed agent who can perform meaningful diagnostics to provide accurate responses to their pointed queries.
Supportfirst helps you realize the true potential of your customer support investments by effectively surmounting these challenges and delighting your stakeholders.
Supportfirst : Support Services Platform
Proactive monitoring of all channels (chat, mail, phone and social)
Accurate diagnosis for first call resolution
Faster resolution via guided solutions
Maximized issue resolution at lower levels
Reduce pre and on the job training times
Incident resolution at Self-help portals via auto agents
Store knowledge of SMEs in asystematic quality controlled process
Continuously evaluate effectiveness of the captured knowledge
Identify gaps and areas of improvement in the KB to ensure complete & accurate knowledge capture
Top call-driver identification through Natural Language Processing techniques
Integrate disparate knowledge sources and associate contextually to top call-drivers
Provide the most relevant and useful information to agents in real time
iOPEX is a new-gen technology focused company in the field of Integrated Automation, Moderation Services, Digital Advertising and Transforming Customer & Technical Support Experience. We acquire the latest advancements in our focus areas and optimize the resources available to deliver the best outcome for our clients in the long run, which in turn improves the top and bottom line of the businesses.