It only takes a few seconds to create a lasting impression on another person. And so the earliest opportunity to influence a customer and prevent a grievance from becoming a complaint is the first interaction. This also provides the best opportunity to ensure regulatory compliance, by proactively identifying customer concerns or preventing future issues by offering resolutions. The data shows:
- The more time elapsed on any query, the more likely it will lead to a complaint
- The longer the complaint continues, the likelihood of a satisfactory resolution reduces significantly, regardless of the final outcome of the complaint.
By applying the principles of consumer duty to each customer interaction, whether or not an expression of dissatisfaction, the improvement to customer satisfaction and loyalty will far outweigh any concessions offered.
So how can you empower the frontline with the tools and insight to identify and resolve a potential complaint early using appropriate and acceptable remedies? Is the universal advisor model the answer?
Achieving a preventative complaints strategy
Adopting the principles of consumer duty creates a proactive strategy to avoid potential causes of customer dissatisfaction. Identifying customers who would benefit from alternative services or plans is one way to delight customers whilst protecting brand reputation and customer loyalty.
For example, suppose a customer has international data roaming but no record of ever using their mobile abroad, proactively recommend they change their package/bundle to their specific needs helps ensure that they are receiving value for money, shows the company is looking for them, and is likely invoke a strong sense of brand affinity.
Empower the frontline
Data and digital tools need to come together to anticipate a wide range of customer issues, and support advisors in real-time. Accurate recognition of complaints is key, and AI tools can help here with real-time prompts, critical process steps and next-action suggestions to ensure compliance with both regulation and customer strategy. The right incentives are also needed to promote complaint resolution at the earliest point and within regulatory timescales. AI-powered triaging of the customer conversation (including intents, sentiment and vulnerability triggers), process adherence (ensuring that the advisor has followed the right steps in the right order) and tailored resolution offers are all technologies that provide in-contact support and direction for advisors.
Applying automated quality assurance to every customer interaction also provides evidence of regulatory compliance and identifies further development for advisors to develop their customer service skills. AI-based coaching tools provide guided and unguided ongoing training that is tailored specifically to individual advisors.
Being proactive
Greater understanding of customer behaviour and product usage provides the insights to apply the consumer duty principles of value for money. Predictive analytics, for instance, helps early signs of vulnerable customers in financial difficulties, allowing for early interventions with an offers of support.
Personalising these preventative strategies with targeted offers and dynamic pricing gives telcos far more influence over customer loyalty. AI and data-driven propensity modelling can optimise the timing and approach to bestuphold the principles of consumer duty and prevent future complaints.
Safeguarding with specialist teams
The frontline can resolve 80% of expressions of dissatisfaction or more, but in our experience a specialist complaint-handling team is better equipped to handle the remaining 20% that are more complex or material.
Root cause analysis can identify which complaints are best diverted to the specialist team. There needs to be a balance between frontline resolution versus escalation to the specialist team. Too high expectations of complex complaint resolution at the frontline is counter-productive, increasing costs and frustrating employees. Equally, overloading a specialist team with simple enquiries forces a customer through a more formal and time-consuming process.
The role of a universal advisor model in Complaint Handling
A universal advisor is trained and equipped to handle all queries for customers. To do this, they require much more than just agent support tools. The advisor requires full access to the data and processes to be able to carry out the full range of queries that the customer may have, which can require major platform transformation and integration across the business. However, a significant step-up in complaint resolution can be achieved with the right data analytics and real-time support technology for the frontline teams.
Conclusion: Resolving complaints better and earlier
With access to the correct data and supported by decision-enhancing technology, advisors can identify, negotiate and resolve at least 80% of all complaints ‘once and done’ at the frontline. And could it go even further?