- BFSI / Cards / Customer Service
In customer-centric organizations, customer experience is paramount as it fosters long-term revenue growth through loyalty.
These organizations provide various channels, including contact centers, chat, websites, and IVR, for customers to resolve issues and share feedback. However, the effort required to solve a problem differs across these channels; some are more time-intensive but cost-effective, while others are faster but more costly.
The optimal customer experience is achieved when organizations prioritize the customer’s time and effort, ensuring minimal time is needed to resolve issues. This approach helps prevent negative sentiments towards the problem.
This can be accomplished in two ways:
1. By meticulously designing customer journeys through these channels to minimize time and effort.
2. By directing customers to the most efficient channels for resolving specific issues.
The customer effort score facilitates this by providing a measurable metric to assess how easy or difficult it is for customers to resolve a problem through a given service channel.
This solution leverages an advanced AI/ML-driven model to map the customer journey through network analysis. It considers the following attributes:
1. Time taken by customers to resolve a problem through a channel
2. Success and failure rates of different paths taken to solve a problem through a channel
The outputs include:
1. A score measuring customer effort, calculated as a combination of clicks needed and time taken
2. Success/failure rates of the most commonly used customer journeys
3. Alternative journeys/rerouting options that can maximize success
4. Identification of technical roadblocks/snags in the system
Through this evaluation, the organization can prioritize and plan phased actions to improve the customer journey over time.
This solution is for organizations that:
1. Are customer-centric in their strategy and have identified it as a key success metric for their business.
2. Are advanced in their customer service journeys and possess rich data on customer interactions across all servicing channels.
3. Aim to achieve self-service goals within a stipulated timeframe using a scientific approach and data science.
4. Seek to reduce costs over the long term without impacting customer experience.
Reducing complaints can lead to several benefits:
1. Lower cost: Strategically moving customers will ensure reduced costs over time.
2. Minimal revenue impact: By maintaining the right oversight on projections and expected outcomes, the organization can plan to minimize the impact on revenue targets.
3. NPS/VOC/CSAT & loyalty: Customers tend to favor organizations that help them maintain a positive experience. A well-executed transition strategy can achieve this without harming customer sentiment and brand image.
The solution needs the following data:
1. Detailed customer interaction level data on IVR, Calls, Digital channels, and APP
2. Data on system outages and outliers, if any, within the same period
“1. Final outputs could include a list of activities across interaction channels, detailing the effort required to complete them, failure rates, success rates, and roadblocks.
2. PowerPoint summaries or automated Excel files.
3. Interactive dashboards.”
This solution will use network flow and graph traversal algorithms to analyze the customer journey and determine the most efficient paths.
Exploratory analysis will also be conducted as required to answer critical questions.
- On prem ( on customer systems or on DeepQ-AI Environment)
- On hosted cloud space ( Customer or DeepQ-AI Environment)
( deployment is subject to data availability in the same environment, or feasibility of seamless data transfers within secured environments)
1. Final outputs could include a list of activities across interaction channels, detailing the effort required to complete them, failure rates, success rates, and roadblocks.
2. PowerPoint summaries or automated Excel files.
3. Interactive dashboards.