Improve customer satisfaction for the card business by reducing complaints using advanced analytics

Did you know that every complaint has a revenue or cost implication attached to it? For example a complaint of dispute not having been resolved not only has an immediate dollar impact associated with the dispute amount but also can disengage the customer over time leading to further revenue loss.

Complaints serve as a critical indicator of problems that disrupt the customer lifecycle. Customers regularly voice their concerns through various contact channels, making complaints a significant component of customer feedback. If complaints are not adequately addressed, they can trigger customer attrition, resulting in revenue loss and higher acquisition costs.

Mining sufficient information from complaints, which are often in voice and text formats, is cost-intensive but essential for enhancing customer service. To allocate appropriate organizational resources for complaint reduction, a revenue impact analysis is necessary.

After assessing the revenue impact, advanced analytics can be utilized to find effective ways to reduce complaints.

This solution offers a comprehensive impact assessment of various types of complaints an organization might encounter. The detailed analysis includes:

1. Analysing revenue impact of complaining customers by matching them with similar non-complaining customers.
2. Evaluating the cost implications of mitigating these complaints.
3. Assessing the impact of complaints on customer attrition.

Equipped with this vital information, organizations can formulate effective strategies to minimize complaint impact and improve customer satisfaction through efficient resolution. Furthermore, it supports the development of proactive strategies to reduce the occurrence of complaints over time.

This solution is for organizations that:

1. Have a high complaint rate and want to reduce complaints scientifically.
2. May not have a very high complaint rate but have a “customer-centric strategy” and aim to continuously improve customer servicing.
3. Seek to increase revenue and/or lower costs by optimizing their servicing channels.

Reducing complaints can result in several benefits:

1. Increased revenue: Customers tend to disengage after encountering issues. Reducing complaints will lead to increased revenue over time as customer experiences improve.
2. Improved operational efficiency: Complaints often uncover underlying problems with products and communication. Resolving these issues can lower service costs and enhance operational efficiency.
3. Higher NPS/VOC/CSAT & loyalty: Customers Favor organizations that address their complaints promptly. This improves the brand image and strengthens customer loyalty.

The model incorporates the following characteristics:

1. Complaints data
2. Categories of complaints
3. Profit and Loss (PnL) data at the customer level
4. Transaction and category-specific spending data
5. Attrition data

To match complaining customers with non-complaining customers, lookalike modeling will be used. The choice of algorithm—support vector machines, clustering, or neural networks—will depend on the data variety available.

Financial modeling will be applied to assess the revenue impact of complaints.

1. On-prem ( on customer systems or on DeepQ-AI Environment)
2. 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 the categorization of complaints, detailing their severity and impact on PnL.
2. PowerPoint summaries or automated Excel files.
3. Interactive dashboards.