In retail banking, a person’s decision to buy more products from the bank or seek them elsewhere depends on their satisfaction with the bank. Similarly, in corporate banking, whether B2B customers remain and continue purchasing financial products depends on their employees’ satisfaction with the bank’s services. Understanding this makes it easier to boost growth in banking sales call centers.

It means that the CSAT metric directly indicates which customers are ready to purchase additional products from the bank. Knowing a customer’s satisfaction history allows us to predict with high accuracy whether they should be offered more products.

Measuring CSAT for each retail bank customer and generating cold-calling lists based on this metric may significantly enhance the sales call center’s performance.

The primary challenge for the OTP Bank sales call center

The main challenge for the OTP Bank sales call center and its reps was to boost sales of additional banking products.

Secondly, it was crucial to increase the credit card reactivation rate.

An individual customer CSAT could help with both challenges, but to implement the idea of an individual customer CSAT, we had to figure out how to identify it.

In sales call centers where reps make cold calls, there are significant fluctuations in conversion rates across different customer call lists.

For example, if agents call customers who have had a negative experience with the bank, the conversion rate will be close to zero. None of these dissatisfied customers will buy anything. Other negative consequences include:

• No sales will occur, regardless of how often agents contact low CSAT customers.
• Agents will waste time listening to complaints or dealing with demanding customers.
• Demotivated agents will struggle to sell to customers with higher CSAT as well.

Solution: Defining an individual customer CSAT

Traditional bank surveys to obtain NPS data, such as calls by voice bots asking people to rate service, yield very selective estimates. This is because surveys are conducted on a specific sample of customers, most of whom have yet to respond. As a result, banks get NPS estimates from only about 15% of their customer base.

Working with customer lists without considering their CSAT history creates an uncontrolled situation. Researching customer satisfaction history, i.e., their CSAT history, can improve customer list preparation.

The Ender Turing platform defines an individual customer CSAT by analyzing each customer’s interaction history and feedback. This approach allows for more accurate and individualized satisfaction scores, enabling better-targeted sales strategies.

AI evaluates each call to determine customer satisfaction, categorizing them as:

All calls and their outcomes are stored and available in reports. If the customer was satisfied with the last three calls, it’s worth calling him again.

This conclusion helped us to create higher-quality lists for cold calling.

This is the statistics from the OTP bank sales call center after they started to make calls having determined individual customer CSAT:

Automatic analysis of failures and their causes in the sales call center

Ender Turing AI automatically categorizes unsuccessful sales calls. All the calls form a Funnel accessible through the graphical user interface. The funnel is easily adjusted to the exact flow of a bank or a team. Switching between the group and individual agent funnels is also possible.

There are a few reasons to have a detailed funnel:

• Managers can use detailed reports to address each failure reason individually, creating targeted scripts and handling customer objections effectively.
• To identify which banking products fail to generate interest and determine which ones need improvement.
• To identify correlations between agents and specific refusal reasons they struggle to handle.

Sales conversation analytics

Ender Turing Generative AI provides the following analytics and insights to optimize processes in the sales call center:

• Customer behavior funnels
• Identification of the most effective sales phrases
• Automatic selection of wrap-up codes for every conversation
• Tracking whether the agent has informed the customer about new promotions, discounts, and bonuses

“My advice to everyone about to start using Ender Turning for outbound sales calls: Make your first sales, build funnels, gather insights from the funnels, tweak the process, and sell better again!” – Dmytro Gramatik, Head of Call Center, OTP Bank.

Self-Training Automation for Sales Agents

The Ender Turing self-training module can be used for sales teams in the following ways:

Learning effective sales pitch and closing techniques:

• Identify and teach the most effective pitches and dialogs that drive conversions.
• Pin successful call samples to the playlist section to train each agent.

Objections handling:

• Share examples with all agents to improve overall performance.
• Analyze common objections and determine which agents handle them best.

The Growth Results in the OTP Bank sales call center :

• Increasing the deposit penetration rate from 7% up to 15%
• Card Reactivation Boost from 15% to 45%
• The conversion rate for upsells in the call center increased by 5%
• Bringing back churned customers – done
• Boosting recovery in the debt collection department – done

Related posts:

1. How to Build a Call Center Quality Monitoring Scorecard for Your Call Center (1)
2. Customer Experience Analytics: What Is It and How to Use It? (1)
3. How AI Can Improve Customer Experience (1)
4. Top 6 Medallia Competitors to Boost Productivity (1)

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