Alex, a contact center executive with a Life insurance company, handles a customer call and commits to something that’s not part of the caller’s insurance coverage. A few months later, the customer files a suit and the company must deal with a costly process to settle the issue.

Incidents like this occur often, due to errors made by Contact Center agents over the phone. Unfortunately, it is nearly impossible to track and analyze every single call to identify the errors and avoid the damage. Most Contact Centers randomly choose a few calls for the quality check and assess them manually. This is a time consuming and inefficient process.

Standardization of processes in contact centers is critical to avoid communication errors and customer confrontations. Speech Analytics plays a key role in this process.

rsz_standardization

Let’s consider a few examples –

Compliance Adherence: Compliance adherence is a must for Contact Centers, and failure to comply can lead to hefty fines. Speech Analytics helps monitor and analyze every interaction between the agent and customer to check for discrepancies. Agents might commit to something incorrectly, or perhaps fail to include the disclaimer statement, both of which create risks for Contact Centers. By identifying and analyzing these specific errors, Speech Analytics helps Contact Centers standardize the information that should be communicated, as well as what should not be shared.

Upsell & Cross Sell: Since Speech Analytics ‘’observes’’ the conversations between agents and customers, it helps craft the upsell and cross-sell strategies based on customer behavior, emotion, and key phrases used on the call.  For example, phrases such as ‘’satisfied’’, ‘’pleased’’, ‘’happy’’, etc., can alert agents to a cross-sell or upsell opportunity, and a script can prompt them to take the lead. Phrases such as ‘’disappointed’’ and ‘’not happy’’ will prompt agents to restrain from selling and focus on creating a better customer experience. Speech Analytics can analyze the calls that led to a successful cross-sell and upsell opportunities, identifying best practices that can be incorporated into agent training.

Sentiment Analysis: The latest developments in Speech Analytics enable sentiment analysis of your customers. Sentiment analysis is key to customer care, as it analyzes the caller’s emotions – whether positive, negative or neutral, as well as the intensity of emotion. Analysis of customer emotion and sentiment can be shared across the organization, from agent training to greater awareness at the executive level.

Quality Control is an integral contact center performance measure. By capturing keywords and phrases, Speech Analytics helps in effective call calibration, reducing the number of calls to be monitored and eliminating redundant Quality Control processes. There is a reduced burden on QC managers, supervisors, and agents, which allows for effective and efficient call monitoring and training.

Reducing AHT: Reducing Average Handle Time (AHT) increases the operational efficiency of Contact Centers. Speech Analytics, together with AI and Machine Learning, can help predict customer behavior based on emotion, tone, and keywords used. This helps in training agents to proactively handle customers in a much more personal and efficient manner, driving down AHT and increasing customer satisfaction.

Speech Analytics provides valuable customer insights and redefines Contact Center operations. This helps drive business outcomes while enhancing customer relationships.

To know more about how Speech Analytics helps contact centers achieve operational efficiency, click Speech Analytics for Contact Centers & BPOs – Revitalizing Customer Experience for the whitepaper. 

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