Speech Analytics and Ways to Adopt Them

May 13, 2020

Speech analytics tools are debunking myths that machines cannot understand emotions. The rising importance of customer first services and business approach owe their success only when they can deliver to their customer’s expectations. With the help of artificial intelligence, this analytic software can find out if the customer has a pleasant or awful experience. These tools are generally employed at customer service, CRM departments, or call centers.

Speech analytics is the method of analyzing live customer calls, voice notes using speech recognition software to extract useful information, and provide qualitative guarantee and assurance. Initially called audio-mining, where audio files were converted to texts to enable mining out specific keywords or phrases, now speech analytics software mines words by studying the audio patterns to detect certain emotions, moods and stress, hold times, silent patches, frequency of agents talking over a caller.

The benefits of this disruptive tech are generally brands with operating call centers. It is because speech analytics helps them derive crucial information out of unstructured data from customer interactions, identify patterns, and draw actionable insights to improve what they are selling or the way they are selling it. These include the provision of enriched customer experience at reduced costs, identify the upsell and cross-sell opportunities, risk issues, calls that can be better handled by IVR, or website self-service. It also reduces repeated requests, headcount from automation of call monitoring, and compliance checking. Besides, it also leads to higher revenue collection, an uptick in promise-to-pay ratios, customized message relays, lower customer churn, and quantify customer satisfaction levels for lead generation and retention.

Speech analytics allow the promotion of customer loyalty, better growth, and profits. For an organization to have higher rates of success in this, they need to adopt some practices to achieve the same. These are:

1. Identifying the Goals: Conduct an audit and find out what does the company wants to use the tools for, what are the struggle points for the agents, and so on.

2. Get On Board Leaders: After the first step, find a trusty person in the higher management division and explain them why does the organization need a speech analytics toolset, the cost-analysis showing the revenue margin at different investments, the benefits and ROI, the team who shall handle it, and how using it can align with the organizational goals.

3. Determine the KPIs: The Key Performance Indicators measure performance by recognizing patterns that might lead to best practices and solutions. These KPIs can include anything like average handle time, check average service levels by seconds, first call resolution rate, and other factors than help to know if the specified standards at met or not compared to the baseline data.

4. Choosing the Appropriate elements/stakeholders: These comprise finding and appointing the perfect, full-time team that shall cater to the customer needs, manage the system, look for trends, and create reports. It is also equally essential to find the right audience and service providers—irrespective of the communication channels such as telephonic calls, e-mails, and chatbox. Every company wants an audience that can provide impartial insights and help them to grow too. Having a right service provider shall help in monitoring behavior and data that used to be missed by humans and better data scrutinization.

5. Have an optimal action strategy: The key to success lies in having a flexible and foolproof plan. Hire a strong team that will review the unstructured, multi-format data, discovers trends and shifts and their drivers. This committee should be well equipped will access to tools that can assist them in ways to overcome the flaws and check for the data validity. Based on the information collected, form a plan to implement speech analytics software, examine the protocols and procedures followed. Explain the team their responsibilities and answer their queries. Give them the authority to hold one another and their managers accountable for their jobs. Furthermore, have a well-planned training program that will educate these members on how to navigate, search, and run reports relevant to their role and impart basic knowledge of how to operate the software.

6. The post-launch phase: it is crucial that the data is shared with others to foster trust. Encourage them to provide feedback and hold meetings now and then to check the progress, goals, KPIs, methods to boost the value of speech analytics, and also for team bonding. Have the patience to witness results over a certain period. Speech analytics is one of the mature and fastest-growing areas of the contact center technology market. In general words, it helps a company brand to figure out what policies are working on customers, the reason behind their frustration and dissatisfaction with the services. It provides them an ability to assess the complaints and calls on a real-time basis and provide them with tangible solutions at a quicker rate than other forms of feedbacks. With an increasing emphasis on quality, the customer-centric markets are gain popularity, so why not employ tools that help to understand them.

Author: Preetipadma K.