Creating a positive customer experience is the key to building a successful business. Knowing what customers want before they change their minds, or move on to your competitors, will help create a positive customer experience. Since you can't read their minds, the next best thing is using speech analytics to capture 100% of your customer conversations and combine the Speech Analytics in PEGA's Next Best Action Decisioning Engine.
Customer feedback gives us the ability to better understand our customers and their concerns, needs, and ideas. Speech analytics saves businesses time and delivers value through loyal customers, increased revenue, and decreased expenses. But in reality, combining Call center Real-Time speech Analytics with the PEGA Decisioning Engine is not a straightforward and easy process. With the recent Rega Acquisition of Qurious.io (for Al-Powered Speech Analytics), integration of Speech Analytics in a PEGA Decision making process would become easy (hoping to hear updates from PEGA world 2021 event on 04-May-2021).
Large Enterprises contact centers typically address multiple challenges and try to resolve them through a measurable improvement process. In simple words...
PEGA Speech Analytics + PEGA NLP+PEGA AI powered Decisioning = Solve many industry problems exist today
I strongly believe Speech Analytics with the power of AI powered Decisioning would solve many of UNCOVERED industry issues today. Here are the most common areas that require constant business improvement.
Improve agent performance and reduce churn
Speech analytics can listen to every call. By listening for keywords and phrases, ensuring the agent follows processes, and by analyzing both agents and customers language and tone for sentiment, every call can be automatically scored against multiple criteria. What's more, these rules will be applied perfectly consistently. As a result, you can improve overall performance with additional training to plug the skills and knowledge gaps identified. This also helps to improve the speed to competency for new recruits, and reduce chum in those all-important first few weeks and months.
Speech analytics can also help us to stay in touch with the emotional and mental well-being of our agents Tone and sentiment analysis is used to assess both parties in an interaction If an agent shows signs of stress, frustration, anger or other negative emotions, this will inevitably come through in the analysis Managers can then be warned to intervene with a metaphorical arm around the shoulder. additional training, or even counselling.
Gain insights into customers and competitors
Even if we are already recording all calls and listening in to a small percentage of them for compliance and training purposes, that still means that most of the useful information in those interactions is not being taken on board.
While talking to our agents, our customers give up lots of incredibly detailed information in off-the-cuff comments related to such things as how they use our products, how our prices compare, how accessible and efficient our after-sales care is, and most importantly how we stack up against your direct competition. This is gold dust insight that you would normally need to conduct thousands of surveys to uncover and it's right there already on a dusty server in your unlistened to call recordings.
Sales and marketing teams can leverage this information with the help of modern technologies and use it to inform their decisions on everything from product development to pricing, to market positioning and what sales channels to use.
Generate more sales
Real-Time Speech analytics combined with Decisioning allows us to identify what sentiments in what situations lead to what behaviors and what the results usually are.
We can then redesign processes to eliminate behaviors that don't lead to sales and retention, and encourage ones that do Decisioning logic to take advantage of the best moments during interactions to make an upsell or cross-sell offer, ensuring that closing rates are maximized Outbound contact.
programmers can also be used to follow up with customers who had, for whom the analytics predict are likely to have a negative experience with a product or service.
Predict and understand your metrics and improve them
Using speech analytics, we can take the measure of each customer's tone of voice and words used to actually predict- quite accurately the customer satisfaction or NPS rating the customer would have given for a particular call This means that rather than relying on the few customers we do follow up with to arrive at those scores, we can effectively get a predicted satisfaction rating for every interaction.
Linguistic analysis can also pick out customers' verbatim comments made to agents to help us understand exactly what they do and do not like about our products, service levels, and processes Feed this information into our analysis of our metrics when you collect them to understand why customers give the scores they do, and what they would like us to do to improve them.
Prevent Customer fraud
Customers may be "king" but that doesn't mean they always do the right thing Speech analytics can not only identify but predict the likelihood of customer fraud with the help of Al Using the outputs of speech analytics (transcriptions, interaction analytics etc), a supervised machine learning module was built against a training data set ("Yes Fraud" and "No Non-Fraud calls). After blind tests and ongoing improvements, the supervised learning model has been operationalized as a customer voice data feed to the existing Fraud Risk engine. Customers are now triaged based on enhanced risk prediction to our Marketing Decisioning Engine
Turning Insights into Actionable Results
Speech analytics can undoubtedly provide its users with a wealth of agent, customer and contact center related information. However, the real trick lies in finding the most relevant insights from the pool of agent-customer interaction data. These insights can then be used to attain the required results and keep the contact center's operations away from any trouble Speech Analytics Insights are "Gold Digger" for business team and use them to make actionable results in both inbound and rest of the customer touch points including outbound channels.
Understanding the Factors Causing Call Dispositioning
Commonly used to describe the outcome or final output of a particular call, call disposition codes or labels are used by agents to classify calls under different heads such as miscellaneous, need follow-up, left voicemail and others Agents can attach such tags to these calls due to several reasons such as impractical call, need monitoring by the agent, saving time and others.
With speech analytics, it gets easier to classify the available call data under different heads so that it gets easier to attain the desired results. It would also get easier to know the reason behind a particular call, gain relevant business insights, etc.
Identify and correct processes or automation outliers
Organizations can use speech analytics to find terms associated with specific processes. Organizations can use Speech Analytics to understand the workflow/Processes broken/requires betterment to improve customer experience.
Fulfillment of an order
Refunds or returns
Employee automation Missing items
Broken systems
Average handle time (AHT) reduction
Understanding long calls also helps identify what customers really want and what the pain points in our product, services are and uncover the potentials to improve both Agent and customer experience.
Resolving customer issues on the first call (Improve first contact resolution)
First call resolution, also known as first contact resolution or FCR, is a company's ability to handle a customer's call, email, question, or complaint during their first outreach for that specific incident. With the help of Speech Analytics in a Decision making process will help us to resolve customer issues on the first call.
What do you think? Do you think we can solve other usecases? Please share in comments section.
Happy Learning,
Nanjundan Chinnasamy
