{"id":18379,"date":"2024-11-22T23:13:33","date_gmt":"2024-11-22T19:13:33","guid":{"rendered":"https:\/\/krisp.ai\/blog\/?p=18379"},"modified":"2024-11-22T23:54:14","modified_gmt":"2024-11-22T19:54:14","slug":"how-to-utilize-speech-analytics-to-grow-your-conversion-rate","status":"publish","type":"post","link":"https:\/\/krisp.ai\/blog\/how-to-utilize-speech-analytics-to-grow-your-conversion-rate\/","title":{"rendered":"How to Utilize Speech Analytics to Grow Your Conversion Rate"},"content":{"rendered":"

Ever heard the saying, “It\u2019s not what you say, but how you say it?” That\u2019s basically the golden rule in sales, especially when you’re on the phone with a customer. The tone of your voice, the words you choose, and even how quickly you respond can completely change the outcome of a call. But figuring out exactly what works and what doesn\u2019t (beyond just a gut feeling) isn\u2019t always easy.\u00a0<\/span><\/p>\n

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Image sourced<\/span><\/a> from cognism.com<\/span><\/p>\n

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Now, conversions over the phone are tough. The average cold calling success rate is only 4.8%, <\/span>according to Cognism<\/span><\/a>. Not great, right? But speech analytics can help change that. By analyzing your conversations in real time, it helps you pinpoint where things are going wrong (or right!). For example, simply asking, \u201cHow have you been?\u201d can boost your conversion rate up to 10.01%.\u00a0<\/span><\/p>\n

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So how can you use this tech to turn things around? In this blog, we\u2019re going to break down the benefits of speech analytics and show you five ways to boost your conversion rates. Let\u2019s get started.<\/span><\/p>\n

What is Speech Analytics?<\/span><\/h2>\n

Speech analytics is the process of looking into recorded calls to better understand your customers and improve future interactions. Think of it as a high-tech way to listen in (in a totally ethical way) on conversations.\u00a0\u00a0<\/span><\/p>\n

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Let\u2019s see this in action. Imagine you run a home improvement store. With a <\/span>data processing pipeline<\/span><\/a>, you can dig into customer calls and spot trends or common issues. For example, you might find that lots of customers are asking about the same power tool or getting frustrated trying to find specific items. With this, you can stock up on what people really want and even improve your in-store signs to help them navigate better.<\/span><\/p>\n

Contact center speech analytics explained<\/span><\/h3>\n

Contact center speech analytics is all about using speech analytics tech in call centers. It fits right into contact center solutions and looks at all the calls agents handle every day, pulling out some really useful info from the recordings.<\/span><\/p>\n

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This tech is a total game-changer for businesses that want to level up their contact center performance and keep customers happy. By checking out those recorded calls, companies can figure out what issues keep popping up and train their agents better, leading to improved customer satisfaction and, in turn, a higher conversion rate.\u00a0<\/span><\/p>\n

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With <\/span>call center analytics<\/span><\/a>, contact centers can turn every chat into a valuable piece of info that helps them keep getting better.<\/span><\/p>\n

How Does Speech Analytics Work?\u00a0<\/span><\/h2>\n

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Image sourced<\/span><\/a> from fortunebusinessinsights.com<\/span><\/p>\n

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The <\/span>global speech analytics market<\/span><\/a> was valued at USD 3.31 billion in 2022 and is projected to grow to an incredible USD 10.37 billion by 2030. But how does it work?\u00a0<\/span><\/p>\n

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Well, speech analytics software uses a bunch of <\/span>sales intelligence tools<\/span><\/a> and technologies to break down spoken language, such as:<\/span><\/p>\n

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Step 1 – Capturing audio: <\/b>Conversations between customers and agents get recorded. These recordings<\/a> are saved for later analysis.<\/span><\/p>\n

Step 2 – Automatic Speech Recognition (ASR): <\/b>Next, ASR tech steps in to turn those spoken words into text<\/a> (AKA a <\/span>transcription<\/span>). This part is super crucial because it takes the audio and converts it into something we can actually work with.<\/span><\/p>\n

Step 3 – Natural Language Processing (NLP): <\/b>Once we\u2019ve got the text, natural language processing algorithms get to work. They analyze what\u2019s been said to understand the context, customer sentiments, and meaning behind the words. This essentially just means they pick out keywords, phrases, and patterns.<\/span><\/p>\n

Step 4 – Machine learning:<\/b> After processing the text, machine learning models like artificial intelligence and other speech analytics solutions extract insights. These models can spot trends, find oddities, and even predict outcomes based on past data.<\/span><\/p>\n

Step 5 – Share insights:<\/b> Finally, the insights are compiled into reports and dashboards that are easy to read. These gems can then be shared with managers, executives, or anyone else who needs to make smart decisions.<\/span><\/p>\n

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Benefits of Using Speech Analytics in Call Centers<\/span><\/h2>\n

Call centers have evolved a lot. They’re not just answering phones anymore. No, they\u2019re now digital hubs where customers can reach out through calls, texts, chats, emails, and even social media and other digital channels. In fact, 40% of consumers say having <\/span>multiple options for communicating<\/span><\/a> is the most important part of a company\u2019s customer service.<\/span><\/p>\n

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When call centers start using speech analytics for these multiple options they get valuable, actionable insights into what customers really want and how they feel. The benefits of speech analytics are huge:<\/span><\/p>\n

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