How Speech Analytics benefits sales teams
Speech analytics is quickly becoming one of the most in demand technologies for organizations across all industries. Most organizations have some type of call recording system for quality control purposes, however now they are realizing that the data that these recording hold can benefit various departments and especially sales teams.
What is speech analytics?
Speech Analytics is a tool that helps analyses telephone conversations. There are normally two parts, one, the transcription of the audio into text, and two,the analysis of that transcribed content. With speech analytics, you can detect and analyze patterns, keywords of interest, etc.
This technology is becoming more advanced and allows for more complex and real-time analysis, and not only calls (audios) but can also analyze emails, SMSs and other communications that are made between a company and its customers.
How does speech analytics benefit sales teams?
The sales department is one of the core ones of an organization, they interact with customers and potential customers daily so it is vital that they are keeping up with best practices and that the department is running as smoothly as possible.
Most companies recording calls for quality assurance and compliance purposes but how can you utilize this huge amount of data and information to benefit the sales team?
1. Gain real insights from real customers
What better way to understand your customers needs and wants than by listening to exactly what they’re saying. For organizations that receive thousands of calls daily, it is impossible to listen or gain any insight into calls without some sort of speech analytics software. Speech analytics software with automatic transcription capabilities yields 100% of customer conversations, thus, eliminating biases and the chance of unmined data. Once transcribed you can easily analyze the data, identifying the wants and needs of customers, dissatisfaction on customer trends etc.
By using this technology, you can automatically evaluate every call and categorize them and use the information found to help improve products or services. For example, if you’re a bank and customers kept on saying “ I wish I could apply for a loan on the app” you could then flag and forward this information to the R&D department to develop this service.
2. Identifying cross and upselling opportunities
Speech analytics allows you to mine call data for related to products, services, price and quality, etc. Listening to your customers and learning about their wants and needs will allow you to identify what they want easier.
Imagine a customer calls your sales team asking for an add-on that currently you don’t offer but it could be easily introduced. Using speech analytics, you can easily identify if this is are repeated requests. By identifying potential up-sell and cross-sell opportunities you give your customers what they want and increase sales.
3. Automatically detect unsuccessful calls and train agents
Automatically detect successful sale calls and identify why they are unsuccessful. Then, analyze them, identify keywords, and topics to improve and optimize your entire sales process.
Once you have all this information you can use it to retrain your sales agents and identify best practices and techniques. Or use your tops sales agents calls as examples and help craft scripts.
4. Spotting competitive challenges
Gaining visibility over key customer interactions using an effective call monitoring strategy allows businesses to gather sales and marketing insight and identify if customers mention competitors. You can set up keyword spotting and anytime a competitors’ name is mentioned in a call you can receive an alert.
The information gathered and the accurate analysis of these calls can refine business decisions that have the biggest impact. It can then be passed on to the relevant departments such as sales and marketing, improving your business’ ability to meet competitive challenges.
5. Sentiment analysis
Some advanced speech analytic software, such as Recordia’s Business Rules, not only allows ou to analyze the text but also how customers are feeling. After you define and label calls with the feelings associated using preselected key words or phrases, through artificial intelligence and machine learning you can analyze user behavior during calls, to define the feelings of people who are talking.
There are two very important aspects of behavior that help define feelings, one, tone of voice in order to know when people shout or speak in a very loudly. And two, when speakers overlap, which happens when people are constantly interrupted while talking.
Using this information, you can better improve processes and how agents handle calls and if they need any retraining or improvement on any weak points.
To learn more about Recordia’s speech analytics feature, click here.