Published October 19, 2022
Companies working in the business-to-business (B2B) market are often working under high pressure for high value contracts. In these conditions, the right tools for the job are essential, and it’s important to stay on top of relevant technology. The right resources, properly deployed, can make a huge difference in client retention and revenue generation.
One of the latest tools to enter this field is conversation intelligence software. Still only used by a few companies, conversation intelligence tools can help a company not just to meet but to exceed client expectations.
So what are conversation intelligence tools, how do they work, and why should your business invest in them?
Conversation intelligence software is designed to help businesses track and analyse customer conversations. Its artificial intelligence (AI) software analyses large volumes of speech or text to give you insights into the people your business communicates with, most often the clients.
This software can sift through masses of information far faster and more efficiently than human agents. The results are data-driven insights that replace the anecdotal or instinctive understandings that often drive business decisions. The outputs are sent to other systems, so that the information is integrated into working records and everyone who needs to can understand what’s been found. It can provide action items for immediate use, informing decisions on a daily basis, as well as longer term strategic insight.
Conversation intelligence software can help businesses to identify trends in customer behaviour, understand what customers are saying, and respond to customer needs. It can also improve your understanding of how employees approach conversations and how this affects customers. These insights allow a business to improve its ways of working. Because it digs into the qualitative data of what people say, instead of the quantitative data of finances and figures, the data doesn’t just show you what’s happening but can help you to understand how and why.
The data drawn on by conversation intelligence already exists, the challenge is making use of it when there’s so much data and so much else to be done. Conversation intelligence takes data collected during client calls and other areas of common client contact, turning it into insights that the whole business can benefit from.
Conversation intelligence tools work from a variety of sources. It’s common for them to get most of their data by recording and transcribing conversations between sales teams and potential customers, but emails, chat transcripts, and scanned correspondence can all contribute. The more information a conversation intelligence system has to work with, the better its insights will be.
While CRM systems store data, conversation intelligence AI, such as Kaizan’s Client Intelligence Platform analyses the communications to extract key data and produce insights. Combining Natural language processing (NLP) to understand the conversation and Machine Learning (ML) to identify patterns and trends, algorithms can extract common pain points, frequently asked questions, sentiment and customer objections. This can be used to understand causality and the variables that cause that effect. As generative language models improve, they can not only summarise but generate content and recommendations for teams, automating workflows like follow-up emails after meetings.
How the data is classified depends upon some initial input by users. This helps the AI to recognise the moods of clients and to understand which categories pieces of communication fall into. This means that the data is sifted in ways that are not just meaningful but useful for the company.
The results can be used to improve the effectiveness of communications. Better conversational strategies, new call scripts, and areas for process improvement can be identified. Even new products can find their origins in insights drawn from customers’ calls.
There are a few key reasons why a B2B company should invest in conversation intelligence software. The most obvious ones are centred directly around clients:
These points are fundamentally interconnected. By drawing information directly from clients themselves, conversation intelligence software provides insights into what clients think and feel and how this affects their behaviour.
This information can then be used to improve client satisfaction by giving them products and services that are closer to what they want. Some of this comes from identifying key issues, such as unsatisfactory products, unclear instructions, and unmet needs. But it’s also about the smaller details of good service. If you can see which approaches to client conversations lead to the best results, then you can write better call scripts and email templates, as well as training Client Service Managers on how to speak with clients.
These areas of improvements to the client journey will increase sales, drawing in new clients who might not have adopted your products. They also improve client retention, as they encourage existing clients to continue working with you. And because you’re providing a better service, customer support costs caused by helping dissatisfied or confused clients fall.
Other benefits come on the organisational side.
The analysis of calls and emails, if turned to focus on what your employees say, can help you to understand and manage teams. You can identify which team members are performing best, which ones are using strategies worth emulating, and which need extra support. It’s an effective way to measure achievement in areas like client success, which might previously have relied on the small sample of interactions a manager sees.
Because the AI carries out the transcription and labelling of data, you can speed up data entry into a CRM and reduce work on making call notes. There is some extra work at the start training the AI to understand your data, but in the long term, it will produce better outputs with less work on your part. It can also ensure that information is passed on to those who need it, by appropriately tagging records for their attention.
B2B client management is a big task that can produce seemingly endless work. Conversation intelligence reduces the burden of that work while directing your efforts toward more effective results.
The benefits of conversation intelligence tools are widespread, but the most obvious can be seen in customer-facing teams. By having a complete record of customer interactions, these teams can more easily identify areas for improvement.
With conversation intelligence, markets can be brought more clearly into view, not as abstract masses but as networks of individuals. The results of NLP show how clients respond to specific campaigns, including not just their actions but their emotional tone, which may affect follow-up work.
While statistical correlation can sometimes show which campaigns lead to sales, complicating factors make this uncertain. By looking at the how and why, conversation intelligence not only helps in identifying effective campaigns but can feed into creating future ones.
Many of the benefits seen by marketing also apply in sales. If you can understand what approaches appeal to clients, then you can repeat and refine them. Conversation intelligence can even identify leads who are likely to be receptive to future contact and how to approach them, turning this into action items for sales teams.
Because it can analyse calls, conversation intelligence is particularly useful in identifying which sales reps are doing well and why. Sales data may point you toward the first part, but conversation intelligence fills in the gaps, highlighting the opinions and emotions leading to a sale, so that fellow team members can learn from productive examples. It can also help you to identify early on if an employee is approaching clients in the wrong way, so that you can pre-empt the problem.
Though less oriented toward conversations with clients, e-commerce teams can still benefit from conversation intelligence. Reviews, customer feedback, and queries about how to get through the purchasing process can be used to generate a better understanding of the e-commerce process. This can fuel improvements that lead to better sales.
The cornerstone of B2B client management, client success teams need to understand as much as they can about the client journey to keep clients happy. This means there’s a lot of data and a lot of different factors to consider. Conversation intelligence’s big picture overview helps teams see the journey end-to-end, identifying areas of friction and risk points for losing clients. This can help in managing individual accounts as well as improving processes and contact scripts.
Getting an accurate picture of performance is one of the biggest challenges for quality assurance teams. It’s impossible to check every piece of work, so approximations have to be found. Sampling techniques are used to pick out representative examples of work, but these are only ever an approximation and only representative in certain ways. What if you want to look at proportional samples of happy and unhappy customers from each team or member of staff? What if you want to focus on unhappy customers to look at what’s going wrong?
By categorising the content and emotional tone of responses, conversation intelligence can provide better samples and identify areas where the company might be falling short. It can flag up interactions that QA staff should pay attention to, or give them better information on which to base their own sampling.
Away from the front lines, conversation intelligence can help companies improve their products by informing product teams. Patterns in what clients ask for or expect can be drawn out, as well as their emotional responses to different parts of the company’s services. This can point at unmet needs, potential areas of improvement, and even specific ideas for how to improve products.
For almost every company, the data to drive conversation intelligence tools already exists, in the form of call recordings and correspondence. Conversation intelligence lets you dig into that rich seam of information, turning data into insights then using them to drive client success and improve revenues.
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