Summary
Data is digital gold, but untapped, it's worthless. In 2017, Gartner estimated 80% of data collected went to waste because it was unstructured.
These billions and billions of bytes have become a nightmare for businesses because they have neither the time, nor the financial or technical means, nor a conversational AI tool to exploit this data.
With the democratization of artificial intelligence, data structuring and analysis has become infinitely more accessible. As a result, fields like revenue intelligence and conversational AI have grown exponentially. To get a better idea of the conversational AI tools on the market,
Best 10 conversational AI tools
Gone are the days when you had to spend long minutes or even hours listening to dozens of recorded calls to recall a piece of information or identify an opportunity Here's a list of the best conversation intelligence tools:
- Modjo
- Gong
- Chorus AI
- RingSense
- DialPad AI Voice
- Conversica
- IBM Watson Assistant
- Amazon Lex
- Microsoft Bot Framework
1. Empower By Ringover
Empower by Ringover offers a range of conversational intelligence tools that prove useful for companies wishing to improve their productivity, customer experience, sales enablement, or coaching and training processes.
Empower integrates easily into your current tech stack. In fact, the software plugs into your VoIP phone software to retrieve call recordings for transcriptions and in-depth analysis.
Empower supports French, Spanish, and English. Plus, it can automatically translate, thus facilitating collaboration in international teams. This translation also works for call summaries.
The software lets you search for terms you choose within customer conversations, and even tag them for future reference. It's an easy way to identify topics, opportunities, and trends–organization which works to surface strategic insights.
In addition to these features, you'll find a strong sentiment analysis service, which helps agents understand the customer's state of mind during specific moments in the call. To give further insight into the agent's performance, Empower also compiles specific performance metrics. This information clarifies where the agents need to improve and what their strong points are.
2. Modjo
Modjo is a French company that was founded in 2020. With a focus on transcription, Modjo attempts to support sales teams in optimizing their performance.
However, this specialization can prove an obstacle for companies wishing to align relevant teams like marketing, customer success, or sales.
Pros
- Supports sales training
- Can be integrated with the most widely used telephony and CRM software
Cons
- Transcription inaccuracies in some cases
- A sometimes confusing user experience
3. Gong
Gong is one of the pioneers of conversational intelligence. On the market since 2015, it's aimed at sales teams, offering insights into each of their interactions with customers and prospects. For example, Gong helps to identify causes of and anticipate churn.
Pros
- Extensive integration catalog
- Number of languages supported
Cons
- Agents don't receive personalized feedback
- Poor user experience
4. Chorus AI
Also founded in 2015, this AI solution for conversational AI specializes in extracting data from exchanges between a company and its customers. Chorus AI's primary use is to identify why a deal fails or succeeds, but its technology can also be applied to other sectors such as recruitment and marketing.
Pros
- Identification of conversation themes
- Free trial available
Cons
- Very limited search capabilities
- Complicated onboarding phase
5. RingSense
Like Ringover, RingCentral is one of the market leaders in cloud telephony for businesses, and has also developed its own conversational AI tool.
Called RingSense, this tool too can identify opportunities that lie in hours of previously unanalyzed conversations. Once again, RingSense was developed for sales teams.
Pros
- Large catalog of integrations
- Supports email interactions
Cons
- Languages are limited
- Lack of pricing transparency
6. DialPad AI Voice
DialPad has also developed its own AI-powered conversational analysis software. DialPad AI Voice focuses on call transcription and note-taking. Dialpad AI Voice simplifies after-call tasks such as lead qualification.
However, you must contact Dialpad's sales team to obtain a personalized quote. The company does not disclose the pricing for this product.
Pros
- Attractive integration catalog
- Supports interactions via email
Cons
- Languages are limited
- Lack of transparency on pricing
7. Conversica
This software focuses on lead engagement and following up with prospects. The conversational AI technology comes in because Conversica can have useful conversations with leads and current customers.
Pros
- Potential for increased conversion rates
- Detailed analytics on lead interactions
Cons
- Pricing isn't listed online, but sources online quote it in excess of $2,000 per month. This may be prohibitive for small- and medium-sized businesses.
- Certain conversations may be too complex for the software
8. IBM Watson Assistant
This is a highly developed platform which offers both chatbots and virtual assistants. IBM Watson Assistant has been on the market for some time, so it offers a relatively advanced ability to interact with prospects and clients.
Pros
- Advanced conversation ability
- Integrations possible with other IBM services
Cons
- Poor user experience, it can be difficult for both users and developers
- Given the advanced functionalities, the price is quite high
9. Amazon Lex
Amazon has to have their say in the conversational AI market, and it's come in the form of Amazon Lex. This tool is more targeted toward developers, as it supports them in creating chatbots.
Pros
- If you already use AWS services, this integrates relatively easily with them
- No need to worry about infrastructure management
Cons
- The bots struggle to understand accents or certain speech inflections
- Quality also decreases when using Lex with the phone
10. Microsoft Bot Framework
Similar to Amazon Lex, Microsoft Bot Framework platform is meant to support developers in building conversational AI applications. The product includes various features and software development kits (SDKs).
Pros
- If you use Microsoft Azure, there are native integrations available
- Great tool to make responding to frequently asked questions more efficient
Cons
- Code is relatively complex and requires significant technical expertise
- Complicated to use it in conjunctions with other technologies
What is conversational AI?
Conversation AI helps companies to analyze telephone interactions with their customers and identify certain topics and trends. The technology provides companies with insights about their market, customers, and prospects.
What is a conversational AI platform?
A conversational AI software, which is often called sales enablement tools, is natural language processing (NLP) software capable of performing in-depth analysis of textual or spoken elements, and determining the emotion and intent behind each message.
This technology can be used to support multiple functions. One application of conversational AI is chat bots which are capable of responding to queries from clients or prospects. Conversation intelligence tools can also integrate with the company's business phone system to record calls or retrieve existing audio data.
Conversational AI tools can also integrate with a company's telephone system to analyze audio data, conduct sentiment analysis, and automate transcriptions thanks to speech-to-text.
Such software is generally based on artificial intelligence technologies that have been trained using NLP, models, and machine learning–all of which contributes to the results' relevance and efficiency.
What are the benefits of conversational AI software?
Conversational intelligence solutions offer real advantages and opportunities for the companies that use them, particularly for sales teams. Generally simple to use, they don't require any particular technical expertise. Here are a few of the biggest advantages offered by conversational AI:
Promoting best practices
With conversation analysis, you can identify the best practices within your team. Conversational AI tools help you understand the key factors that top performers rely on to close more deals. These practices can then be shared with the entire team to improve the department's overall performance.
Identifying and analyzing trends
One of the most important features of conversational AI software is its ability to quickly analyze large volumes of data. Based on the nature of your conversations with customers, there are likely trends that emerge. Empower allows you to clearly identify and classify these trends with tags. This visual information helps you quickly identify what works well or what needs improvement, enabling you to understand how your customers' needs are evolving.
Providing clear feedback
With access to multiple data points and metrics (turns speaking, monologues, interruptions, sentiment analysis, etc.), managers can provide more detailed feedback. They can also quickly assess the relevance of each sales agent's pitch by looking at the statistics associated with each call, allowing them to provide better coaching.
By leveraging conversational AI, sales teams can optimize their strategies, adapt their approach to customer needs, and ultimately increase their chances of closing more deals.
Improved, AI-supported coaching
AI tools provide an overview for managers, who can easily identify areas of improvement, control the relevance of the sales pitch, identify performance factors, and use them as a pillar to create a team culture.
An enriched CRM
The information collected during each call enriches the corresponding customer records in your CRM to centralize data and ensure that you have up-to-date data. This is guaranteed by the integration of conversation analysis tools within the CRM.
Optimized onboarding
New recruits have direct access to customer conversations and can rely on the most effective factors and practices to interact with their prospects. They become operational more quickly, and debut with a higher quality than they would otherwise.
Aligned teams
Finally, the last advantage in this list and not the least concerns the alignment of the different departments. The conversational AI analysis contributes to this by making the collected data available to all teams, whether it be the marketing team, the customer service team, the support team, or of course the sales teams.
Conversation intelligence vs revenue Intelligence: what's the difference?
These are two similar concepts, as both deal with acquiring and analyzing data from customer or prospect interactions. The main difference is how the data is used. Conversational AI focuses on the acquisition and analysis of conversational data, the insights from which are then disseminated across an organization, while revenue intelligence focuses on transactions and usually looks at a greater variety of data sources.
Features of Conversation Intelligence
Conversation intelligence generally reveals information around three main issues:
- Team performance
- Revenue and risk prevention: identifying the best practices and eliminating poor habits
- Decision making
Features of Revenue Intelligence
Revenue intelligence encompasses all the features of conversation intelligence, except it goes beyond the conversational exchanges between the company and its customers. In fact, revenue intelligence will incorporate non-conversational data using other sources and provide an overview for salespeople.
In conclusion, conversational AI leverages previously unexploited data and is gradually becoming a fixture of daily life for salespeople, complementing their arsenal of sales software.
Tools such as Empower help companies lead this revolution by allowing them to optimize their strategies and maximize their revenues. In this sense, conversational intelligence acts as a growth catalyst while allowing brands to remain competitive and in line with their customers' needs. Test conversation intelligence with Empower now. The trial is free and does not require a credit card.
Conversation Intelligence FAQ
Why is conversational intelligence important?
Conversational intelligence is important for companies as it helps them strengthen their customer relationships and optimizes their sales and marketing strategies. Thus, it stimulates their growth.
How can I improve my conversational intelligence?
One of the key elements to improve your conversational intelligence is to adopt active listening during each exchange to adapt your communication to the context. To improve your conversational intelligence, you can also use an analysis tool to better understand your interlocutor and respond to their needs appropriately.
What is a conversational intelligence platform?
A conversational intelligence platform is characterized by a set of tools capable of capturing, analyzing, and interpreting written or verbal interactions and facilitating communication between a company and its customers.
What is conversational intelligence compared to revenue intelligence?
The concepts of conversational intelligence and revenue intelligence are often confused. However, they are not entirely identical. Indeed, conversational intelligence focuses on optimizing exchanges and relationships between the company and its customers, while revenue intelligence focuses on maximizing financial benefits.
How does conversational intelligence work?
Conversational intelligence or conversation intelligence is based on the analysis of large volumes of linguistic data, itself based on artificial intelligence capable of extracting and interpreting this information in order to improve understanding and use by the professional.
