Around the world, countless companies are investing in conversational intelligence software to gain a competitive edge in the customer experience landscape.
Offering valuable insights into customer sentiment and the reasons behind loyalty and churn, this software unlocks endless opportunities for organizations. That’s one of the reasons the market is expected to reach a value of $46.8 billion by 2033.
However, as demand for AI analytical tools increases, so does the number of solutions business leaders have to choose from. Here’s your guide to effectively comparing conversational intelligence software in 2024 and beyond.
Step 1: Examine your Conversational Intelligence Use Cases
The first step in comparing conversational intelligence software is defining what you want to accomplish with these tools. Innovative AI vendors offer solutions to address a range of use cases. For instance, you might use conversational intelligence software to empower your teams. You could create assistants that can analyze sentiment, surface data, and deliver coaching in real-time.
Alternatively, you may want to use conversation intelligence software to help you build and optimize your self-service strategy. Infusing AI bots with tools to analyze customer tone, sentiment, and intent can help you rapidly deliver valuable 24/7 support to your audience.
You might even consider looking at tools that can help you overcome issues with quality assurance monitoring, CSAT (Customer Satisfaction) scoring, and compliance. Whatever your requirements, ensure you have a plan in place for tracking the success of your initiative.
Step 2: Consider your Data Landscape
Once you know how you will be using your conversational intelligence software, the next step is figuring out which types of data your solution needs to process and leverage. As demand for omnichannel communications continues to increase, conversations in the contact center are evolving.
The right solution should allow you to collect and consolidate interactions from all the discussions you have with customers. It should be able to utilize natural language processing and understanding features for speech analysis, as well as give you insights into the intent and sentiment behind messages and emails.
Most importantly, your solution should make it easy to maintain a consistent view of the customer journey, aligning your data for you, eliminating inconsistencies, and improving accuracy. Ensure your software can bridge the gaps between all of your communication tools.
Step 3: Explore Deployment Options for Conversational Intelligence Software
The next stage is figuring out how to implement conversational intelligence software into your existing technology ecosystem. If upgrading your contact center technology and shifting processes into the cloud, you may look for an innovative CCaaS vendor. Some contact center as a service providers build conversational intelligence into their technology.
Another option could be to use an API or integration to implement a standalone solution into your existing CRM or contact center system. When looking at deployment options, focus on flexibility, scalability, and opportunities for customization.
As your contact center evolves, you may need to scale your system accordingly. The right vendor should help you to take full advantage of the software available to you as your business grows.
Step 4: Remember Security and Compliance
Conversational Intelligence software works best when your system can access huge volumes of data. The more you can feed your ecosystem with information about your customers and your business, the more effective it will be.
However, data in the contact center is a valuable resource prone to attacks from outside parties. To stay compliant with the latest data privacy standards, and protect your company’s reputation, you must ensure you’re collecting, storing and managing data correctly.
Look at the solutions your vendor offers for end-to-end data encryption and how much control it gives you over access policies. Ensure you know how data is collected and used by the system.
Step 5: Explore Opportunities for Innovation
Most of the leading conversational intelligence software solutions available today feature many of the same capabilities. They include natural language processing technology, machine learning algorithms so they can improve over time, and may even come with built-in sentiment analysis.
However, some leading solutions offer more advanced capabilities for various use cases. For instance, some tools use generative AI and large language models to help businesses create powerful bots for agent assistance and self-service.
Other solutions can include features for automated omnichannel journey mapping, content transcription, and translation, or data categorization. There are even tools that can automatically score conversations based on factors like compliance and customer sentiment.
Step 6: Prioritize Customer Service
Finally, when investing in innovative tools like conversational intelligence software for the contact center, the right support is crucial. The right vendor should make it easy to onboard employees and train them on using your ecosystem. They should offer access to detailed documentation, training videos, and guidance for your entire team.
They should also be able to help you integrate various parts of your communication stack with the analytics software. Look for a vendor that offers step-by-step assistance with your deployment and opportunities to scale your investment.
A good vendor will ensure you can optimize the results of your conversational intelligence software and increase your return on investment.
Comparing Conversational Intelligence Software
Conversational intelligence software has emerged as a vital tool in the customer experience landscape. With the ability to surface valuable insights from every critical conversation, this technology can give you the information you need to grow.
Use the steps above to carefully assess the vendors and solutions available in the modern market and ensure you can get the most out of your AI investment.
