Conversational Analytics tools are quickly becoming a must-have for modern brands. After all, companies collect huge amounts of unstructured data from discussions every day. However, leveraging actionable insights from this data can often be time-consuming and complex.
By implementing AI solutions with Natural Language Processing capabilities into your UC and contact centre systems, companies can uncover hidden gems among streams of information. The right solutions not only show business leaders how to improve customer experience and sentiment but can also pave the way for better collaboration and team performance too.
The biggest challenge for many business leaders is figuring out which vendor to work with on their new conversational analytics investment. Here are some top tips to help you find the company best suited to deliver your AI goals.
Step 1: Identify your Use Cases
The first step in choosing a Conversational Analytics vendor is deciding what you want to accomplish with your AI tools. Notably, it’s worth looking beyond the basics of using NLP solutions to drive better customer conversations here. While its true conversational analytics can help you to enhance CX with more personalised, meaningful conversations, the right technology can also serve a variety of other purposes.
For instance, as the world shifts more progressively towards a future of hybrid and remote work, we’re relying more extensively on meetings to keep teams connected. To prevent staff members from wasting time in inefficient meetings, companies can leverage conversational analytics to make discussions more valuable.
AI systems equipped with NLP and NLU functionality can recognise the sentiment and emotions of employees in meetings to determine which staff members might be disengaged. These tools can bridge the gaps between distributed workers in different countries through automatic transcription and translation services. Some tools embedded into virtual assistants and bots can also respond to keywords spoken in a meeting to provide team members with relevant information and documents instantly.
Step 2: Consider How You’ll Implement Conversational Analytics
As insights from natural language become more crucial to the functioning of many professional entities, there are now various ways for teams to implement these tools into their workflows. Brands may decide they want to work with a CPaaS vendor to integrate conversational analytics capabilities into existing tools for collaboration and voice recording.
Other business leaders making the transition into a new age of work with their employees might want to access all-in-one solutions, where conversational analytics are delivered as part of a feature set. For instance, if you’re planning on building a new immersive environment for hybrid work, you might want to leverage a tool like RingCentral for collaboration, which already has tools for smart meeting analysis built in.
In some cases, you may even want to build your own UC tools with conversational analytics capabilities from scratch. This could involve working with developer resources and machine learning ecosystems to design custom chatbots, virtual assistants, and similar solutions. This path would give companies the freedom to leverage conversational analytics in the way most likely to benefit their employees and users.
Step 3: Know Your Existing Environment
While assessing how you’re going to implement your conversational analytics strategy into your business, it’s also worth considering your existing environment and tech investments. For instance, if you’re already using a tool like Microsoft Teams to keep your employees aligned in a hybrid workplace, the AI services you implement for meeting insights will need to work seamlessly with the landscape you’ve built.
If you’re creating a conversational analytics bot to work as an assistant alongside your employees, surfacing valuable information from different environments, integrations will be crucial. You’ll need your solution to be able to access various software systems, like CRM tools and helpdesks, so it always has access to the right data for various user needs.
Even if you’re building a new cloud communications environment from scratch, it’s worth thinking about the various tools that will be responsible for collecting data in this new ecosystem. The more your solutions are connected, the easier it will be to create a single source of truth for your analytics requirements. Look for a vendor with the right level of flexibility and extensibility for your needs.
Step 4: Consider Your Support Needs
While many companies are beginning to recognise the value of conversational analytics for improving both customer and employee experience, the concept is still relatively new. Not every business will have access to experts in machine learning, data analytics, and bot creation. Without the right support on hand to help you leverage your new investment, you won’t be able to see the true benefits conversational analysis can offer.
With this in mind, it’s worth looking at the level of support and guidance you can access from your vendor. The right partner in your transformation project should be able to work with you on implementing your technology and pursuing your goals. They may be able to show you how to align your different databases to create a more powerful analytics strategy.
Some vendors will also be able to work with you to provide training to business leaders and employees, so they can make the most of the analytical system. At the very least, the vendor you choose should have plenty of documentation and educational content available to assist you with your new AI initiative. The more support you can access, the easier adoption will be.
Step 5: Remember Your Future Needs
Finally, it’s worth thinking about your needs both now and in the future when investing in an AI-focused strategy like conversational analysis. The worlds of analytics and AI are evolving at a rapid pace, and it’s important to ensure you can keep up with the latest trends.
Right now, your focus may be on making meetings more efficient for your team members with simple NLP tools. However, in the future, you might want to implement bots capable of responding to certain alerts in a meeting and performing automated actions. You may also want to connect your conversational analytics strategy throughout your UC and CCaaS systems, so you can unlock the benefits for both employee and customer experience at the same time.
Looking for a vendor with a strong focus on the future and the ability to assist you in taking advantage of new initiatives will be crucial. I am running a few minutes late; my previous meeting is running over.
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