For all businesses, being able to leverage clear, actionable insights from unstructured communications can deliver amazing benefits. In the contact centre, companies are constantly engaging in discussions with customers which house hidden information about preferences, sentiment, and intent.
Unfortunately, in the past, surfacing the right insights from raw conversations wasn’t always easy. Many companies were forced to manually assess each conversation, requiring a significant investment in time and money. Conversational AI solutions can eliminate this problem. With new tools for conversational AI, businesses can dive deeper into the meaning behind each discussion.
The right solutions not only provide useful insights into customer preferences and requirements, but they can also offer guidance on how to improve the efficiency of any workplace. Here’s how businesses can ensure they’re choosing the right vendor for their CX conversational analytics needs.
Step 1: Set your Conversational Analytics Goals
The first step in choosing the ideal vendor for any new technology, is setting the right goals. Companies with a clear understanding of what they want to accomplish when leveraging conversational AI will be able to prioritise the right features and functionality when comparing vendors. After all, there are a number of ways to implement this technology.
Companies hoping to expand their existing communications strategy to include more self-service features may consider building their own conversational AI chatbot or voicebot from scratch. Alternatively, those looking to leverage more meaningful insights into concepts like customer sentiment and intent may focus specifically on software for tracking data.
When setting goals for conversational AI, keep in mind these tools often work best when they have access to a versatile selection of data points. The right technology should always be able to integrate with existing tools, whether a CCaaS system, or a CRM deployment.
Step 2: Choose your Analytics Deployment Strategy
Conversational Analysis as a concept is growing at an incredible pace. Currently, the market is set to reach a value of $41.39 billion by 2030. As trends like hyper-personalisation take over in the CX marketplace, and companies become reliant on data-driven decision making, the need for AI-driven tools has prompted a rise in a variety of different solutions.
Today’s companies investing in conversational AI can choose from a range of different options for deploying their technology, including:
- Integrated analytics: Analysis and AI tools designed to integrate with the existing CRM, CX, and contact centre technologies already present in the business.
- CPaaS and APIs: Flexible tools which work on top of existing applications and systems, like Facebook Messenger, WhatsApp, and dedicated business communication apps.
- Advanced CCaaS: Many contact centre vendors offering CCaaS are now providing conversational AI tools as part of their complete kit of features.
Companies planning on moving their entire contact centre into the cloud with a CCaaS system may benefit from looking for a vendor with an in-built conversational analytics strategy. Alternatively, brands simply looking to add to their existing technology with AI bots and conversational analysis could consider using APIs and tools designed to integrate with pre-existing technology.
Step 3: Explore Available Feature Sets
As mentioned above, there are a number of use cases available for conversational AI in today’s landscape. The most common way to use this technology among most companies, is to derive better insights into customer experience and the consumer journey. An analytics tool capable of assessing trends and patterns in customer interactions can make it easier to plan better service efforts.
