Choosing the Right Conversational Analytics Vendor in 2022

How to find the ultimate conversational analytics vendor

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Choosing the Right Conversational Analytics Vendor in 2022
Speech AnalyticsInsights

Published: October 6, 2022

Rebekah Carter

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.

However, the right conversational AI vendors can also offer a range of other features too. For instance, some solutions can come with the option to create custom, visual reports based on the information discovered, to share data with shareholders. Others will come with bot-building tools so companies can design their own self-service systems and intelligent IVRs.

There are conversational AI vendors who also focus on empowering team members, with agent assistance bots capable of surfacing information from any environment instantly into the contact centre during a conversation. Plus, many tools come with automation options, so companies can develop workflows based on conversational AI discoveries. For instance, a company could create a workflow that allows an IVR system to automatically route customers to an agent based on intent.

Step 4: Prioritize Excellent Support

The rising demand for conversational AI tools has prompted vendors to create a host of straightforward and easy-to-use applications. Even the solutions available for building self-service apps and bots have grown more accessible, with no-code and low-code functionality. However, accessing any AI and data-driven initiative can be complex.

Companies without their own data scientists and AI experts may need extra assistance to ensure their conversational AI system is delivering the right results. The best vendor should be able to provide end-to-end support for any company, starting with initial recommendations on how to use the AI tool, and training resources.

When searching for excellent support, it’s also worth assessing the user-friendliness of the technology in general. Examine how much work will need to go into training any bots or IVR systems implemented into the ecosystem. Consider the level of training required for team members who might be using the bot to navigate customer service requests.

Step 5: Plan for Compliance

Finally, conversational analytics relies heavily on data, and the ability to capture and analyse the conversations held with customers. This sensitive information is subject to a huge number of industry and government regulations, which businesses need to be aware of. Most vendors offering conversational analytics tools will be able to provide help with compliance.

Many solutions allow companies to choose exactly which information they capture from their customers, as well as what kind of data they need to keep out of their records. There are also solutions which can allow businesses to control the sovereignty of their data, by determining where records are stored, and how long they’re preserved.

Checking on the security and privacy standards implemented by any AI vendor is a good way to ensure a new initiative doesn’t lead to compliance problems.

 

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