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Market Compass
The KuppingerCole Market Compass provides an overview of the product or service offerings in a certain market segment. This Market Compass covers conversational AI building platforms with a focus on chatbot solutions. Such solutions are a common trend in marketing, sales, service management, human resources, and many other use cases.

1 Management Summary

The KuppingerCole Market Compass provides an overview of a market segment and the vendors in that segment. It covers the trends influencing that market segment, how it is further divided, and the essential capabilities required of solutions. It also rates how well these solutions meet our expectations.

AI-based conversational interfaces developed plenty of hype for use cases within marketing, sales, and service management. Various types of solutions are on the market, offered by both small start-ups and large, international, established enterprises.
This Market Compass covers solutions based on chatbots that use machine learning to manage and continuously improve communication flows.

Conversational interfaces experienced hype in 2016, followed by some disillusionment in the next years, as many solutions were technical gadgets rather than delivering real value. This is about to change, as many solutions are more mature now—and implemented as a part of digitalization projects within marketing, sales, or service management. It is expected that the market for conversational AI building platform will grow significantly within the next several years.

Marketers and service management experts see conversational interfaces as a key topic when it comes to customer-centric approaches. Furthermore, conversational interfaces are becoming more popular among organizations for internal communication and service management.

Ideally, the choice of a conversational AI building platform is based on a proper business or use case, considering individual requirements, as there are many solutions on the market, each with specific strengths.

The quality of the conversational flow is only one criterion among many. Considering which channels and devices to support is crucial and depends on each use case. Furthermore, the ability to integrate with third-party systems is an important criterion, as conversations with a chatbot are usually part of a complex customer journey or business process. Therefore, it is important to consider the whole scenario when implementing conversational interfaces.

Some vendors offer solutions with a narrow focus on conversational interfaces and offer connectors to integrate with other systems. Others offer comprehensive suites covering other aspects, such as data management, marketing automation, and customer relationship management. An organization’s individual situation will determine which approach fits better. There is no right or wrong. In some cases, there already exists a best-of-breed approach, which means that it makes sense to integrate a solution with a narrow focus on conversational interfaces into an existing systems landscape. In other cases, the right way might be to implement conversational AI building platforms within a project with a larger scope, e.g., including more marketing automation or service management components. In every case, it is crucial to consider a clear business case, including change management procedures.

In general, it is important that requirements in terms of front end (communication with users) and back end (configuration, machine learning processes, analytics, and interfaces) are fit for purpose.

The practical experience of a vendor with similar use cases can be beneficial. Many vendors support their customers when setting up conversational flows; preconfigured conversational setups are also available and can be used as a foundation. In such cases, a vendor’s experiences with a particular business sector is helpful.

In terms of scalability, many vendors offer flexible models that can scale from technical and financial points of view. When it comes to international projects, the availability of and support for multiple languages is mandatory and supported by most systems. In such cases, the availability of preconfigured data can be helpful as well.

Whenever it comes to the processing of personally identifiable information (PII), compliance with relevant legislation (such as GDPR) is mandatory and ensured by most systems in general. Nevertheless, each individual scenario will have to be checked accordingly, especially when it comes to integration with third-party systems, such as social networks.

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