Comparing chatbot platforms: Mobile Coach Platform vs. Lex

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An energy services company located in Texas were looking to employ a chatbot to reduce operational costs for its contact center. So, they compared chatbot platforms because of the rapid growth, customers were growing increasingly impatient with the long wait time. This company embarked on an evaluation to determine what chatbot provider would best meet their needs.

Primary Requirements

 
  • Robust automation functionality. The chatbot needed to handle large volumes of user inquiries and intelligently respond.
  • Planned resolution paths. There had to be a clear handoff to a human agent for resolution.In case a user’s query was too complex or too unclear for a chatbot to respond automatically.
  • Elegant user experience. Customers had to be able to maneuver within the chatbot intuitively. 
  • Easy authoring and management. With limited staff, this company needed their chatbot solution to be easily managed. 
  • Secure. They required the highest level of security and privacy for user data.
  • Cost-effective. They needed the chatbot solution to drive a strong ROI, and so costs needed to be reasonable and controllable

Comparing Mobile Coach Platform and Amazon Lex

After several months of diligence, the company came down to two chatbot provider finalists for their final round of chatbot platform evaluation, Amazon Lex and Mobile Coach.

Mobile Coach’s platform scored higher on virtually every requirement. However, Amazon Lex’s business model initially seemed more appealing. The reason is that Amazon’s pricing model was based on the number of messages the chatbot exchanges with users while Mobile Coach’s pricing model was based on the number of end-users. 

Initial cost analysis based on the forecasted number of users and interactions showed that Amazon Lex could be less expensive than billing. On the other hand, Amazon Lex’s platform required the company to deploy software engineers to set up the chatbot and engineering budget for maintenance and support over time. Mobile Coach’s easy-to-manage platform means that non-engineers can easily stand up and manage even the most complex chatbot experiences. 

Calculating total project costs of resources needed to set up and manage the chatbot, Mobile Coach became the clear winner in comparing these two chatbot platforms in terms of overall value. Not only did it have a more robust and enterprise-friendly platform, but it also delivered an overall stronger value proposition.

Final Decision

The company eventually launched a series of three chatbots in 2020 with Mobile Coach. Almost immediately, they saw a reduction in contact center costs by 20%.  They are looking to expand their use of the Mobile Coach platform in 2021.

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