Solvemate Contextual Conversation Engine™ Enables More Meaningful Conversations to Eliminate Traditional Chatbot Frustrations
BERLIN, March 31, 2021 /PRNewswire/ -- Customer service experience automation leader Solvemate today announces the addition of natural language processing (NLP) capabilities to its customer service automation platform solution to create the Solvemate Contextual Conversation Engine™. This unique engine understands and resolves customers' questions faster and more reliably than any chatbot on the market today and in a way that is easy to build, train and maintain for low total cost of ownership.
Delivering on the Promise of Overhyped Chatbots of the Past
The Solvemate Contextual Conversation Engine™ addresses a need in the market to overcome the limitations of traditional chatbot algorithms which often leave customers frustrated when they can not find the answers they are looking for online. Until now, most chatbot technology companies tend to take one of two approaches: either a static decision tree or natural language processing.
Building on Solvemate's Innovative Dynamic Decision Tree Logic
The unique Solvemate Contextual Conversation Engine™ uses a powerful combination of NLP and Solvemate's dynamic decision tree (DDT) to precisely understand customers. The addition of NLP allows customers to type in their questions which makes them feel understood in real time in a personalized, one-to-one, conversational style. The combination of NLP on top of DDT offers a faster response time which helps build customer trust and loyalty. The Solvemate chatbot is context-aware by channel and individual user to solve highly personalized requests, in any language. If necessary, a human agent can always be included and handovers can be integrated into existing CRM or ticketing systems seamlessly.
The additional NLP feature was beta tested by today's fastest growing running shoe brand On. Verena Strunk-Wenzl, Global Head of DTC Customer Experience at On commented, "We tested the Solvemate Contextual Conversation Engine's™ full capabilities for a month and we saw user engagement increase by over 30% and were able to provide more helpful bot resolutions while keeping our CSAT up. We were already very happy with the results of the Solvemate chatbot but this will take our customer service automation to an even higher level and give us the insights we need to continue to improve our customer's experience with the brand."
This unique benefits of the Solvemate Contextual Conversation Engine™ include:
- Create a great conversational experience by guiding customers to find the right solution with both buttons and free text fields
- Offer a faster, more reliable resolution to customer's questions
- It's easy to build, train and maintain for low total cost of ownership
Jürgen Vogel, co-founder and CTO of Solvemate, comments: "NLP is a powerful technology, but NLP alone does not deliver the 'service automation' promise, especially not for SMB or SME companies that cannot spend massive resources in bot maintenance. That's why the Solvemate Contextual Conversation Engine™ is such a great solution - it combines the best of both worlds."
Solvemate's research and development was supported by the Pro FIT program of IBB and the European Fund for Regional Development (EFRE), which is focussed on industry-shaping innovation projects.
Read more about why Solvemate developed the Solvemate Contextual Conversation Engine™ from our co-founder and CTO of Solvemate, Jürgen Vogel.
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About
Solvemate enables brands to deliver quality customer service through meaningful conversations. Our customer service automation platform is powered by smart conversational AI that allows companies to create highly personalized chatbot conversations at scale, guiding customers to find answers when they need them, so service teams can focus their expertise where it matters most. Solvemate is trusted by brands such as musicMagpie, egym, JustPark, and Berliner Sparkasse. Learn more at solvemate.com.
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