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Delivering Fast and Effective Chatbot Solutions: Strategies for Success

In this special guest feature, Vikram Khandpur, Chief Product Officer at Sinch, discusses how at the core of its capabilities, chatbots bring to life data-backed communications technology. Vikram is a seasoned product executive who is leading a diverse portfolio of CPaaS and SaaS products at Sinch (XSTO: SINCH), a global leader enabling CPaaS and customer experiences for thousands of companies. He had a decade-long career as an accomplished product leader at Microsoft, where he shipped category defining B2C and B2B products such as Skype and Microsoft Teams. He loves building product teams with a vibrant culture and enjoys forging win-win partnerships with other brands and channels to unlock product distribution and user acquisition.

AI, machine learning, and the world of big data are driving forces behind the future of work. The possibilities of streamlined business operations with automation are endless, and the desire to implement these solutions is becoming a critical component in effective user engagement. At the core of its capabilities, chatbots bring to life data-backed communications technology.

A recent Gartner study found that organizations that embed AI in their multichannel customer engagement platform will elevate operational efficiency by 25% by 2025. A platform that enables strong, consistent automated information is increasingly critical to the flow of communications as a key business differentiator. COVID-19’s rapidly evolving impact has led many organizations to speed up AI implementation but, if not done thoughtfully and strategically, risks stifling the full impact of chatbots. What’s most at risk from rushing: failing to place empathy at the heart of conversational design, and using a complex, heavy-code framework.

To make the strongest impact, here are three effective strategies to develop smart chatbot solutions that power streamlined business communications — no matter how quickly an AI platform is integrated.

Give bots a framework of empathy and humanity

Even on a time crunch, the tone and cadence of a chatbot’s communication flow should never feel robotic. Chatbots often act as the first point-of-contact for a user. This means clear, consistent, and empathetic information-sharing is critical. Keeping an authentic, personalized tone when developing a chatbot conversational design can help to mimic the assistance of a service agent without the long-waited connection times. Often, platforms chose to use a Natural Language Understanding (NLU) framework that breaks down complex inquiries to create a more natural two-way conversation between user and bot. Sentiment analysis is another technique in AI integration that uses algorithms to check the mood of a user and tailor responses according to the appropriate sentiment.

With an empathetic foundation, a chatbot should also foster maximum accessibility by including the ability to translate and compute conversations in non-English languages. This not only ensures that user inclusivity is not ignored, but it also guarantees all inquiry data is effectively tracked and measured.

Simple frameworks yield impactful results

Implementing automated technology to meet the rising demand for self-service and around-the-clock assistance at lower operational costs is just one of the key factors driving growth in the chatbots market. With this emphasized desire to quickly integrate low-cost, hyper-speed solutions, a no-code or low-code framework is more important than ever for high-impact, optimized chatbot development. For example, platforms such as Chatlayer.ai are created with businesses in mind, making the implementation so intuitive that an experienced IT team is not a necessary piece of the integration launch, which decreases ramp-up time to subsequently reach users faster.

A multimodal, omnichannel-enabled platform that provides accessible communications across devices is especially important when users are spending more time at home. With several mediums to reach businesses, people crave the flexibility to connect through mobile devices, tablets, laptops, or desktops. Chatbot solutions should be as adaptable as its users and integrated into any channel — including web, SMS, or any chat application such as WhatsApp — for quick and easy access to critical information.

Use data to stay agile

Chatbot inquiries evolve as quickly as the environment around us and, in times of uncertainty, data is the best way to keep track of key trends. The volume, frequency, and overall patterns of information a chatbot receives on any given day can give businesses incredible insight into what is working and what needs to be adjusted, which is especially vital in cases of quickly implemented solutions. Smart frameworks gather a holistic view of the nature of concerns and quality of response. As would a service agent, chatbots must stay agile, trying new techniques and conversation flows for better communications. The self-learning abilities of chatbot solutions — driven by data-backed insight — can have a powerful effect on the ways in which businesses evolve communications to best fit the needs of users.

In 2020 and beyond, purpose-built AI will be a key competitive differentiator in business communications — and essential to delivering at a time when people across the globe crave interaction with a continuously changing business landscape.

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