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The New and Improved Chatbot—What it Means for Business


With new technologies and approaches, today's chatbots have come a long way from the traditional bots of years past. Learn what this means for the future of intelligent support.

Until recently, when you thought of a chatbot, you probably thought of something relatively simple—another format for that automated Interactive Voice Response (IVR) that you’ve heard on the phone. Those traditional chatbots (just like IVR systems) tend to fulfil basic tasks, but quickly falter if you try to say anything they don’t expect, or even just talk in an order they weren’t programmed for. While they do save time in some instances, the threshold for when escalation to a human operator would provide a better customer experience is not very high.

However, we are beginning to see a major change in the technology behind chatbots that will change all this. In the next 5-10 years, a combination of much greater availability of data and increased cognitive machine learning capabilities will give chatbots much more flexibility and power. They will become more and more autonomous, with the ability to handle complex tasks and deliver a personalized experience to both employees and customers.

The next generation of chatbots will enable improved or even entirely new customer journeys and overall experiences across all channels. Your chatbot will represent you to your customers, providing a unique experience and creating new relationships.

Enable Personalization through Cognitive Computing
To deliver this degree of personalization, organizations will first need to implement cognitive capabilities across their internal and external business applications. Cognitive computing is the computerized simulation of human thought, and it involves self-learning systems that use analytics, pattern recognition and natural language processing to simulate the human mind.

Cognitive computing is necessary to give both customers and employees the new experiences they increasingly expect. Organizations that want to provide this experience need to build dedicated platforms that are cognitive-first and cloud-first, because only this kind of platform can meaningfully harness the level of big data required to derive new insights and competitive advantage.

Once implemented, the applications using machine learning will be able to analyze vast volumes of data to make predictions related to user preferences, reliability of assets, or anything else. In retail, for example, major players like Amazon are already utilizing this technology, and the trend is quickly expanding to more and more businesses.

Mastering the Flood of Data
Cognitive platforms require a steady stream of data to operate successfully, but the data must be collected thoughtfully and with the right technologies. Multiple data sources and often overlapping data mining and analytics platforms can create an overly complex and challenging data environment, especially for SMBs.

Proper data science capabilities are needed to overcome this hurdle. Automating the discovery of data that matters and the subsequent personalization of customer journeys opens up the ability to offer unique experiences and predict what customers will want tomorrow. Taking advantage of AI and automation, organizations of all sizes can realize the full potential of their data.

Create New Customer Experiences
Chatbots, now harnessing cognitive capabilities based on big data, are becoming more intuitive and increasingly autonomous. A critical step to empowering this kind of chatbot is the use of a high-level declarative programming approach, where developers describe the goals for chatbots rather than giving them direct instructions. These advanced virtual assistants, such as NativeChat, will make 24/7 intelligent support an option for more businesses, leveling the playing field.

These bots will also function as agent bots, taking on increasingly complex tasks and making predictions about what users need. Human agents will have the freedom to be more strategic, and we will see new roles created dedicated to designing customer journeys.

Finally, if your organization has a customer-centric approach, your mission-critical applications need to be connected, quick to market, reliable, secure and easy to evolve to deliver the kinds of experiences your users expect

 

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