Product Engineering

by Azilen

September 05, 2018

Top Five Fundamental Rules to Make the Most Out of a Chatbot

Conversational AI phenomenon has been around since 1960. However, its prevalence as chatbots has been escalated in last few years due to:

Computation power and availability of high volume data sets
Advancement in technologies related to AI and machine learning
Compatibility of Conversational AI with all major digital platforms such as social networks, web apps and messaging apps catering wide range of end users

Why chatbots are on the way of being new normal?

So far, chatbots have already proved their worth in:

Providing 24x7x365 seamless and monitored services to the user
Making the interactions cost effective due to minimal or no human involvement

Moreover, the AI enabled Chabot is anticipated to be a potential tool furnishing the industries with advantages such as:

Automated interactions: Connected with backend, chatbots can automate predefined processes and even transactions. For example, after responding initial inquiries, the travel chatbot can directly navigate the user to relevant booking page where the user can complete the entire booking process.
Future positioning: A chatbot with pleasing personality that can drive the brand value is a must have feature to stay tuned with current trends as well as to avail future positioning
Enhanced Customer Experience: Customer experience is all about how customers perceive their interactions with the organization during their entire customer journey. Chatbots can be a significant part of carefully crafted customer experience strategy. In fact, AI bots provide personalized, to the point and relevant information that make the customer on boarding a quick and delightful experience.

Which types of Chatbots actually fulfill above expectations?

Conceptualizing a high-yielding Chatbot requires sensible strategies so that they can deliver amazing customer experience, add brand value and differentiate the company into the market place.

Technology providers are coming up various APIs and platforms with ready to use functions to enable Chatbot development with less of programming. In such scenario, only well-analyzed and tactical development and deployment of technically robust chatbot can make the desired mark. First, let’s understand three basic challenges.

Conversational UI: Catboats differ to traditional UI as they directly communicate with users using one or couple of sentences at a time. Thus, there are possibilities of communication gaps leading to user frustrations. How the bot is expressing itself to the user utilizing effective cues is without any exaggeration, a game changing factor.
User Expectation: Users are getting habitual with virtual assistants such as Amazon Echo and Siri. Hence, their expectations are more of those kind of experiences. Businesses are expected to deliver similar digital experiences for comparatively more process specific or complex operations.
Technology Stack: The backbone technologies of the chatbot, AI and Machine Learning are still not at the mature stage. Sometimes, developers do struggle in coping with them. The other factors such as working over context or memory of the chatbot, bot integration with HRM, CRM or ERP like legacy system and applying brand specific persona to the bot require in-depth technology expertise.

Overall, the chatbot success factor is all about the bot’s capability to hold smart, interactive and helpful conversation flows. This requires something more than coding or programming.

Development of yielding chatbot starts with 360-degree contextual analysis. Furthermore, we need to mind the key components such as robust technology stack, ability to understand and keep the record of individual user’s context and preference, multi-tasking and self-learning capabilities, and Omni channel seamless experiences.

Following are few of the fundamentals for the same.

[1] Chatbot-to-System Integration for seamless interactions

The chatbot must be connected with backend system in order to provide personalized or transactional interactions. In general, enterprise backend systems are kind of integrated solutions made of multiple systems ‘seamlessly talking to one another’.

These integrated systems have their own abundance of data, data processing powers and infrastructural capabilities. Moreover, enterprises prefer Omni-channel bots to cater maximum users. In such scenario, flawless integrations utilizing efficient Channel Adaptors and APIs are prime requirements to deliver relevant user experience.

[2] Administer Omni-channel bot functioning well

Omni-channel deployment is a necessity to be available to the wider range of audience. It also offers flexibility to customers and users. It is mandatory to keep following particulars in mind:

Well craft the user interface elements and responses start with any one channel
Make sure that the user can maintain the conversation history across all channels
Define the secured authentication criteria, centralized updates across channels
Leverage Active Directory and other relevant tools

[3] Efficient NLP engines make difference

Users are going to use different and broad range of communication habits to convey their messages. Hence, the role of NLP engines is critical and it must have efficiency to deliver interactive responds.

The engine must understand the user input regardless of spelling mistakes, grammatical mistakes or type of sentence structure. Language keywords need to be mapped with multiple synonyms in order to make intent recognition quick and easy. High degrees of efforts are required in this area during the bot development process.

[4] Realistic and Sensible User Engagement

If any of your bot conversation creates inconvenience or deliver a bit of disappointment, it will leave negative impacts to your brand experience. As bots are still in the stage of infancy, there will be a gap in the user’s digital experience expectations and the reality.

Simplicity and straightforwardness cannot be compromised while experimenting innovative ways to create delightful user engagement
No matter, how complex or complicated the process is, it is imperative to make sure the user should not be forced to adapt too much for each scenario. On the other hand, the bot extension must bring an actual uplift in productivity of the business’s workforce.

[5] Backing the bot with multiple process accelerators

It is essential to figure our process accelerators such as radio buttons, calendars or other relevant widgets that make the user response or task completion quick and simple. Embed the pleasing UI elements to make the experience both interactive and satisfying. Even human intervention may sound sensible in some cases.

Mobile

Conclusion

Businesses have high expectancy from AI enabled Chatbots and Chatbot development companies are keeping the maximum efforts to fulfill those expectations.

However, artificial intelligence is not a magic but a science. When a perfectly developed bot architecture aligned with well thought of functional and conversational design strategies keeps learning from the customer interactions, it evolves as a much rewarding technology tool. Additionally, such bot needs to be enhanced time to time to cope with changing trends of time, technology and market.

Azilen