If you are a growing company with a focus on latest technology – chatbot or simply bot should be a common word. With Facebook’s introduction of bots on FB messenger and growing popularity of Microsoft Bot platform, there is a marked transition of bots from toys to customer engagement and e-commerce tool. However, many businesses may ask – what’s the strategy for successful bot development and its best practices?
Here are some best practices for a successful bot development project.
First of all, building a successful bot requires some deep understanding of the customer’s product or services and it’s user base. First goal should be to understand what is the utility of this bot for the audience. According to the uses Bots generally fall into these categories: entertainment bots, commerce-focused bots, news bots, utility bots and customer service bots. Talk with them about the bot and really listen to their answers. Make sure that bot platform has feedback mechanisms and machine learning capabilities The development team should also pay attention to support logs and run regular analytics.
A clear idea of goals is very important to realize returns on investment in building a chatbot. Some of the practical objectives behind making a bot are opportunity to drive new sales, customer engagement, streamline internal processes, etc. Since chatbot is a technology(IT) endeavor, it requires developers and testers. It should be integrated into your larger information infrastructure and maintained. With changing goals and increasing product lists, the chatbot will require regular updating.
As bot technology improves, businesses finding their way into more use cases where human judgment and effort have traditionally been required. Some relevant business use cases are assistant bots, finance compliance, supplementing HR practices etc. The use cases can be classified and explained in terms of automation and augmentation. Automation of routine tasks can improve overall productivity and performance. Augmentation bots powered by artificial intelligence and natural language processing are better than humans at switching task and sifting through gigabytes of data. Bot can listen to a customer’s needs and help filter through a long list of choices, perform more accurate search, and finally prompting the user for relevant information as required. Also, a bot can accumulate targeted feedback during a chatbot conversation.
Businesses can build bots from scratch or use comprehensive bot frameworks aimed to mass-produce bots. Apart from tech giants like Microsoft and Facebook, there are numerous startups with their own frameworks and specialized offerings.
Prominent frameworks for building Bots are:
Custom bot development is also popular because relying heavily on a platform comes with the risk that the parent company can change terms and conditions. Also, businesses with a lack of clarity and development skills should approach a Bot development firm for making a bespoke bot.
A well-designed chatbot should automate routine tasks which are monotonous for an employee. Thus it should fit into your business model like an employee. A chatbot should have an understanding of the business logic and should easily communicate the end results to appropriate employee. Don’t expect everyone to come to the bot. The bot should be integrated with internal communication tools such as Trello and Slack. Don’t tell the sales team to log into a chatbot administration console to see what leads have come in. Export those directly to the existing sales management tools in use at your business. Also, avoid giving your chatbot an explicit product list that’s certain to continually fall out of date. Connect it to your existing product database.
Though bot is not a replacement for human to human interaction, the development team should make it user-friendly. This requires a conversational logic which has understands user’s perspective in terms of coherence and context. The bot should initiate the conversation and lead it.
Tone of chat is crucial for companies employing chatbot for commercial and customer service. For such organizations, chatbot becomes an opportunity to delight or enrage existing and prospective customers. The bot should elicit reactions similar to those of an employee. Showing concern and understanding towards a frustrated customer can calm a hostile situation. Similarly conveying gratitude to a happy customer will exhilarate the customer’s mood. Sentiment analysis is a powerful tool to determine the tone of bot user. It not only understands the emotional content of the message but also acts as a useful marker for controlling the flow of a conversation.
Bot conversations can be nonlinear with users asking questions which are not predicted by bot developer. Thus a plan for failure should be built by the developer.
The bot design should have the following responses to avoid unsatisfactory user experience:
Sometimes a clearer explanation can get the bot back on track. If not, log the user’s goal and add new paths to the chatbot later to deal with this case. If you can reliably catch the tasks that a user failed to accomplish, you’ll have the data to make the most impactful updates next time you upgrade the bot. Besides automated analytics, explicit feedback from users taken through email or social media may offer insights for application updates.
Thus, chatbots promise a swifter and smarter online experience. Our new virtual assistants will be ever-ready, able to listen to our questions and respond intelligently. If you are willing to take the next technology leap, head over to our bot development page and give it a try.
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