If you happen to be a growing company with a focus on latest technology – chatbots or simply bots should be something you definitely must have heard of. With Facebook’s introduction of bots on Messenger and the growing popularity of different bot platforms, there is a marked transition of bots from being just a buzzword to a full-fledged customer engagement tool. However, many businesses may ask – what’s the strategy for successful bot development and its best practices?
Elucidated below are some of the best practices for a successful bot development project –
Building a successful bot requires some deep understanding of the customer’s product or services and it’s user base. The 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 or lead generation bots. Talk with them about their bot use case 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 bot. Some of the practical objectives behind making a bot are an opportunity to drive new sales, customer engagement, streamline internal processes, etc.
Since the chatbot is a technology (IT) endeavor, it requires developers as well as testers, and it should be integrated into your larger information infrastructure with proper maintenance. With changing goals and increasing product lists, the chatbot will require regular updating.
As bot technology improves, businesses need to keep 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. A bot can listen to a customer’s needs and help filter through a long list of choices, perform more accurate search, and finally prompt the user for relevant information as required. Also, it can accumulate targeted feedback during a conversation.
Businesses can build bots from scratch or use comprehensive 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:
- Facebook bot engine (Wit.ai)
- API.ai (now known as DialogFlow)
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.
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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.
The 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 is bound to exhilarate the customer’s mood. Sentiment Analysis is a powerful tool to determine the tone of bot user where 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:
- Revisit a previous state
- Restart a conversation
- On failure politely ask the user what they are trying to accomplish
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.
Enterprise chatbot development is a whole other ball game which requires far more scoping and precision in terms of bot functionality and use case. All in all, chatbots promise a swifter, smarter and an intuitive online experience. Our new virtual assistants will be ever-ready, able to listen to our questions and respond intelligently.