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Bots act like personal shopping assistants engaging users by suggesting products to purchase and notifying them on real-time offers and delivery status of purchased items.
Chatbots take away many mundane tasks from the shoulders of recruiters. Bots can analyze information from different sources and help shortlist candidates based on input criteria.
Through quick and simple conversations, bots provide real-time investment advice and help carry out banking tasks such as payments and checking transactions.
A virtual hospitality assistant available round the clock helps users plan a stay, book rooms, and avail amenities through chatting, providing greater customer satisfaction.
Travel bots provide personalized services from booking tickets to timely notification of time-sensitive logistics alerts through quickly accessible messaging interfaces.
Car dealer bots help car shoppers find their perfect vehicle. The bots ensure 24/7 sales assistance, so the dealership never misses a lead or keeps a customer waiting.
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Chatbots can be integrated with ERPs to carry out routine tasks more efficiently, saving on the cost of resources.
The three main instances where chatbots come to operation are for self-service applications, round-the-clock automated interaction, integration with enterprise applications for different teams to function efficiently.
An eCommerce chatbot helps a customer identify and shop for a product by engaging in question-answer interaction influenced by the customer’s browsing pattern.
A person who wishes to travel can visit an airline website and interact with its chatbot to find the right flight and book tickets. The bot answers to related queries and provide personalized recommendations and offers on hotels, tourist attractions if programed to do so.
An employee in a business firm can inquire details such as company policies, vacation and holiday details, medical insurance and travel allowance details to a virtual office assistant chatbot integrated with other applications in the enterprise.
Having a character makes bots more appealing to people. Chatbots can be trained to express their personality through language. Bot UX designers feed in responses that project empathy, anticipating all possible directions of a conversation. They are also built with the capability to learn from the conversations they make.
Based on the application, bots can be made to sound somber or to express moods. For instance, an investment advisor bot may be more ‘serious’ than an eCommerce bot. A personal assistant chatbot may give emotional responses when told something ‘hurtful’.
Bots analyze idioms, phrases, and language usage patterns from conversations to respond. Responding in this fashion instead of providing search results for inquiries, makes the conversation appear more personal than machine-like.
Bots recognize entities by extracting and categorizing data such as name, place, organization and events from an inquiry and store it. The categorized data when mapped to known entity types helps it to understand the context and provide relevant responses.
Bots are built with algorithms that automate learning by identifying patterns in input data. With more conversations, the bot automatically improves and performs predictive analytics to prepare itself with relevant responses. In other words, machine learning is what makes a bot think and respond.
Positive, negative or neutral, the bots are programmed to understand the tone of the conversation by recognizing the sentiment associated with words. For example, when a bot identifies ‘anger’ in a customer, it can be programmed to speed up request resolutions rather than engage in further pleasantries.
We build AI-powered, self-learning chatbots that respond to queries or complaints, follow-up or take feedback, and perform defined tasks so that you can create higher-value interactions with your customers. Take the burden off your resource-intensive functions such as sales, help desk, admin, or even human resources. We will help you identify the use cases and develop suitable chatbots.
First, we work with you to identify your use cases, end goals, and target audience. With this information, we can design various conversational flows based on the type of user interaction.
To build bots that can hold contextual chat conversations, we need to infuse it with machine learning and natural language programing (NLP) capabilities. Cloud-based cognitive computing platforms such as IBM Watson are used to power the AI capabilities. We train the pre-built NLP model using training data, defining custom intents and entities. The model is tested with new data and depending on the results, we retrain the model. As we configure and customize the model, we also implement a workflow for human takeover in complex scenarios that a bot cannot handle.
While some self-service chatbot development tools allow business users to create chatbots, machine learning and AI integration often require deeper technical knowledge. We help our clients deploy chatbots by working on the complex AI integrations.
Wit.ai helps to build voice-enabled interfaces like Siri that convert natural language to actionable data.
Chatfuel enables intuitive chatbots for Messenger and Telegram that links external resources with the user.
Botsify framework requires minimal coding knowledge to build a completely customizable chatbot for FB Messenger.
With API.ai, it is possible to build voice and text-based chatbots that can be integrated with any messaging platform.
Aspect’s customer experience platform and natural language understanding together enables chatbots for customer service applications.
Imagine increasing customer engagement with your own version of Siri! We can build it for you.