Is your business future-ready?

World is almost at an inflection point where bot era will takeover. Starshot enables businesses and organizations to build and deploy robust industry-specific chatbot applications. We architect and deploy chatbots for specific customer requirements to support leaders across all industries.

When you work with Starshot, you get to focus on delivering a good conversational UX to your customers without getting bogged down in development related complexities. We’re here to help you optimize the workflow, reduce the response time, and retain your prospects with intelligent, smart, and reliable chatbots.

How do chatbots work?

Bots are text-based programs empowered by artificial intelligence and natural learning processes. They are made to interact with users over a given platform, medium, network, or application. There are various types of chatbots and they can perform a number of tasks. Gartner predicts that by 2020, the average person will have more conversations with bots than their spouse.

Chatbots offer 24/7 availability, where a fully dedicated resource is providing you the desired service with unmatched control and transparency. Using the deep learning powers, you can train your chatbots to behave more like a human and deliver interactions in different languages of your choice. Their ability to deliver a cognitive digital experience and manage multiple interactions with natural interface makes them a very cost-effective option for customer support.

Conversational UX

Conversational UI and UX is the ideal way to engage users and keep them interested while delivering an experience which helps them to get the desired result without any hitches. These are the best practices that we follow when developing chatbots.

Providing a way back for users

Avoiding long paragraphs

Cross platform / device testing

Optimum user experience

Undo and Cancel as options

Striving for consistency

Safe professional humor

BOT IMPLEMENTATION STRATEGY

Our five-phase approach in building chatbots

Discovery

Service optimization
End-user gain analysis
Deciding the overall aim of the bot and decision makers

Definition

Scope definition
Conversation tree
Data sources to be used
Expected output
NLP (Natural Language Processing) – involves free text input

Bot Development

User engagement with conversation design
Binary options for conversation flow
Appropriate multiple choice questions

Launch

Launching to a closed group before it goes live
Ensuring launch on the right messaging apps
Training the botmaster to handle maintenance
Developing user retention and engagement strategies

Natural language processing retraining

Studying the user reaction
Bot usage analysis
Creating a NLP retraining program based on these inputs
Delivering a self-training NLP-driven bot