Chatbots are set to dominate enterprise-customer communications. But what’s probably less flaunted but equally important fact is that chatbots are being leveraged to streamline several intra-enterprise processes as well.
Srijan is currently enabling clients from different industries deploy chatbots for strategic business use cases. Here’s a look at the multiple ways in which these bots are aiding enterprise operations:
Estée Lauder Company(ELC), with close to 30 brands, is revamping its enterprise learning system. Srijan is working to develop a digital learning ecosystem that would give the brand’s beauty advisors and over-the-counter sales teams anytime anywhere access to extensive learning resources. Part of this will be delivered via targeted micro-learning videos and training modules powered by xAPIs.
The other key part of the ecosystem with be simplified access to the ELC’s entire product information documentation, via chatbots.
ELC has an extensive database including information on different kinds of beauty products, their USP, and their suitability according to skin tone or type, ingredients, allergies and more. But memorizing this huge amount of information and answering accurately when dealing with a customer is almost impossible for the sales people. And having to search for this on a site or manual is not a great experience for the customer.
All the information is stored on a decoupled Drupal database, and the chatbot is designed to pull the necessary information from this repository to accurately answer questions. So the next time a customer enquires about whether a beauty cream is suitable for oily skin type, the salesperson could simply ask the chatbot, “What are the suitable skin types for using Product A?” and get the answer within seconds.
While this undoubtedly solves the challenges of a counter staff, it also has added benefits of enhancing the customer experience, who are now able to get their queries handled accurately and quickly.
As a leading provider of intelligent cleaning solutions - both chemicals and cleaning equipment - the company wanted to be able to analyze and optimize the performance of their products. They leverage IoT sensors to collect performance data from their equipments installed at various client sites. From the soap level in the dispensers, to equipment temperature, to resource consumption, the sensors tracked all sorts of data that could be viewed on interactive dashboards, and drive operational efficiency for their clients.
However, these dashboards had a few drawbacks:
And that is when chatbots came into the picture.
To get around these challenges, Srijan built a chatbot that could make the data collected on the dashboard easily accessible to client stakeholders
The chatbot worked on an “asked-and-answered” approach where the client simply had to ask a query and the bot would analyze all necessary data to give a clear answer.
For example, by simply asking the chatbot, “Which machine is underutilized in France?”, the client exec could get an idea of which equipment, in which region and which factory is not underutilized, and why.
Other similar questions around equipment performance, profits, resource usage etc can be answered by the bot in real time. Because the bot is easy to use and does not require people to look at and analyze a lot of data, it has seen increased adoption by the company’s clients.
Besides real-time reporting, Srijan teams also created chatbot PoCs for two other use cases for the company:
Enterprise operations such as ticketing, travel resourcing, customer care, customer onboarding etc. could all be streamlined to save the company’s time and resources.
For example:
Field teams out for equipment repair and servicing could use chatbots to quickly access necessary information like technical specification and manuals. Any challenges they face during repairs could be directly addressed to the chatbots, and correct answers received. Also, with the help of AWS DeepLens a field team member can directly communicate with an offsite expert when stuck, as well as run machine learning models to allow the chatbot to master the process.
Srijan worked with Python as a backend, PostgreSQL database, and AWS solutions like Lambda, S3, and Lex to build these chatbots.
Srijan recently built a PoC for a prospects in the aviation industry, building a branded Alexa skill to interact with their customers. The skill can be activated when customers make a named invocation similar to “Uber, book me a cab”. It is designed to address customer queries like status of a flight, flight details, and latest deals and offers being provided by the company.
Srijan is also currently beta-testing JIRA Assist, an Alexa skill built to interface with JIRA and keep you updated on the status of your JIRA board, without actually having to open the board. This serves as a simple project management tool where people can ask for the status of their JIRA board, track stories and deliverables, create tasks and sub-tasks and more.
Srijan teams are developing chatbots for diverse use cases across industries. As a Standard Consulting Partner in the Amazon Web Services Partner Network, Srijan has machine learning expertise and certified AWS professionals who can help you build Alexa skills specific to your business area, as well as high-performance conversational interfaces.
So if you are looking to build chatbots for specific business requirements, let’s get the discussion started on how Srijan can help.