Untrite for Email Sentiment Analysis 🤟.
Learn how Untrite solutions can help you save up to 90% of your document search, creation, reviewing and analysis time using Machine Learning.
Untrite Email Sentiment solution (Untrite ES) identifies and categorises emotion expressed within the email, but can also be successfully implemented in other text-based formats such as news reports, emails, documents, reviews, etc. It can categorise the sentiment as positive or negative but it can also quantify the sentiment and categorise it at a more granular level (e.g. very negative, negative, neutral, positive, very positive).
Where is it applied?
Companies have many channels, including many email inboxes available to customers. By asking customers to find and select a correct inbox for their request they are putting the burden on them.
Obviously, customers don’t bother finding the correct email inbox to write their query to. They choose the first one they find. This results in emails and communications with clients sent to the wrong recipient/action person to deal with the query and cause a burden of the companies having to sort through the emails to resolve this problem. This process is laborious and time consuming.
We solve the problem by automating the process using AI technology. Our Untrite Email Sentiment solution (Untrite ES) engine ingests the data coming from various communication channels, understand them using Natural Language Processing (NLP) and categorise based on predefined business workflows. This business workflow could be customised based on client requirements i.e. automated responses either supervised or non supervised with the option of rerouting emails or forwarding them for further processing as required.
Additionally, we analyse the customer query in the email. We then look for an answer in selected company documents.
The system also has the capability to provide in depth analytics to aid the business in understanding trends highlighting key issues, risks or opportunities.
The average person is able to efficiently process 80-100 emails (varying in complexity) in an 8hr work day based on various tech industry literature. An average shared inbox requires an average 400USD/month for subscription to a cloud based software to enable the collaboration of internal staff to manage this shared inbox.
The process, however, is still manual and has much room for error, double handling and enormous number of task repetition.
Direct Cost Savings
For a shared inbox which receives an average of 500 emails/day it requires 4-6 FTE support staff dedicated to reviewing/sorting and responding/assigning tasks for further actions by “others”. The average annual cost of a support FTE is £40k/year. The semi-supervised approach enable the process to operate with max capacity using only one FTE for 500 emails/day.
The full use of Untrite ES offers potential direct savings for a medium customer service operation with one person only cutting down costs from £200k to as low as £40k.
The direct savings calculated do not account for downstream operational efficiencies gained, reduced backlog of emails, customer satisfaction and improved analytics and insights.
The economic benefits resulting from the application of Untrite ES are numerous and varied, subject to the nature of the application and the extent of waste embedded in the process for managing the communications.
Mapping the business process in question and understanding the process boundaries is key to studying the potential transformation achievable and opportunity how Untrite ES could make it even more efficient.
Other Use Cases
With emails alone representing the preferred method for communication by business for 86% of formal comms, emails ranked as the third most influential source of information for a company. These challenges presented in these data are primarily in their nature of being unstructured, though the contain an enormous amount of data, the value of which, which is often at risk of being overlooked with people moving on and the difficulty of finding meaningful knowledge out of them if navigating them blindly. For example; emails are a recognised form of formal communication and could be used in a court of law. In the event of arbitration or legal jurisdiction, companies have to pay expensive hourly rates to lawyers to surf through these in search for important information which could help with their case development. This could be very efficiently reduced into an algorithm which does the leg work for the expensive lawyers.
Insights and Analytics
Untrite Email Sentiment Analysis provides various bespoke tools for insights and analytics based on the clients process and requirements. This is key to understanding the business drivers so that to enforce the engine to highlight the relevant key patterns, trends and knowledge available from the unstructured pool of data and relate it to the business key performance indicators.
The closed loop of the engine promises an ever evolving improvement process, providing the required tools for companies in their journeys with their customers to best capitalise their learning and experience into actionable improvements.
Who is it for?
Companies that invest in outstanding customer support
How does it work?
By using Machine Learning and Natural Language Processing technology, Untrite processes documents in dozens of formats and automatically converts them to machine readable text. Depending on client needs, our solutions can be implemented on premises or in the cloud. They include includes workflow tools for your team to validate the results prior to them being exported into Excel, Word or PDF for final documents.
Untrite makes sense of your unstructured data and helps you derive valuable information from it
Untrite solutions have been used on various projects, helping organisations gain greater visibility into their contracts and their employees – focus on more meaningful, challenging and creative part of their work. Our users include many of the world’s leading professional service firms and corporations. We enable people to do meaningful, extraordinary work. We use data technology to solve those to help companies grow. To do more with less.
Find out how.