Release Notes April 2023
We’re excited to share with you all the exciting new features and improvements that have been implemented in this release. From the improvements in our mobile app to the AI/NLP capabilities, we’ve been working hard to ensure that this release delivers the best possible experience for our users. So, without further ado, let’s dive into all the exciting changes in the latest release!
In case you have any suggestions or queries, please feel free to reach out to us at email@example.com.
As a part of our monthly deployments, we had a release on 25th Apr 2023. Following is the summary of the changes:
Web-like Product search feature in Live chat is now available on the mobile app as well for agents to manually recommend/share products with users in order to provide better shopping assistance. This feature is applicable to all the Engati platform users integrated with Shopify & WooCommerce.
Web-like single and double ticks for sent/received/read notifications for each agent message will also reflect for the mobile app
It’s now a 2-click and streamlined process to add a new user and start the conversation, instead of the previously available 3-click workflow where there was also some confusion regarding country code selection
Mobile app artifacts are now in the Beta stage, where we can start accepting working partners and help them publish a white-labelled mobile app on iOS and Android app stores.
Images and files can now be attached by dragging and dropping them into the response box of an active conversation. More improvements will be planned on this in the near future.
Agents or portal users need not refresh to confirm the session being logged out due to inactivity. The web portal will now be automatically logged out and the customer redirected to the login page upon session timeout after 3 hrs of inactivity.
Users coming in through Facebook advertisements - Click to chat WhatsApp link will now be properly tagged and available on the portal. Agents will also be able to see the full context of the advertisement that the user clicked upon.
Customers will be able to download data from the Engati portal and use the same to run advertisements from the Facebook Ad manager on the same or similar custom audience segment.
Bot builders can now change the paths to send carousels and options as the one private reply automation when the user comments on a post, instead of a static message that was previously possible.
Customers can now through the Messages screen find out if the user from the conversation has commented in the past and the information on those comments.
Agents can also now send private replies to user comments on ‘Instagram Comments’ view and get more context on past conversations with the same user.
Using eSenseGPT, a GPT-based Generative AI engine built by Engati on Large Language Models (LLM), and the HTML web pages and PDF files uploaded on the platform, the bot will be able to respond to user queries related to the product, providing customers with detailed information about the return process and estimated timelines for refund processing, seamlessly. It will also retain the context of previously asked queries while responding similarly to ChatGPT. It uses natural language processing and machine learning algorithms to understand customers' questions and provide relevant responses. This reduces the workload on the customer service team, freeing up their time to focus on more complex queries and providing a better customer experience.