With Olvy AI Copilot, finding patterns in feedback relied on keyword extraction, feedback type, and other widgets, but these weren't enough to clearly identify patterns and lacked a broader picture.
Today, we have something massive to announce!
After successfully launching our brand new AI Copilot, we have introduced a new widget in it โ Themes โจ
Themes in Olvy AI Copilot
Themes offer a comprehensive understanding of the diverse topics users discuss in their feedback. It intelligently groups sim
Ever find yourself drowning in a sea of feedback, struggling to navigate through the chaos and organize it for different teams or categorizing feedback based on your product's segments?
Imagine a world where all your customer feedback magically falls into the perfect categories, tailored to your company's context. Well, stop imagining because with Olvy AI, that magic is now a reality!
๐ Introducing AI Autofills โจ โ a smart, flexible solution to create AI-powered Custom Properties for your
A couple of months back, we launched Generate Summary feature in our Olvy AI Copilot to help you summarize tons of user feedback in just one click so you don't have to go through each of them manually to make sense out of it.
As Olvy's summaries used to give you only the top 5 things your users request, you might miss out on a lot more things if you have thousands of feedback as the top 5 may not cover all the things you need to improve. So, to solve this problem and help you get more pre
Some questions require you to dig deeper into your user feedback - maybe you want to discover the sentiment about a feature in a particular timeframe. Getting to this data was difficult because of limitations in the types of filters we allowed you to add, we're changing that.
We're introducing the modern way of feedback filtration with Olvy's Conditional Filters โจ that bring endless flexibility in filtering feedback along with customizability, letting you effortlessly navigate through
As businesses scale to enterprise levels, they often find themselves flooded with a huge volume of user feedback, making it really difficult to manage all the feedback, let alone real-time analysis and comprehension. All these enterprise companies need a way to convert that unstructured, mammoth level of qualitative data into well-enriched, meaningful, structured data.
Keeping that in mind, we introduced Olvy AI Copilot a few months back to help you analyze high volumes of feedback in real-time a
Capturing the true essence of user concerns with every issue is hard and with an increase in the number of feedback, we often miss out on crucial details and product teams often miss out on what users actually said
With Olvy, we helped you to attach relevant feedback to the issue but writing the issue description still remains an unsolved problem, you still had to write them on your own.
From today you can skip getting into "writing mode" every time (feel free to also close the ChatGPT tab
Before Olvy most of users maintained an excel sheet for their product feedback, also some of their feedback was in different tools. For them, we've built a Feedback Importer that supports CSV, TSV, and Excel files. In just three simple steps, you can seamlessly import your existing feedback into Olvy and consolidate it all in one place.
Here are the steps on how to use the latest integration.
Uploading Feedback
Once your feedback is already neatly organized in a structured CSV, TSV, or Excel fi
Olvy automatically brought your feedback in, but categorizing each feedback as a feature request
, bug report
, idea
, or question
still required you to manually tag it as that.
Not anymore ๐คฏ
We are thrilled to announce the introduction of auto-tagging for feedback ๐. We have implemented an intelligent system that automatically identifies the type of feedback based on its content. So whether it's a feature request, product idea, bug report, question, or praise, Olvy will now assign the appropri
We are excited to announce a new and improved keywords analysis feature that will help you prioritize feedback more effectively.
Previously, the feedback analysis tool only showed a word cloud of keywords. However, with our latest update, you can now view a list of keywords along with their corresponding sentiment scores, which indicate the percentage of negative, positive, or neutral feedback associated with each keyword.
We've also introduced keywords grouping, which groups together similar
Before we make a release live for everyone, we first share it with our team and beta users for feedback. Previously we did that by sending direct messages to everyone on Slack.
But why do it twice?
Introducing user segmentation in Olvy.
What is user segmentation?
User segmentation is the process of dividing a user base into distinct groups based on common characteristics. This technique helps businesses and product teams better understand their users, tailor their messaging and experiences to differ