AI Summary
“Just in one day we can have one or hundreds of conversations and yes, I need to review each of them” for a conversational tool, the increase of chats it’s a good new, but not for everyone like the Sales Rep. and Admins that must review each chat to understand what are happening in the conversations and if the bot it’s answering the way it supposed to be, and the answer was in front of our eyes: AI
Company:
DRIFT
Role:
Product Designer, UX Researcher
Date:
Feb 2024
Tools:
Figma, GreatQuestion, Miro
Why does a new feature had such a negative feedback?
On the second half of 2023, Analytics team decided to migrate from a untenable but interactive section to review the conversations, to a sustainable but simple data table. This change immediately receive a negative impact from the users and the amount of complains and tickets in Customer Suppot increase critically.
We might empathize with our customers, understand their workday and how did they use and expected from our platform. After multiple rounds of discovery calls and reading all the feedback collected, we figure out their main pain points and other interaction problems that we might be facing by updating this section.
I N T E R A C T I O N
The usability of the page requires a lot of clicks to review the chats.
A R C H I T E C T U R E
Not enough or easily to find information of what is happening during conversations.
A R C H I T E C T U R E
Drill-down to other reports like Playbooks and Opportunities
U S A B I L I T Y
The usability of the page was the most critical pain point to solve and the one that requires more effort from the engineering team, since some microinteractions were not contemplated (at least at this point) in the DDS.
A possible solution for this might not be only moving a button, since the problem of closing the drawer and click on the next still there. Changing to clickable rows was not allowed by our system.
K E Y · I N F O R M A T I O N
Following the new flow that we set up in the ROI project, Chats data are now more important than ever.
The goal is to connect them to the activity timeline, so our users will be not only able to understand if an opportunity it’s “influenced” or “sourced”, they can also dig into the actual conversation and see what happens there and why we’re claiming it.
K P I · C A R D S
I decided to highlight 3 key data related to the chats: First the sentiment, a new feature that also uses AI to detect if the conversation went with a positive mood, negative or neutral.
S N E A K · P E A K
We used to show up the first part of the conversation in C.A., but I changed to the last part, so our Sales Rep. can understand why the conversation ended.
R A T E · T H E · B O T
To introduce a way to give us an evaluation of the Chatbot performance, we’re also using the “sneak peak” space to it.