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A photo taking assistant to qualify and onboard leads for appointment booking. The assistant is capable of detecting, assessing and prompting resubmissions through visual cues.
MY ROLE
As Product Manager for the assistant, I worked with our multidisciplinary team to take the assistant from conception to launch of MVP, pilot testing, reiteration and phased extension.
I gathered insights from user interviews, oversaw AI training, and worked closely with the CEO, product designer and AI engineers.
PRODUCT
The demo video shows photo submissions with the AI-powered assistant. It handles the entire digital guest experience without extra input from Pre-Assessment Doctors.
The assistant knows who the customer is, where the User last left off, and if the submitted photos are eligible for Pre-Assessment. During the photo taking process, visual cues offer an intuitive experience on proximity to the subject, and guides the user to make high quality, secure submissions.
If a user is eligible for Zenyum, there's no additional logins, it instantly shows available slots to schedule a call for onboarding and consultation with the Dentist. The customer can propose general available location and time slots for ease of consultation booking.
EVOLUTION STORY
The concept behind OBT (Onboarding Tool) optimizes for lead generation and qualification.
OBT was originally a test bed for the product team to gain insights into the customer experience in pre-assessing the User's teeth concerns, and with minimal cost and resources. We validated the demand for various teeth complexities and validated photo taking as a means of interaction, instead of consulting for eligibility at a clinic. The OBT proved to be a big success giving us full detail into the pain points for channelling consumers-to-dentist.
After the success of the test bed, the product team outlined a photo submission process that did not check for quality of submission, and it's efficiency was limited to back-and-forth communication from Pre-Assessment Doctors back to Users. The wait times and extra effort was unenjoyable and created a poor experience; the initial feedback mirrored this issue. We also designed a hybrid onboarding solution, that used a mix of conversational UI and traditional communication means (email, phone call). Interviews about the conversational UI went well, but there was a lack of visibility in photo collection through various channels, especially in a business shared across 8 markets with varying messaging tools.
Utilizing the conversational concept and focusing features back on the onboarding tool itself, we were able to minimize risk and start on the first version of an intelligent agent that used photo and text input to ensure high quality submissions of photos, specific to all required angles – the assistant was born. We quickly evolved from being able to detect images where teeth is present to detecting correct teeth angles, built AI training & user onboarding tools, and added features like displaying incorrect photo angles and visual guides to the user. We also built a proof of concept feature via our App that allowed us to scope the use of voice as feedback and positive feedback to the user for faster photo taking. This smart assistant concept allowed for better prioritization of the roadmap for future goals.
It took us less than 6 months to take the first version of the AI to being an extension to allow eligibility results to be passed in seconds as soon as the user has submitted the final photo. The following months were used to build out the machine learning database, reduce false deferred cases and optimize to save costs in Pre-Assessment resources. The product is considered successful based on the pilot testing we have done and be rolling out market by market to automate 20% of total traffic to Clinics without extra input from Pre-Assessment Doctors.
METRICS
85% of actions performed through OBT over Facebook, WhatsApp, LINE submissions.
62% average Lead to Qualified Opportunity Conversion through OBTAI, improving low quality submissions from 30% to 2% in 3 months.
Processes over 10K data points from Zenyum, past conversations, and users.
Implemented the assistant as an omni-channel solution across 8 markets.
KEY TAKEAWAYS
As one of the most recent products I've worked on, I've validated that I can work with new technologies (e.g. AI, ML, NLP) without being able to write any level of production-ready code.
How to use techniques from other disciplines to strengthen my process. This comes from the realization that designing a Conversational UI is fundamentally the same as traditional interface design.
How to increase communication through all team members by optimizing the tools that are already in use via scrum methodology, Jira, and Slack.
How to approach a multi-sided platform and make sure you're solving for the correct side, aka "When the user feels X, the business feels Y".
How important it is to "get out of the office" and interact with all possible user types regularly.
What it means to be in a venture-backed startup, how it impacts decisions, and how to manage budgeting & burn rate while running lean.
How to network to strengthen connections with CEOs and veterans of the AI industry for mentorship.
"Edna displays great confidence and determination. She takes pride in her work and has great personality. It has been my pleasure working with her on our project and various assignments. Edna ensures that the work produced is of great quality and accepts different viewpoints given during meetings. Her willingness to learn and teach has motivated the team to strive for the best. She has been an awesome team player throughout the process and her great positive attitude has driven our team to overcome challenges along the way! I believe she will be able to value-add to any organization in future."
— Adora Tay, Community Executive @ IWG PLC
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