The Big Picture

The global dental industry is undergoing a technology driven transformation where players looking to empower their users by leveraging best-in-class technology and artificial intelligence. By investing strategically in their products and through tech interception along their business value chain, dental providers are going digital-first, with the aim to add value to their users and to redefine the dental healthcare experience.

The customer’s mission is to help users achieve a happy, confident and radiant smile that is affordable. By harnessing the power of 3D printing and thermoforming technology, their teeth aligners are the solution to straighten teeth and a healthier bite.

Founder & CEO

Asia-based Digital Dental Platform

Dentistry is a little bit of an old industry. But by putting a layer of technology on top of that, you can predict very much what are the patterns that are happening

The Blox.ai Impact

The Blox.ai team worked closely with with the customer to understand which mission critical challenges they were looking to solve, and thus aligned on key goals to be achieved. Read on to understand about the Blox.ai intervention for this customer and how our A.I. was able to add value across their business.

97
%

Accuracy In User Qualification

90
%

Reduction In Finer Resubmission Rate

50
%

Reduction In Overall Resubmission Rate

75
%

Reduction In User Bounce Rate

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A new user would need to log in to the customer’s site or app to take a photo of their teeth, in order to get started. Users had to wait up to 24 hours to get feedback from dentists on:

  • Whether they had taken the photo correctly
  • Whether they were eligible for treatment
2

The long waiting time resulted in a high drop off rate within the session and multiple lost opportunities due to the waiting time, just to get images validated.

Key Goals

With the challenge to deliver faster user onboarding and to reduce user bounce rate at that stage, the key goals identified for the Blox.ai intervention were:

Reduction of user bounce rate during the image upload and qualification process, in the user onboarding workflow

Reduction of the existing user onboarding resubmission rate i.e. based on the image qualification and approval, how often do users need to re-submit images for pre-assessment

The Blox.ai Intervention

Integrating Blox.ai’s AI-powered image recognition capabilities into the customer’s onboarding workflow.

This would enable:

Use Cases

Instant feedback for the user on whether the image uploaded was accepted or rejected, based on predetermined guidelines built into the image qualification

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Faster movement of the user to the pre-assessment phase, based on evaluation from the image, to determine whether they are eligible for treatment

Use Cases

Reduce bounce rate at the user onboarding stage, and increase engagement via the intuitive machine feedback as well as pre-assessment

Use Cases

Enable dentists to assess, diagnose and treat eligible users, thus leveraging their time better

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AI-Powered image moderation, integrated into the existing onboarding workflow, enables the user to onboard and move to the pre-assessment stage faster.

One thing we kept investing in at all points in time was the product team. It was so strategic for us to keep building and expanding the solution of the product. The first thing is an Automated smile Assessment and that's something that Blox.ai helps us a lot with And it really gave us an advantage in the end. We're seeing some super exciting stuff.

Founder & CEO, Asia-based Digital Dental Platform

AI-Powered Workflow Automation

The AI-powered workflow ensures higher user engagement, lesser bounce from the onboarding process and faster conversion from onboarding to pre-assessment, and further to diagnosis and treatment

Use Cases

User

UserUser uploads images to the platform
Use Cases

Instantaneous

InstantaneousThe A.I. qualifies the image and request retakes
Use Cases

Blox.ai

Key Outcomes

By intercepting the user onboarding workflow, Blox.ai was able to significantly increase user engagement. The accuracy in user qualification enabled them to move to pre-assessment faster, and the instant feedback ensured a reduction in user churn.

97% accuracy in detecting user qualification based on A.I. assessment of images uploaded

90% accuracy where the A.I. rejected the image, however user was allowed to submit to better the overall user experience

50% reduction in overall resubmission of images by the user

75% reduction in users leaving the onboarding workflow without completing the process

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