For eye care professionals, effectively managing your optical can be a difficult and time-consuming task. You want to keep patients’ purchases in-house, you want to make sure your inventory is properly stocked and you want to ensure your revenue reflects the effort you put into maintaining this side of your business.
While this can be daunting for some practitioners, utilizing artificial intelligence to the best of its capabilities can change how you operate in your optical. AI is poised to change how eye-care practices manage retail, inventory and patient engagement by focusing on data-driven AI patterns. AI’s immediate optometric value is not in futuristic diagnostics, but in three practical areas: reducing friction in buying decisions, optimizing inventory and monetizing relationships beyond clinical care.
Making AI Work for Your Optical
The average practice derives about 60 to 70% percent of its revenue from optical and retail sales rather than clinical services. How can AI-driven frame recommendation systems increase retail revenue? AI analyzes where practices get the majority of revenue—optical and retail data—to make predictions based on patient interest.
The best opticians in the world treat frames as both medical devices and fashion statements when advising patients. Those who are not trained opticians may not know which frames will work best for certain prescriptions. For example, a very high myopic prescription may not sit well in oversized frames because the lenses can become excessively thick. AI helps address the gaps in practices that fail to capture sales in the optical.
AI narrows frame choices from the start based on observing facial geometry, such as jawline and face shape, to predict what will look best on each patient. This helps standardize the level of care on the retail side of business, and reduce the time patients spend choosing frames.
The Future of Retail is “Persona-lization”
The future of retail is personalization, which can be difficult because it requires detailed knowledge of patients’ interests. My solution is what I call “persona-lization.”
AI “persona-lization” is targeted marketing for different patient personas—groups that share traits like behavior, appearance, or occupation. This approach lets practices target each group specifically. Existing tools—like your EHR—can expand this persona-lization further by accessing and analyzing your practice data.
There is value in targeting patients who currently buy frames or contacts elsewhere. AI tools can recapture those who choose low-cost online alternatives because they feel that in-office processes are slow or cumbersome. These tools are not for every single patients; they are for patients that present opportunities for optical purchases that you’re currently not capturing. For patients who are not as tech-savvy, it may be easier to stay away from virtual try-ons—but there’s no reason not to personalize the way you market to them.
AI Low-Effort Wins and Long-Term Integration
Patients in certain geographic areas, such as Silicon Valley, tend to have higher digital expectations for their health care professionals. While AI can help some patients, not every tool suits every patient. For the best chances at success, I suggest starting with lower-effort AI tools, such as virtual try-ons and social media tools. Then, begin planning for longer-term projects—like those that connect patient records to personalized outreach. After patients leave the practice, you almost never get them to do anything transactionally with your business. The issue often lies in the staff’s availability for following up amidst their other duties. However, AI can change that.
AI gives you the opportunity to connect with patients by grouping them based on different demographics, interests or medical needs, segmenting your marketing to those specific groups, and then automating social posts that are directly targeted at each individual group. There are tools out there that can create and post all your social media content for months at a time. All you have to do is input the information and the system does all of the hard work for you—saving you time, and hopefully catching the eye of patients who need your services.
Where integration is harder, such as pulling data across systems to enable automated re-engagement, practices will need vendors focused on optometry workflows. This will enhance the flow between your business and AI.
Inventory Overhaul and Optimization
Inventory is a frequent blind spot for optometry practices and it presents a major cash-flow issue. While building electronic health records (EHRs) and practice management systems, I visited thousands of practices and found that many did not manage inventory effectively.
Having built the two most-used practice-management systems in optometry, I’ve seen firsthand how AI can optimize inventory. Export your practice report and run it through an AI analysis to reveal which demographics buy specific frames, glasses, contacts and lens types, and to evaluate the performance of every lens item in your catalog. Include your full lens inventory and AI can recommend whether to keep, reorder or discontinue each item—helping you reduce waste and improve turnover.
With this data, AI can align your inventory with your current demand by analyzing historical sales of frames, brands, price tiers, lens types and prescription ranges. The right AI tools can predict what people will buy based on patterns of transaction history or links to clinical outcomes, such as whether cataract patients regularly buy sunglasses. It also considers seasonality such as promoting sunglasses before summer or contact lenses in winter to avoid foggy glasses. This prediction reduces slow-moving items and frees up capital. AI shifts inventory decisions from subjective judgment to a data-driven decision-making process.
Integration Improves Efficiency
These are operational, not theoretical, steps to integrate AI into your practice. AI solutions are feasible, and everyone should demand that they have access to these systems. Practices should begin experimenting with the data they already have, while pushing vendors to build optometry-specific tools. Those who refuse to use AI forgo the opportunity to improve efficiency, patient access to care and staff operations.
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