The authors want to thank Luis Cabrera-Cordon, senior director of product management at OCI, and Chenai Jarimani, principal cloud architect at OCI, for their contributions.
Now Optics, LLC is a national eyeglass retailer in the United States spanning more than 20 states. The company has two main brands: Stanton Optical and MyEyelab. Of its 250+ stores, 75% of locations are corporate-owned and operated by 1,000+ employees, while the remaining 25% are franchised under the MyEyelab brand.
The company is at the cutting edge of technology in the optical industry. They’ve developed their own proprietary telemedicine equipment for remote control of optical machinery.
Now Optics’ goals
Now Optics is looking for ways to grow its business. The company had accumulated a large volume of data but had no tangible way to reap its benefits to optimize its business and expand to new offerings. To address this struggle, Now Optics invested in their own AI development. The company had the following critical goals aligned to this initiative:
- Now Optics has accumulated thousands of customer feedback forms and reviews for their hundreds of stores over the years and wanted to use that data to gain insights on improvements for their operations, stores, and products. This process is difficult without gaining insights into the big picture or macro trends, but because most of the data was unstructured, in the form of text-based reviews, it was difficult to consume and analyze.
- They also wanted to better understand the sentiment of their customers and quickly identify the keywords that signaled different sentiments and the entities (stores, personnel, and products) that garnered positive or negative feedback.
Enter OCI: Key services used
The company used the following Oracle Cloud Infrastructure (OCI) services, software development kits (SDKs), and frameworks:
- Oracle Artificial Intelligence (AI): Oracle AI is a family of artificial intelligence and machine learning services. Developers can add prebuilt models to applications and to operations’ logic. Data scientists can build, train, and deploy models using their chosen open source frameworks or choose to benefit from the speed of in-database machine learning.
- OCI Language: Part of the OCI Artificial Intelligence offering, OCI Language makes it possible to perform sophisticated text analysis at scale. With pretrained built-in models, developers don’t need machine learning expertise to build sentiment analysis, key phrase extraction, text classification, named entity recognition, and more language AI capabilities into their applications.
- OCI Data Integration: Easily extract, transform, and load (ETL) data for data science and analytics. OCI Data Integration enables you to design code-free data flows into data lakes and data marts. Part of Oracle’s comprehensive portfolio of integration solutions.
- OCI Object Storage: Enables customers to securely store any type of data in its native format. With built-in redundancy, OCI Object Storage can be used to consolidate multiple data sources for analytics, backup, or archive purposes and is ideal for building modern apps that require scale and flexibility.
- OCI Functions: Functions is a serverless platform that enables you to create, run, and scale business logic without managing any infrastructure.
Now Optics’ customer-centric solution on OCI
Now Optics was able to improve their customer engagement and experience by using state-of-the-art pretrained models in OCI Language to extract aspects and sentiments for customer reviews, as well as automatically extract entities (such as names of people, facilities, and products) from each of the records. This process structured the data, so employees can visualize trends and decide what changes to focus on. The company has already processed all its historical feedback and are planning to process more data monthly to stay up to date on customer feedback.
Technical Implementation on OCI
The total implementation time from proof of concept (POC) to production workloads was about three months, including the winter break.
The architecture pattern includes several steps for managing and interpreting data: Discover, ingest, transform, curate, analyze, learn, predict, measure, and act. The overall process flow includes the following steps:
- 1. Client data resides on SQL Server database.
- 2. OCI Data Integrator extracts data from SQL Server and loads into an Object Storage bucket.
- 3. OCI Functions calls OCI Language services and performs sentiment analysis.
- 4. The analysis from OCI Language is then stored in Object Storage.
- 5. The client then accesses the file and visualizes results using Tableau.
Thanks to OCI, Now Optics can identify the top issues that their customers feel strongly about to decide what actions to prioritize. With the sentiment analysis functionality in OCI Language, Now Optics converted unstructured textual content to structured content. Managers can analyze data, visualize it for actionable insights, and make changes to the business.
By using OCI’s AI and data integration capabilities, Now Optics can automate the processing of customer feedback, improve business efficiency, and increase customer satisfaction. Further, the company was able to achieve cost savings, which helps managers focus their efforts on other growth areas.
Next, Now Optics intends to use other OCI AI capabilities, such as OCI Vision, to flag eye diseases such as glaucoma, diabetes, and cancer by using only pictures of the retina and eye. The company also plans on adding some of the Lakehouse components, starting with Autonomous Data Warehouse for data management and Oracle Analytics Cloud for visualizations.
For more information on Now Optics and Oracle Cloud Infrastructure, see the following resources: