Enhancing Customer Experience with AI-Powered Image Recognition and Sentiment Analysis
Business Problem
Level Up Llama Tech, a tech accessories company, faces challenges in managing customer feedback and product reviews efficiently. The company needs a solution to automatically analyze customer reviews, identify product images, and provide actionable insights to improve customer satisfaction and product quality.
Proposed Solution
Implement an AI-powered system that leverages Azure AI services to analyze customer reviews and identify product images. The system will use image recognition to classify product images and sentiment analysis to gauge customer satisfaction levels. By integrating these insights into the company’s customer relationship management (CRM) system, Level Up Llama Tech can quickly respond to customer needs and enhance product offerings.
Benefits
- Improved Customer Satisfaction: Quickly identifying and addressing customer issues enhances the overall customer experience.
- Efficient Review Management: Automating the review analysis process saves time and resources.
- Enhanced Product Quality: Insights from sentiment analysis can guide product improvements and innovations.
- Competitive Advantage: Leveraging AI technologies positions Level Up Llama Tech as a forward-thinking and customer-centric company.
Requirements
- Azure Services: Azure Cognitive Services (Computer Vision, Text Analytics)
- Description: Use Azure Cognitive Services to process a set of pre-collected customer reviews and images.
Process
- We are going to start things off by logging into your Azure account and creating a resource group
- Name the resource group, assign it to a region, and click create
- Next, we want to head over to computer vision and create a resource there
- Computer vision will be in the AI Services tab
- Click create and fill in the required details (resource group, resource name, pricing tier, etc)
- Next, go to the Network tab and confirm type is set to all networks, so your resource can be reached
- We can create the resource once you review and confirm
- Now we will create a text analytics resource
- Like before, we will fill in all required information and confirm the resource can be reached in the Network tab.
- Click create once you review and confirm everything.
- Now we have our Cognitive Services set up. We can now store datasets for the deployment.
Store a Dataset of Customer Images and Reviews
- Head over to the Storage Account and click create
- Fill in the required information and review before you create
- We will follow this by creating a Blob Container
- You will find the tab within the storage account you just created
- Here is where we will upload images and reviews
Analyze Images with Computer Vision and Reviews with Text Analytics
- Head to the resource created in Computer Vision and access Vision Studio within it
- We can find this icon and click try it out
- First, you link your subscription and resource group, and then you can test our images
- JSON format is also given for each image as you test them
- To analyze text, we will head back to the text analytics resource we created earlier
- Find Language Studio and click the link
- You will provide the required information to get started (resource group, subscriptions, etc)
- Find this icon under the Classify Text tab, here we will upload the customer reviews
- Once uploaded, click Run to see your findings
Here we have it! The analyzer was able to describe the reviews to better help understand business needs accurately. As you see in sentence 6, we can see an area that needs improvement to make the experience better, In sentence 31, We can take that there are also customers out there who do enjoy the aesthetics. This is great because you can always get a report of how your customers are feeling with their comments and reviews. We will continue to grow these skills to continue to support business needs.
