Our client is a Shopify store that sells premium coffee beans and accessories. They have a loyal customer base, but they wanted to expand their reach and grow their sales.‍

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They also wanted to provide a more interactive and personalized shopping experience for their customers, especially those who are new to coffee or have specific preferences.

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They contacted us to create a custom Copilot for their Shopify store, using our Managed Code service. Managed Code is a service that allows you to create your own conversational AI assistant, without any coding or technical skills.

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You simply tell us what you want your Copilot to do, and we handle the rest. We use state-of-the-art natural language processing and machine learning to create a Copilot that can understand and respond to your customers' queries, and integrate it with your Shopify store.

Our client faced several challenges in their Shopify store, such as:

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1. How to provide quick and accurate answers to common customer questions, such as stock availability, color options, delivery times, etc.
2. How to provide personalized product recommendations based on customer preferences, such as roast level, flavor profile, origin, etc.
3. How to use visual search to allow customers to upload photos of their favorite coffee products and find similar items in the store.
4. How to increase customer engagement and retention by creating a friendly and helpful tone of voice for the Copilot.

Solution Development

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We used our Managed Code service to create a custom Copilot for our client's Shopify store.

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The development process involved the following steps:

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1. We analysed the client's store and their target audience and defined the goals and scope of the Copilot.
2. We designed the Copilot's personality and tone of voice, based on the client's brand identity and customer expectations.
3. We created a list of possible customer queries and intents and mapped them to the appropriate responses and actions.
4. We trained the Copilot using natural language processing and machine learning, to enable it to understand and respond to customer queries, and to learn from feedback and data.
5. We integrated the Copilot with the client's Shopify store, using Shopify's API and webhooks, to allow it to access and update the store's inventory and product information.
6. We added a visual search feature, using computer vision and image recognition, to allow the Copilot to identify and recommend products based on customer photos.
7. We tested and refined the Copilot, using real customer data and feedback, to ensure its accuracy and performance.

The result was a custom Copilot that could handle a variety of customer queries, such as:

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1. "Do you have any dark roast coffee beans in stock?"
2. "What are the best coffee accessories for a French press?"
3. "I like chocolate and caramel flavors, what coffee do you recommend?"
4. "Can you show me some coffee products that look like this?" (customer uploads a photo)

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Our Shopify Copilot could also provide personalized product recommendations, based on the customer's preferences, purchase history, and browsing behavior. For example, the Copilot could say:

Implementation

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The Copilot was integrated into the client's Shopify store, using a widget that appeared on the bottom right corner of the website. The widget allowed customers to initiate a conversation with the Copilot, by typing or speaking their queries, or by uploading a photo. The Copilot would then respond with text, voice, or images, depending on the query and the customer's preference.

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The implementation process involved the following steps:

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1. We design and develop the Custom Copilot widget for the client's Shopify store.
2. We did prompt engineering for our Copilot's, such as the language, the voice, the color, and the logo.
3. We trained the Copilot using the client's store data, such as the product catalog, the inventory, the prices, the reviews, etc.
4. We monitored and optimized the Copilot's performance, using analytics and feedback tools.

The implementation process was smooth and fast and did not require any technical skills or changes to the client's store. The Copilot was ready to use in less than a week.