Generative AI tools like chatbots and virtual assistants have the potential to dramatically enhance the customer journey at retail businesses and drive increased sales. They can provide personalized shopping experiences to returning customers, engage with new customers across all channels at all times, and deliver 24/7 customer support.
However, implementing AI chatbots can be a significant challenge. A recent survey of major retailers found that only 4% have successfully scaled generative AI tools across their businesses.
That’s why we’ve compiled this guide. Below, we explain how retailers can rapidly deploy AI chatbots and virtual assistants with low code and begin harnessing the power of generative AI.
AI chatbots and virtual assistants can boost customer engagement, increase sales, and reduce customer service costs.
Traditional development approaches make deploying an AI chatbot costly and time-consuming. They struggle to address challenges like data silos or privacy requirements and require professional developers.
Low code cuts AI chatbot deployment time by reducing the need for professional developers and offering tools to sidestep data challenges. Low code is also more flexible and scalable than traditional development.
AI chatbots and virtual assistants hold massive promise for the retail industry. These tools can transform the customer experience while enhancing operational efficiency and reducing costs.
One key way AI chatbots can achieve this is by engaging directly with customers. If a customer clicks on a product in your online store, for example, a chatbot can answer questions about it or suggest similar items the customer might like. This direct engagement can increase conversions and boost your business’s revenue.
Generative AI-powered virtual assistants can also build loyalty among existing customers. For example, they can analyze a customer’s preferences to suggest new products or help them choose the right size in a new outfit. This personalized attention is similar to what a customer would get from a personal shopper, and it can lead to a major increase in repeat sales.
The benefits of AI chatbots and virtual assistants extend beyond enhancing customer experiences and boosting sales. They also reduce costs by automating many aspects of customer service. Customers can speak with a chatbot to ask about the status of an online order or initiate a return, freeing human agents to focus on more complex issues. This reduces retailers’ overall staffing needs, increasing operational efficiency and saving money.
Despite AI chatbots' promise, few retailers currently use them expansively. That’s because traditional approaches to chatbot development are costly, time-consuming, and challenging to scale.
These approaches rely on professional developers to build chatbots from scratch, integrating natural language processing models with workflows for collecting and analyzing customer data. This is a slow process that often requires bringing in data scientists to find the best way to harness your business’s data.
To make matters worse, developers can run into numerous challenges along the way. Data silos, data privacy issues, and outdated IT systems that don’t easily support data sharing can all slow down development and increase costs. The result is that what might seem like a simple project at the outset can significantly drain your company’s IT resources.
The good news is that there’s a way around these challenges: low code development.
Low code approaches eliminate much of the coding traditionally required for chatbot development and deployment. Instead of code, low code platforms use customizable templates, drag-and-drop interfaces, and pre-made content elements to help you build AI-powered tools.
Low code accelerates AI chatbot deployment in a few key ways.
First, low code platforms minimize the code needed to build a chatbot. Many come with pre-built integrations for popular AI models, so all you need to do is provide the data and design the user interface.
This means you can lean on your existing IT team to spearhead development rather than hire a team of developers working around the clock. So, it’s possible to get started on your project right away instead of waiting until a new team is in place. The overall cost of building an AI chatbot or virtual assistant is also dramatically lower with fewer developers involved.
Another benefit to low code development is that it sidesteps many issues that pop up during traditional development approaches. For example, low code tools make it easy to build custom data pipelines and automated databases that break down data silos instantly. They also provide granular data security controls, ensuring sensitive customer information can be handled safely. With fewer problems to navigate, development can proceed much more quickly.
Additionally, low code approaches enable flexibility and scalability in a way that often isn’t the case with traditional development methods. With low code, you can develop a basic chatbot for one customer-facing channel—like your online store—and then expand it to more channels and add more capabilities later.
This stepwise approach also increases the likelihood of project success. You can deploy a prototype chatbot quickly and immediately see results in your conversion rate or customer satisfaction ratings. Then, based on customer feedback, you can iteratively improve your chatbot.
Building an AI chatbot with low code starts with choosing a low code platform.
CLEVR works exclusively with Mendix low code because of its advanced features for AI integration and data security. Mendix is also highly flexible, making it ideal for various retail businesses and chatbot deployments.
Using your chosen low code platform, you can integrate your business’s data flows with a generative AI model. Then, you can build a new data pipeline for your chatbot or continuously stream data from your existing databases to the AI model.
Finally, deploy your chatbot on your online store, mobile app, and customer service platform. Mendix offers tools to streamline these integrations and ensure customer interaction data is fed back into your business for in-depth analysis.
CLEVR can serve as an expert partner for your business throughout this implementation process—providing end-to-end support, including identifying opportunities for generative AI within the customer journey and assisting in building a capable chatbot or virtual assistant with Mendix. Additionally, CLEVR ensures the AI tools remain flexible and scalable, enabling continuous improvement of the customer experience.
This guide is based on a survey of retail executives and the latest insights from retail industry publications. It also draws on input from IT leaders, retail operations managers, and customer experience experts currently using low code and generative AI tools.
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