Reinventing E-commerce: Low-Code and AI Solutions for Retailers

Explore how low-code platforms and AI tools are revolutionizing retail by enhancing efficiency, cutting costs, and improving customer experiences.

Mar 25, 2025

Retailers are transforming their operations with low-code platforms and AI tools to meet customer demands faster and more efficiently. These technologies simplify app development, automate key tasks, and improve customer experiences. Here’s what you need to know:

Low-Code Platforms: Build apps up to 10x faster using visual interfaces and pre-built components - no advanced coding needed.
AI Tools: Automate personalization, inventory management, and customer service, driving sales and reducing operational costs.
Key Benefits:
- Cut development time by 75%.
- Enable non-IT staff to create solutions.
- Boost repeat purchases by 44% with AI-driven recommendations.
- Improve inventory accuracy and reduce stockouts.

Quick Example: A $60 billion retailer built a curbside pickup system in 11 days using low-code, compared to a year with traditional methods.

Why It Matters: AI and low-code are helping retailers adapt quickly, save costs, and deliver better customer experiences. Ready to get started? Evaluate your store’s needs, choose the right tools, and begin with small, impactful projects.

Full E-Commerce Solutions built with Low-Code 🛒

How Low-Code Speeds Up Retail Development

Low-code platforms are transforming how retailers approach digital development. Research by Iterate.ai reveals that these platforms can accelerate mobile app development by up to 10 times compared to traditional methods. This speed is a game-changer for meeting market demands efficiently.

Key Benefits for Retailers

Low-code platforms don't just save time - they offer a range of practical advantages for retailers:

Benefit	Impact
Development Speed	Cuts development time by 75% (200 days vs. 800 days using Java)
Cost Efficiency	Reduces dependency on highly specialized developers
Team Involvement	Enables non-IT staff to participate in the development process
Quick Prototyping	Speeds up testing and launching of new features
Scalability	Simplifies deployment across multiple stores or regions

Building Custom Store Solutions

Retailers are leveraging low-code platforms to create tailored solutions for their unique needs. For instance, Lidl Portugal developed an Order Control application that revolutionized their inventory management. Gonçalo Henriques, IT Consultant at Lidl Portugal, highlighted the dual benefits of cost savings and operational improvements:

"Apart from the financial savings, which are significant, we have also seen improvement in our inventory. As a result, we saw that this recovered trust between the stores and warehouses, which is a huge benefit for overall business operations."

Using intuitive visual interfaces and reusable components, retailers can easily build tools like:

Mobile apps for customers
Inventory tracking systems
Supply chain management solutions
Employee scheduling tools
Product recall management systems

Real-World Retail Successes

Several retailers have already demonstrated how low-code can enhance their operations:

Schwarz Group's Digital Transformation (2021–Present): The company developed over 120 applications using low-code, including PRIA - a product recall app completed in just 4 months. Their EDI application now handles communication with more than 15,000 vendors.
Lidl Switzerland's Store Operations (2023): They introduced a Cleaning App that digitized store maintenance, reducing email usage and boosting efficiency for store employees.

Zdenek Prochazka, Head of Rapid Application Development at Schwarz IT, shared his thoughts on the platform's impact:

"Because we can get new applications live so quickly with Mendix, we can see the real-life benefits and more quickly figure out how to industrialize a solution or roll it out on an international level."

AI Tools That Improve Shopping

AI is reshaping online shopping, boosting sales and improving customer engagement. During the 2023 holiday season, AI influenced $199 billion in sales, highlighting its growing role in retail success.

Smart Product Suggestions

Recommendation systems powered by AI use customer data - like browsing habits, purchase history, and preferences - to create tailored shopping experiences. Here’s what they can achieve:

Metric	Result
Repeat Purchases	44% increase globally
Conversion Rates	15–30% improvement

Take UnderX, a medical supply retailer, for example. Their recommendation engine analyzes customer feedback to suggest products based on factors like absorbency and size. The result? A 35% rise in repeat purchases and a 25% drop in product returns. On top of product suggestions, AI is also revolutionizing customer service.

AI Customer Service Helpers

AI chatbots and virtual assistants now provide 24/7 support that rivals in-store service. Handling up to 85% of online interactions, these tools assist with product queries, order tracking, and personalized recommendations.

They New York, a footwear brand, offers a great example. Their AI sales assistant, "Rep", boosted conversion rates by 3.2X. Yoav Oz, Co-founder and CEO of Rep, explains:

"Through conversational voice AI chatbots and virtual assistants, customers receive a level of service and support that match interactions with associates at brick-and-mortar stores. These autonomous interactions create relationships that are built on self-learning scenarios that become personalized and provide better CX, in turn keeping consumers on your site."

This implementation also delivered a 14X return on investment, with over half of transactions involving the AI assistant. Beyond chatbots, visual search is another game-changer in online shopping.

Shopping with Pictures

Visual search allows customers to upload images instead of typing descriptions, making product discovery faster and more intuitive. This feature is especially popular with younger shoppers - 62% of millennials prefer it over text-based search. Its impact includes:

A projected 30% increase in online retail revenue by 2025
Up to 4X higher conversion rates compared to keyword searches
2X higher average order values

Amazon’s StyleSnap is a standout example. Introduced in 2019, this tool uses deep learning to analyze uploaded images, helping customers find fashion and home furnishings by identifying elements like color, pattern, and style.

Chris Baldwin, VP Marketing, Brand and Communications at Insider, sums it up well:

"AI-driven personalized shopping experiences improve customer retention and drive, on average, 44% of repeat purchases worldwide."

Making Stores Run Better with AI and Low-Code

AI and low-code are reshaping how retail operations work by improving inventory management, simplifying pricing strategies, and reducing costs. Let’s dive into how AI-powered systems make inventory management smarter.

Stock Planning and Control

AI-powered inventory systems use historical sales data, market trends, and seasonal patterns to help retailers make better stocking decisions. This is critical, especially since 78% of U.S. shoppers have faced out-of-stock issues while shopping in stores.

Here’s how AI-driven inventory management helps:

Advantage	Outcome
Better Accuracy	Automated tracking reduces errors
Lower Costs	Optimized stock levels cut expenses
Greater Efficiency	Automation lets staff focus on strategy
Higher Customer Satisfaction	Fewer stockouts mean faster fulfillment

Order Processing Systems

AI and low-code make order processing faster and more reliable. Predictive order models can increase conversion rates by 5–20% and lower service costs by 3–15%. With 73% of online shoppers reporting out-of-stock issues, AI systems step in by turning data into actionable insights, automating inventory checks, and ensuring real-time stock visibility.

Smart Price Adjustments

Dynamic pricing powered by AI helps retailers stay competitive while improving profits. For example, Amazon makes 2.5 million pricing decisions daily, boosting profits by 25%. These systems analyze competitor prices, adjust rates based on demand, clear out excess inventory, and even tailor pricing for local markets.

A great example is Airbnb’s AI pricing tool. It adjusts rental rates based on local events, seasons, and competitor pricing, which helps improve both occupancy rates and revenue.

Steps to Add Low-Code and AI to Your Store

Check If Your Store Is Ready

Start by evaluating your store's current data, systems, and team capabilities. According to research, 85% of engineering leaders believe low-code will soon be a standard approach in their organizations.

Readiness Factor	Requirements
Data Quality	Organized and clean customer and inventory data
Technical Infrastructure	Cloud-enabled systems and accessible APIs
Team Skills	Basic technical knowledge and eagerness to learn
Business Goals	Clear objectives and metrics for success

Once you've confirmed readiness, choose tools that align with your retail needs.

Pick the Right Tools

Choosing the right tools is a key step. Look for platforms that provide:

Retail-Specific Features: Choose platforms designed with retail functions in mind. For example, Pampered Chef quickly developed solutions tailored to its business model:
"We were able to rapidly build, pilot and iterate on a digital solution that is enabling virtual parties that match our unique business model"
– Shiv Dutt, VP of Digital Experience and Innovation at Pampered Chef
AI Integration Capabilities: Opt for platforms that include built-in AI features. As Hans de Visser, Mendix's chief product officer, explains:
"We believe AI tools and low-code development are a natural fit to build better software faster... Enterprises using low-code will be able to extract more value from AI in an efficient way using the new features of the Mendix 10 platform"

With these tools in place, you'll be ready to integrate them effectively.

Tips for Success

Start small with a pilot project, then expand based on results. Here are some strategies to guide your implementation:

Strategy	Benefits
Start with Pilot Projects	Test solutions with minimal risk
Focus on Customer Value	Prioritize features that enhance the shopping experience
Measure Results	Track key metrics like development time and customer satisfaction
Continuously Refine	Use performance data to make ongoing improvements

Regularly evaluate your progress by monitoring:

Efficiency improvements in processes
Time saved during development
Enhancements in customer experience
Return on investment

As Amir Piltan, Mendix's senior product manager for AI, notes:

"Enterprises with sophisticated machine learning capabilities can easily incorporate their models into Mendix applications using the ML Kit... This makes AI deployment easier from an operational, commercial, and governance standpoint."

Conclusion

Key Takeaways

Low-code platforms and AI are reshaping the retail landscape. Industry data highlights these technologies as the future of application development. They offer clear benefits:

Advantage	Impact
Faster Development	Mobile app development up to 10x faster
Market Expansion	Low-code market projected to hit $21B by 2022
Revenue Growth	Example: PLUS aims for €180M in e-commerce sales
Broader Customer Base	PLUS serves 25M annual e-commerce users

These benefits lead to streamlined operations and happier customers. Real-world examples show that quick implementation is possible.

Next Steps

With proven results and clear advantages, it's time to take action. Michael Dell puts it best:

"If you're not applying AI across your organization and thinking deeply about reinvention, you're already behind"

Here’s how you can start integrating low-code and AI into your retail operations:

Evaluate Your Needs: Pinpoint areas where these technologies can enhance efficiency and customer experience.
Target Quick Wins: Automate repetitive tasks to see immediate results.
Adopt Scalable Solutions: Learn from PLUS's model to continuously improve and grow your platform.