A No-Code Market Basket Analysis Journey
Introduction : Why basket market analysis matters
Have you ever walked down the aisles of a grocery store and noticed that milk is placed next to bread or soda is right beside chips? At first glance, it might seem like a random arrangement, but it’s far from accidental. Behind every strategic placement is a powerful technique called Market Basket Analysis(MBA) - a method retailers use to understand what customers are likely to buy together. By studying purchase patterns, businesses can optimize store layouts, run promotions that truly work, and increase sales, all by anticipating customer behavior.
Traditionally, performing Market Basket Analysis requires specialized skills. Data scientists often spend weeks cleaning data, writing code, running algorithms, and visualizing results. Even with their expertise, the process is time-consuming and often inaccessible to managers or business owners who don’t code.This is where Terno AI comes in. Terno transforms raw transaction data into actionable insights without a single line of code. Even someone with zero technical experience can uncover hidden shopping patterns, identify cross-selling opportunities, and design smarter promotions in minutes.
In this journey, we tested Terno AI on a publicly available grocery dataset[1]. The results were fascinating. From discovering best-selling staples to uncovering hidden relationships that could boost revenue, the experience highlighted the potential of AI-powered, no-code analytics. Here’s a step-by-step breakdown of our MBA journey with Terno AI.
Prompts explored via Terno AI: Conversation Link
Step 1: Uploading Data and Running Exploratory Data Analysis (EDA)
Before diving into advanced analytics, it’s crucial to understand your data. Our dataset [1] contained thousands of grocery transactions, with each row representing a single item purchased in a customer’s basket. While this may sound simple, even basic insights can reveal a lot about customer behavior.
Prompt: “Perform exploratory data analysis, check for missing /duplicate values, and show top-selling products.”
Key Insight: Even before performing Market Basket Analysis, it was clear that staples like milk and bread drive the size of baskets. Recognizing high volume products is important because they can anchor promotional strategies and ensure that stores maintain stock of items that frequently appear in transactions. EDA not only identifies trends but also ensures data is clean and ready for more advanced analysis. Terno’s automated cleaning feature saves hours of manual work, which is especially valuable for business managers without technical expertise.
Step 2: Finding Product Associations
Once we understood the dataset, the next step was identifying which products are frequently purchased together. This is the heart of Market Basket Analysis: uncovering patterns that reveal customer preferences and buying habits.
Prompt: "Run Market Basket Analysis on the top 20 products. Show frequent itemsets and association rules with support, confidence, and lift."
Insight: Whole milk acts as a “magnet product”. It appears in nearly every frequent pairing. Retailers should ensure milk and related items are always in stock and cross-promoted. Understanding these associations allows businesses to design data-driven store layouts. For example, placing rolls or baked goods near milk encourages additional purchases. Similarly, recognizing that soda is often bought with milk opens opportunities for targeted promotions or bundle offers.
Step 3: Going Deeper with Lift Analysis
Frequency alone does not capture the full value of an association. Some item combinations appear often simply because they are popular individually. To uncover unexpected, high-value relationships, we examined lift values. Lift measures how much more often two items are purchased together compared to what would be expected if they were independent. A higher lift indicates a strong, potentially surprising association that could unlock new cross-selling opportunities.
Prompt: “Which products have the highest lift values when bought together”
Insight: These hidden relationships are valuable for crafting incremental revenue strategies. Imagine offering:
1. A discount on soups when buying preservation products
2. Pasta + kitchen utensils as a meal-prep bundle
Lift analysis highlights opportunities that go beyond obvious associations. It helps businesses create innovative promotions that surprise and delight customers while increasing basket value.
Step 4: Smart Cross-Sell Strategies
In addition to uncovering popular product pairs, Terno AI identifies ways to bundle slow-moving products with high-demand items. This prevents losses from low-selling inventory and boosts overall sales. For example;
- Kitchen utensil + bottled water
- Bags + yogurt
- List Item
- Baby cosmetics + bottled water
- Frozen chicken + bottled water
Prompt: "which low selling products can be bundled with high selling products to improve sales.”
Why this matters: Instead of randomly discounting low-selling items, pairing them with staples ensures promotions are effective and improve basket size. This approach also enhances the customer experience by offering convenient, curated bundles. Cross-selling strategies informed by lift analysis can significantly impact revenue. Retailers can create themed bundles — such as “weekend cooking essentials” or “healthy meal prep packs” — that feel natural and useful to customers.
Step 5: Weekly Shopping Habits
Shopping patterns often differ between weekdays and weekends, reflecting lifestyle changes. Terno AI can segment transactions by day to uncover these nuances.
Prompt: “How do product combinations change between weekdays and weekends”
Findings:
- Weekdays: Customers tend to shop quickly and buy functional items (e.g., sausage + whole milk).
- Weekends: Shoppers are more likely to prepare family meals or bake (e.g., other vegetables + rolls/buns become the top pairing).
Insight: Promotions should be tailored to match these habits:
- Weekend offers: Focus on fresh produce, bakery items, and meal-prep bundles for families.
- Weekday offers: Emphasize convenience items and essentials that support busy routines.
Step 6: Visualizing Patterns with Terno
While numbers provide insight, visualizations make patterns instantly understandable. Terno AI generates interactive heatmaps, network graphs, and other visualizations to reveal clusters of related products.
Prompt: "Create a heatmap of frequently co-purchased products.”
- Darker spots indicate stronger co-purchase patterns.
- Staples like whole milk, vegetables, and bakery items form clusters, showing which items are naturally grouped in baskets.
Network graphs provide additional insights: clusters reveal shopping themes such as breakfast items, meal prep kits, or snacks. These visualizations are essential for:
Optimizing store layouts.Designing in-store displays.Planning targeted marketing campaigns.
The beauty of Terno is that these visualizations are interactive, enabling managers to explore relationships in real time without programming skills.
Step 7: Getting suggestions on cross sell strategies
The primary goal of cross-selling is to increase the average order value (AOV). By providing data-backed suggestions for cross-selling, Terno.ai enables FMCG retailers to significantly boost revenue and profitability. Its AI-powered platform moves businesses beyond guesswork by identifying non-obvious product relationships, like the co-purchase of "sausages + soda" or "citrus fruits + root vegetables." These actionable insights can be used to optimize physical store layouts, create highly targeted marketing campaigns, and deliver a more personalized customer experience.
Ultimately, Terno's ability to turn complex data into clear, strategic recommendations empowers retailers to make smarter, more effective decisions that increase the average order value and enhance customer loyalty.
Prompt: "Suggest cross-sell strategies for FMCG items with declining demand.”
Step 8: Real-World Applications and Business Impact
The insights generated by Terno AI are more than just numbers; they directly translate into business strategies that increase revenue, optimize inventory, and improve customer satisfaction. Here are a few ways businesses can leverage these findings:
- Inventory Management: Ensure magnet products like whole milk are always in stock, especially when paired with other high-demand items.
- Promotional Campaigns: Design bundle offers based on lift analysis to boost sales of slow-moving inventory.
- Store Layout Optimization: Group frequently co-purchased items together to encourage incremental purchases.
- Targeted Marketing: Send personalized promotions based on shopping patterns segmented by weekdays and weekends.
- Revenue Growth: Incremental cross-selling and bundling can significantly increase basket size without heavy discounting.
- By turning raw transactional data into actionable insights, Terno AI empowers businesses to make data-driven decisions with speed and confidence.
Conclusion: Turning Baskets into Business Strategy
Our journey with Terno AI demonstrated the transformative power of no-code Market Basket Analysis. In just a few steps, we went from raw grocery data to insights that typically require weeks of work by data scientists.
Key Achievements:
- Identified best-selling staples driving basket size
- Discovered frequent product pairings for cross-selling opportunities
- Revealed high-value, hidden relationships using lift analysis
- Designed smart cross-sell bundles for slow-moving products
- Tailored promotions based on weekday vs weekend shopping patterns
- Visualized patterns using heatmaps and network graphs for actionable insights
The Takeaway: Businesses no longer need to guess what customers want. With Terno AI, predictive, intelligent analytics are accessible to anyone, regardless of coding skills. Whether you are a small grocery store, a retail chain, or an e-commerce platform, Terno enables you to unlock hidden shopping patterns and turn them into revenue-driving strategies.
Curious about the full findings? The complete analysis is available here at : Terno AI Link
Stop guessing and start predicting. Book a demo with Terno AI today and see how easily your business can transform data into decisions.
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