Market Basket Analysis: Optimizing Promotions and Retail Strategy with Product Associations
- lancejosephmanalan
- Jun 28
- 3 min read
Updated: Jul 10
In a highly competitive retail landscape, understanding what products customers tend to buy together can unlock powerful opportunities for smarter promotions and more efficient store operations. By applying association rule mining, this analysis dives deep into Brwr Coffee & Bread’s transaction data to uncover meaningful product relationships that go beyond surface-level trends.

The dashboard titled "Optimize Promotions: Top Product Associations" presents a visual summary of these relationships through key performance indicators like support, confidence, lift, and conviction. These metrics help identify not just frequent combinations, but also those with high strategic value—whether for bundling, upselling, promotional planning, or even store layout decisions.
This blog explores the top rules revealed by the data and turns them into actionable insights for enhancing both customer experience and business performance.
I. Overview
This product association analysis reveals high-value insights from transaction patterns at Brwr Coffee & Bread. Using association rule mining, the dashboard pinpoints which items are commonly bought together, and how these relationships can drive smarter promotions, bundling, and in-store placement.
II. Best for Bundle Sale
Top Rule by Support
Rule | Support (%) |
Coffee (C) → Bakery (Bk) | 98.17 |
Insight: A striking 98.17% of transactions that include Coffee also include Bakery items. This strong support suggests a natural product pairing, ideal for combo deals, meal sets, or grab-and-go packages (like Breakfast Bundle). Placing these items together and bundling them at a slight discount could increase basket value, enhance customer convenience, and increase overall sales.
III. Top Recommendations
Top Rule by Confidence
Rule | Confidence (%) |
Bakery, Drinking Chocolate → Tea | 99.96 |
Insight: When customers purchase Bakery and Drinking Chocolate, they are almost certain (99.96%) to also buy Tea. This makes Tea a perfect upsell target when either or both of those items are selected—either online (recommendation engine) or in-store (suggestive selling at checkout).
IV. Best for Promotions
Top Rule by Lift
Rule | Lift |
CB, DC, F, PC, T → Branded, Loose Tea | 3.17 |
This rule exhibits the highest lift value (3.17), meaning that when customers purchase Coffee Beans, Drinking Chocolate, Flavours, Packaged Chocolate, and Tea, they are over three times more likely to also purchase Branded items and Loose Tea, compared to customers who buy those items independently.
This strong relationship suggests that these products complement each other exceptionally well in the minds of customers, reflecting a pattern of premium or curated purchasing behavior.
V. Product Repositioning Strategy
Top Rule by Conviction
Rule | Conviction |
CB, DC, LT, PC, T → Bk, F | 55.43 |
Insight: With a conviction score of 55.43, this rule indicates that customers who purchase Coffee Beans, Drinking Chocolate, Loose Tea, Packaged Chocolate, and Tea are very likely to purchase Bakery and Flavours as well. This suggests a strong associative pattern that can guide product placement strategies. Positioning these items near each other can encourage complementary purchases and impulse buying, improving store flow, boosting sales, and enhancing customer satisfaction through convenience.
VI. Strategic Recommendations
From this focused one-rule-per-metric view, we extract the following actionable insights:
Bundle Coffee and Bakery for high-traffic morning promos and to increase average basket size.
Upsell Tea when customers buy Bakery or Drinking Chocolate, both in-store and online.
Promote Branded items and Loose Tea using discounts or coupons, as they’re significantly more likely to be purchased with certain product combinations than independently.
Group Bakery and Flavours with related products in-store to encourage impulse purchases.
Personalize offers in loyalty apps and email campaigns using common purchase pairings.
VII. Conclusion
This product association analysis highlights the value of turning sales data into clear, practical actions. From identifying strong product pairings to guiding promotions and product placement, these insights offer Brwr Coffee & Bread an opportunity to align operations more closely with real customer behavior.
By applying these patterns, Brwr can:
Increase average basket size through well-matched bundles like Coffee and Bakery.
Boost promo results by offering discounts or coupons on Branded items and Loose Tea when bought with related products.
Capture more add-on sales with timely upsells like Tea alongside Bakery or Drinking Chocolate.
Improve store flow and visibility by grouping commonly paired products together.
Personalize marketing in loyalty programs and email campaigns for better engagement.
Smart retail means staying one step ahead of what customers want. With these data-backed insights, Brwr Coffee & Bread is equipped to optimize promotions, improve customer experience, and drive sustained growth.
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