![Sweet Wheat Bakery Image](https://cdn.prod.website-files.com/63ae1987a2e57b458adc01f6/64a529d8f0a3977d207ccc28_Image%20(1).jpg)
Sweet Wheat Bakery
![](https://cdn.prod.website-files.com/63ae1987a2e57b458adc01f6/649c573eca8dcee4600df792_Sweet%20Wheat.png)
This customer case study will explore how Sweet Wheat Bakery uses product mix optimization and market basket analysis to create an assortment of baked goods that not only delights customers but also drives profitability.
The Science Behind Product Mix Optimization and Market Basket Analysis
Have you ever wondered how food service businesses like restaurants, coffee shops and bakeries determine which products and menu items to offer together in order to maximize sales? The answer lies in the intricate world of product mix optimization and market basket analysis.
Romain and Alexandre Lecat bakers and serial entrepreneurs from France fell in love with the California Coast and the West Coast lifestyle. When they decided to relocate to Los Angeles they experienced the lack of access to French products made with authentic French ingredients. They missed the flavors of France immensely, enough to start Sweet Wheat Bakery, with a promise to only use authentic French ingredients. From the Lecat brothers' humble beginnings of delivering baguettes by bicycle during the pandemic, their first bakery has grown to offer over 50 menu items that are fresh made and baked daily.
In today's competitive market, brands and businesses are constantly seeking ways to enhance their product offerings to appeal to core customer groups and attract a broader audience. The Lecat brothers wanted to optimize the brand's product mix as they consider opening more locations in new markets and expand distribution channels.
Romain believes that understanding the science behind product mix optimization and market basket analysis is crucial to stay ahead of the curve. By leveraging data analytics and consumer behavior insights, Sweet Wheat Bakery can strategically design product mixes that cater to customer preferences and drive profitability.
In this customer case study, we will delve into the fascinating world of product mix optimization and market basket analysis, exploring how these methodologies can revolutionize the way Sweet Wheat can approach their product strategies.
Uncovering Sweet Wheat Bakery's authentic French product mix
Near the coast and the bustling landscape of Los Angeles, Sweet Wheat Bakery stands out by carefully curating a product mix that not only tantalizes the taste buds of LA Francophiles but also bolsters the bakery’s bottom line. With a commitment to quality and a passion for authentic French baking and ingredients, Sweet Wheat Bakery continually seeks to enhance its offerings to better serve its dedicated customer base while attracting new patrons.
By harnessing customer buying patterns, Sweet Wheat Bakery can strategically design its product mix to align with the preferences of its clientele, ensuring each selection complements one another. Understanding the sales trends down to the day and time of top selling products also mean that they never run out of the bakery's most purchased items.
That sure is a lot of Mini Pain au Chocolats to make in a day!
Understanding the basics of Market Basket Analysis
Before we go into the details of Sweet Wheat Bakery's success, let's understand the basics of Market Basket Analysis (MBA). MBA is a pivotal data mining technique widely embraced by retailers to enhance their understanding of consumer purchasing behaviors. At its core, MBA explores historical purchase data to uncover patterns and associations between products, revealing which items are frequently bought together by customers. This insightful analysis empowers retailers to make informed decisions that increase sales and optimize marketing strategies.
The concept of Market Basket Analysis stems from the idea of a shopping cart, where each item represents a product that a customer may choose during their shopping experience. By analyzing vast datasets, businesses can identify combinations of products that often co-occur in transactions, allowing them to devise targeted marketing campaigns, improve product placements, and implement effective cross-selling strategies.
For instance, if a customer frequently purchases milk alongside bread, understanding this association could lead retailers to promote these items together, optimize their shelf space, or create bundled offers.
Ultimately, Market Basket Analysis serves as a powerful tool for retailers, providing the analytical foundation needed to enhance customer engagement, maximize sales potential, and streamline inventory management. As the retail landscape continues to evolve, leveraging insights from Market Basket Analysis becomes increasingly crucial for businesses aiming to stay competitive and responsive to consumer needs.
Sweet Wheat Bakery's Challenge #1: Identify combo opportunities to enhance sales performance
![Top 3 products: Sales Trends Over a 90-Day Period](https://cdn.prod.website-files.com/63ae1987a2e57b458adc01f6/66c3e6e090c8b671c7adf91d_66c3e1445c20340c812124be_Sales%2520Trends%2520Over%2520Time%2520-%2520Basket%2520Analysis%25402x.png)
In today's highly competitive retail environment, understanding consumer behavior is more important than ever. With countless products vying for attention, businesses must take steps to optimize their product offerings and drive sales performance.
To help our readers visualize how data and insights can help your business, we will provide excerpts to sales trends, product mix analysis and Market Basket Analysis and our recommendations for Sweet Wheat Bakery.
What insights can be gleaned from sales trends over a 90-day period?
The graph above "Top 3 Products: Sales Trends Over Time" provides a visual representation of the sales trends for three menu items: Mini Pain au Chocolat, Pain au Chocolat, and Baguette. The sales data is from a period of 90 days, February to August 2024.
The analysis of Sweet Wheat's item specific sales trend data:
Mini Pain au Chocolat (Teal Line):
- Trend: There is a noticeable fluctuation in sales over the period of 90 days, with several peaks and troughs. The sales generally range between 10 to 30 units per day.
- Consistency: Despite the fluctuations, Mini Pain au Chocolat shows a relatively consistent performance with frequent peaks.
Pain au Chocolat (Pink Line):
- Trend: The sales of Pain au Chocolat also fluctuate, with a range typically between 5 to 25 units per day.
- Patterns: There are periods where sales dip significantly, but there are also noticeable spikes, indicating sporadic high demand.
Baguette (Purple Line):
- Trend: Sales of Baguette are generally lower compared to the other two items, mostly ranging from 5 to 15 units per day.
- Variability: The sales trend is more variable and less consistent, with some significant drops and occasional spikes.
Opportunities for enhancement
Focus on high-performing items:
- Leverage Mini Pain au Chocolat: Since Mini Pain au Chocolat shows strong and relatively consistent sales, it can be further promoted by bundling the item with a combination of offers throughout the day. A more in-depth sales trend should include high-demand and low-demand sales periods during the day. The marketing team could experiment with a few different campaigns, target each campaign by customer groups and unique offers to understand the consumer's buying patterns.
Address Pain Points for Lower-Performing Items:
- Boost Pain au Chocolat: Introduce promotions, combo deals, or limited-time offers to increase the appeal of Pain au Chocolat during its low-demand periods.
- Revamp Baguette Sales: Investigate potential reasons for lower sales of Baguette with a customer survey and analyzing reviews and feedback from customers. Consider introducing variations (e.g., flavored baguettes) or pairing Baguettes with other popular items.
Promotions and Marketing Strategies:
- Combo Deals: Create combo deals that include one high-performing item (Mini Pain au Chocolat) with lower-performing items (Pain au Chocolat or Baguette) to boost overall sales.
- Seasonal Promotions: Implement seasonal promotions that align with the sales trends. For example, to boost sales during traditionally lower periods offer special discounts, a free drip coffee with a purchase of a Pain au Chocolat.
Customer Feedback and Preferences:
- Gather Feedback: Conduct surveys or gather feedback from customers to understand their preferences and reasons for purchasing certain items. Use this information to adjust product offerings and marketing strategies.
- Enhance Customer Experience: Improve the overall customer experience by ensuring product quality, timely availability, and the product knowledge and attentiveness of staff, which can lead to increased repeat purchases.
Inventory and Supply Chain Management:
Optimize Inventory: Ensure that the inventory levels of high-demand items are always adequate to meet customer needs. Avoid stockouts, especially for popular items like Mini Pain au Chocolat.
- Optimize Inventory: Ensure that the inventory levels of high-demand items are always adequate to meet customer needs. Avoid stockouts, especially for popular items like Mini Pain au Chocolat.
- Adjust Supply Chain: Review and adjust the supply chain processes to ensure timely delivery and freshness of products, particularly for items that show variability in sales.
By experimenting with different strategies, Sweet Wheat Bakery may potentially improve the sales performance of slower sales items, while maintaining and even enhancing the sales performance of the already popular product items.
Sweet Wheat Bakery's Challenge #2: Find optimization opportunities for the top 20 item product combinations
![Sample product network graph for a bakery's market basket analysis](https://cdn.prod.website-files.com/63ae1987a2e57b458adc01f6/66c3e6e090c8b671c7adf92f_66c3e1bc090020855cbdcff4_Network%2520Item%2520Combination.%2520Market%2520Basket%2520Analysis%2520-%2520Basket%2520Analysis%25402x.png)
The network graph in Market Basket Analysis is a visual representation that illustrates the relationships between items frequently purchased together. This type of graph uses nodes (or vertices) to represent individual items, and edges (or lines) to represent the connections between them, which indicate that these items are commonly bought together in transactions.
The above network graph represents the top 20 menu item combinations from Sweet Wheat Bakery's named customers. Named customers are customer profiles in your Customer Relationship Management system (CRM) with unique Personal Identifiable Information (PII), like an email address, a phone number or a physical address.
To help understand the visual, here's an analysis:
Core Items with Strong Connectivity:
Mini Pain au Chocolat and Quiche Lorraine are central items in this network graph, indicating that they are frequently paired with other items when in a customer's basket or order. Mini Pain au Chocolat, in particular, shows multiple connections, suggesting it is a popular item that Sweet Wheat Bakery customers tend to purchase alongside a variety of other products.
Commonly Paired Items:
- Mini Almond Chocolate Croissant and Camomile Orange Blossom are often bought with Mini Pain au Chocolat.
- Egg, Ham & Cheese Croissant and Prosciutto & Fig Croissant are frequently purchased together with Quiche Lorraine.
Combination Boxes:
- Items like Take Away Box, The Delivery Box, and SW - (Red) Unsalted Butter are linked to Mini Pain au Chocolat, indicating that these may be part of bundled or promotional offerings, where customers are encouraged to buy these together.
Cross-Selling Opportunities:
- The network suggests potential cross-selling opportunities. For example, since Quiche Lorraine is linked with items like Pears Asparagus Soup and Hazelnut Madeleine, offering promotions or discounts when these items are purchased together could increase sales or purchase frequency.
- The network suggests potential cross-selling opportunities. For example, since Quiche Lorraine is linked with items like Pears Asparagus Soup and Hazelnut Madeleine, offering promotions or discounts when these items are purchased together could increase sales or purchase frequency.
Key Observations:
- Items that have fewer connections, like Seasonal Fruit Tray 6-8 and Saucisson Sandwich, might be less popular or more niche to a specific customer group in Sweet Wheat's market. To validate this data point, consider A/B testing a marketing campaign to two groups: Offer a vegetarian product bundle to test group A and a non-vegetarian bundle to test group B. Consider targeted marketing or bundling these with more popular items like the Mini Pain au Chocolat to boost sales.
Strategic Recommendations
- Focus on Popular Pairings: Given that Mini Pain au Chocolat and Quiche Lorraine are central to Sweet Wheat Bakery's offerings, consider including these items as part of meal deals or bundles. There may be an opportunity to test different price points too. For example, Combo A at a lower price point will not include a Mini Pain au Chocolat, while Combo B at a much higher price point will include a Mini Pain au Chocolat.
- Introduce Bundles: Create meal deals or bundles that include popular combinations, such as a "Breakfast Bundle" with Mini Pain au Chocolat and a coffee or a "Lunch Special" with Quiche Lorraine and soup.
- Expand on Niche Items: For less connected items, such as the Saucisson Sandwich, you could introduce a new promotion or highlight them in marketing campaigns to increase their visibility and sales.
This network graph provides valuable insights into customer preferences and potential opportunities for upselling and cross-selling within your product mix.
Sweet Wheat Bakery's Challenge #3: Is there a relationship between the Mini Pain au Chocolat and Quiche Lorraine?
![Sample correlation product matrix for a bakery's most purchased menu items.](https://cdn.prod.website-files.com/63ae1987a2e57b458adc01f6/66c3e6e090c8b671c7adf93a_66c3e00e973163a709577fa9_Correlaton%2520Matrix%2520-%2520Market%2520Basket%2520Analysis%25402x.png)
What is a Correlation Matrix in Market Basket Analysis?
A Correlation Matrix in Market Basket Analysis is a table that displays the correlation coefficients between pairs of items. These coefficients measure the strength and direction of the relationship between the items based on how often they are purchased together in transactions.
How to use the Correlation Matrix in Market Basket Analysis
- Identifying Relationships: The matrix helps in identifying strong positive correlations (items that are frequently bought together) and negative correlations (items that are rarely bought together).
- Cross-Selling Strategies: Retailers can use these insights to create marketing strategies that promote positively correlated items together, like bundling or discounts.
- Inventory Management: Understanding item correlations can help optimize stock levels for items that are often bought together.
Differences from Other Tools:
While a network graph (see Sweet Wheat's challenge #2), visually represents the associations between items, a correlation matrix provides a precise, numerical summary of these relationships, making it easier to quantify and compare the strength of associations between multiple item pairs simultaneously.
Example:
If you have a correlation matrix for a bakery and see a high positive correlation between "Coffee" and "Croissant," you might decide to run a promotion offering a discount when both items are bought together, capitalizing on their strong association.
In summary, a correlation matrix in Market Basket Analysis is a powerful tool for quantitatively assessing the relationships between items, which can be leveraged to improve sales strategies and customer experience.
Analysis of the Sweet Wheat Correlation Matrix
The Correlation Matrix in Sweet Wheat's Challenge #3 is a visual representation of how the sales of different core menu items at Sweet Wheat Bakery relate to one another.
In this context:
Diagonal Elements: The diagonal elements (with a value of 1) represent the correlation of each item with itself, which is always perfect.
Off-Diagonal Elements: The off-diagonal elements show the correlation between different menu items:
- Mini Pain au Chocolat and Quiche Lorraine: The correlation is -0.014, indicating a very weak negative relationship. This suggests that sales of Mini Pain au Chocolat and Quiche Lorraine are almost independent of each other.
- Mini Pain au Chocolat and Egg, Ham & Cheese Croissant: The correlation is -0.087, showing a slightly stronger (but still very weak) negative relationship. It suggests that when one of these items is bought, the other is slightly less likely to be purchased, though the effect is minimal.
- Quiche Lorraine and Egg, Ham & Cheese Croissant: The correlation is -0.035, also indicating a very weak negative relationship, suggesting these items are purchased independently.
Interpretation and Recommendations:
- The weak correlations between these items suggest that they do not compete directly with each other in terms of sales. This means customers purchasing one item are not significantly more or less likely to purchase another from this set.
- Actionable Insight: Since these items are not closely related in customers' purchasing patterns, Sweet Wheat Bakery could consider bundling complementary products that may not show strong correlations naturally. For example, pairing a savory item like Quiche Lorraine with a sweet treat like Mini Pain au Chocolat could encourage customers to make additional purchases.
- Additionally, if the bakery aims to increase sales of specific items, targeted promotions that encourage trying different combinations might help in creating new purchasing habits among customers.
Overall, this matrix helps in understanding the current purchasing trends and offers insights on potential strategies to cross-sell or create attractive bundles.
Conclusion: The benefits of using Market Basket Analysis in bakery operations
Danny Meyer, a famous restaurateur and the CEO of Union Square Hospitality Group, talks about the importance of data and insights:
“Data is important, but insights are everything. We use data to understand what our guests want, but it's the insights that drive the experiences that make them want to come back.”
The Market Basket Analysis sales trends, network graph and correlation matrix optimizing the product mix for Sweet Wheat Bakery offers valuable insights that goes above and beyond data interpretation.
Romain Lecat, owner and entrepreneur, Sweet Wheat Bakery
By identifying the weak correlations among our top menu items, we can better understand customer purchasing behavior, facilitating informed decisions on product placement and promotions. The analysis not only highlights the independence of certain items but also opens the door for creative product bundling strategies.
This case study showcases the importance of data-driven decision-making in the modern retail and restaurant landscape. By leveraging GoGoGuest's Market Basket Analysis, Sweet Wheat Bakery is well-positioned to adapt to customer preferences and continuously refine its product offerings. As consumer tastes evolve, ongoing analysis will provide the bakery with the adaptability needed to stay competitive.
What can GoGoGuest do for you?
GoGoGuest is a data and insights driven marketing platform for food service businesses, restaurants, bars, coffee shops and retailers. Our suite of software products is designed and built to empower businesses of all sizes so they can readily adapt to ever changing landscape of consumer behavior.
Our data management and audience building suite comes with basic Market Basket Analysis features for Growth and enterprise customers. This means, your business can run MBA analysis frequently without spending Dollars on a costly consultant.
To learn more about how GoGoGuest can help automate Market Basket Analysis, product mix and other insights reporting capabilities, Book a Demo.
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