Incorporate product bundling strategy to generate more revenue.
Have you been struggling with your Ecommerce store growth? How much do you truly understand about increasing your GMV? Drawing from my substantial experience in the FMCG industry and a background in analytics, I understand how having a solid revenue strategy can help.
I will share all about product bundling strategy including types of bundling, how does product bundling works, how to conduct product bundle analysis, and more.
This post is all about product bundling strategy.
Understanding GMV
Before delving into product bundling, it is essential to fully comprehend what Gross Merchandise Value (GMV) is. Many people widely use this in the Ecommerce space. Regardless of your Ecommerce business offerings, GMV serves as a key indicator of your growth.
The most common formula for GMV is the price of products multiplied by the number of products sold. However, have you considered GMV like this?
GMV = AOV x CR% x Traffic
- AOV (Average Order Value): The average price customers pay for every order in your ecommerce store. Calculated by total revenue divided by total orders.
- CR% (Conversion Rate): The number of visitors who make a purchase. Calculated by total orders divided by total visits.
- Traffic: The number of visits to your ecommerce store.
Looking at GMV this way, to increase it, you simply need to:
- Increase AOV
- Increase CR%
- Increase Traffic
- Increase all of the above
For product bundling, it’s a strategy Ecommerce businesses use to enhance AOV, driving business growth. Simple, right?
Now, let’s break down AOV further.
AOV = ASP x Basket Size
- ASP (Average Selling Price): The average price customers pay for each product. Calculated by total revenue divided by total products sold.
- Basket Size: The average number of products per order. Calculated by total products sold divided by total orders.
Here, with the same theory, to increase AOV, you need to either increase ASP, basket size, or both. Recognizing this, can you now see how product bundling contributes to increasing AOV? – By increasing basket size.
What is Product Bundling?
Now that you understand the core elements of driving revenue in an Ecommerce store, let’s dive straight into Product Bundling. Product Bundling involves combining 2 or more products together and offering them as a package deal.
As many other strategies, product bundling has its pros and cons as well.
PROS
- Increased AOV – Customers now purchase more items in a single transaction.
- Enhanced Perceived Value – You create value for customers by offering complementary or related products together, which will make the deal more attractive.
- Inventory Management – internally, it can also assist you in managing your inventory by promoting the sale of specific products.
CONS
- Potential Overhead – when it comes to bundled packages, there may be additional costs when it comes to packaging and marketing materials
- Choice Overload – Too many bundled options may leave customers feeling overwhelmed, leading to decision fatigue.
Common Applications in Product Bundling
Below are 3 product bundling examples that may be familiar to you.
1. Supermarket Strategies
In supermarkets and grocery stores, product bundling is a well-established strategy aimed at improving shopping experiences and encouraging customers to explore a wider range of products. Supermarkets often employ the following bundling techniques:
- Meal Kits: Offering pre-packaged meal kits containing all the ingredients for a specific recipe. This not only saves customers time but also introduces them to new products they might not have considered.
- Seasonal Bundles: Creating bundles that align with seasons or holidays, such as a BBQ bundle for summer or a Thanksgiving dinner package. This taps into the consumer’s desire for convenience during specific occasions.
- Buy One Get One (BOGO) Bundles: Providing additional quantities of a product for free or at a discounted rate when customers purchase a specific item. For instance, buy one pack of pasta and get a second pack free.
2. Beauty and Cosmetics
In the beauty and cosmetics industry, where personalization and self-expression are key, product bundling takes on a creative and enticing role. Businesses often leverage the following bundling strategies:
- Skincare Sets: Offering a curated set of skincare products that work together to address specific skin concerns. This could include a cleanser, toner, moisturiser, and a serum.
- Theme-based Bundles: Creating bundles inspired by themes such as “Summer Glow” or “Travel Essentials,” that combine products like sunscreen, a hydrating mist, and a versatile makeup palette.
- Mix-and-Match Bundles: Allowing customers to create their own bundles by choosing products from a selection. For instance, “Build Your Own Lip Kit” where customers pick their preferred lipstick, lip liner, and gloss.
3. Apparel and Accessories:
In the beauty and cosmetics industry, where personalization and self-expression are key, product bundling takes on a creative and enticing role. Businesses often leverage the following bundling strategies:
- Skincare Sets: Offering a curated set of skincare products that work together to address specific skin concerns. This could include a cleanser, toner, moisturiser, and a serum.
- Theme-based Bundles: Creating bundles inspired by themes such as “Summer Glow” or “Travel Essentials,” that combine products like sunscreen, a hydrating mist, and a versatile makeup palette.
- Mix-and-Match Bundles: Allowing customers to create their own bundles by choosing products from a selection. For instance, “Build Your Own Lip Kit” where customers pick their preferred lipstick, lip liner, and gloss.
By understanding how product bundling is effectively utilised in these diverse sectors, you can tailor your bundling strategy to align with the preferences and expectations of your target audience.
Types of Bundling
There are 6 types of product bundling strategies that you should know of.
- Pure Bundling: Involves selling products only as a bundle, encouraging customers to purchase the entire package. For example, offering a Family Feast Bundle in the supermarket for a complete and convenient meal preparation.
- Mixed Bundling: Offers both bundled and individual products, providing customers with flexibility. For instance, having a pre-curate bundle for a complete makeup look while also offering the individual make up items.
- Joint Products: Bundling items that are typically used together, like a camera and camera accessories.
- Several Products: Combining unrelated products to create a unique bundle, such as a book and a coffee mug.
- Complementary Bundling: Combining products that enhance each other’s usage, like a printer and ink cartridges. A great example in the beauty industry will be serum and day cream, day cream and night cream, or even shampoo, conditioner and scalp treatment.
- Substitute Bundling: Offering alternatives for a specific need, such as bundling different brands of headphones.
Understand How Product Bundling Works
When it comes to implementing suitable product bundling strategies, it is essential to grasp the concept of association rules – a fundamental concept that forms the backbone of conducting an analysis.
In analytics, there are 2 types of predictive analysis – supervised learning and unsupervised learning. Supervised learning is when we want to predict a value (Y) while unsupervised learning is when we want to find patterns in the dataset without depending on Y. Association rules are considered unsupervised learning and this is usually used to understand the purchase behaviour of the consumer. And in this case, by understanding the purchase behaviour of your customer, you can better come up with unique product bundling ideas that work for your ecommerce business.
In this data mining technique, there are 2 main concepts to grasp.
Antecedent and Consequent
First, the difference between an antecedent and a consequent. To understand this well, look at it like an if-then situation. To put it simply,
{A} → B
{A} is a set of items and B is an item. The way we interpret this is if all of the items in {A} appear in the shopping cart, then B is likely to appear in the shopping cart. Here {A} is the antecedent and B is the consequent.
To further explain, imagine looking at a statistic like this.
{serum, day cream} → night cream
Here, what this says is that shoppers who bought serum and day cream are highly likely going to buy night cream.
Support, Confidence, Lift
Depending on how many product offerings your ecommerce store has, you will have thousands of possible combinations of products. What you want to do is to identify those combinations with a strong relationship. And to do that, we use 3 measures – Support, Confidence, Lift.
{A} → B
SUPPORT
Tells us how frequent item A and B are bought together.
Support (A and B) = P(A ∩ B)
Here, we usually use a min support threshold to reduce the number of itemsets we need to analyse.
CONFIDENCE
Tell us how likely item B is bought given that item A is bought.
Confidence (A → B) = P(B | A) = P(A ∩ B)/ P(A)
You may face a situation where the confidence is misrepresented if item A is a best seller. This is because confidence only takes into account how well item A is sold but not item B. Hence, we use lift in conjunction.
LIFT
Tell us how likely item A and B is bought together as compared to if they were independent. This is defined as the ratio of the observed confidence to the expected confidence.
Lift ( A → B) = P(A | B)/ [P(A) x P(B)]
- Lift = 1 implies no association between the items
- Lift > 1 means that item B is likely to be bought if item A is bought
- Lift < 1 means that item Y is unlikely to be bought if item X is bought.
Resource for you: Beginner’s Guide to Data Analysis
How to Conduct Product Bundle Analysis?
Now, it is time to put your knowledge into practice. You can leverage these 3 platforms to conduct your product bundle analysis. While the code syntax and steps may differ from one platform to another, the underlying theory remains the same.
Platform 1: Python
Python offers a powerful tool for product bundle analysis using the Apriori algorithm. The Apriori algorithm is widely utilised for association rule mining, making it an excellent choice for identifying patterns in customer purchasing behaviour. For detailed steps, read more at
- Association Rule Mining in Python Tutorial by Moez Ali
Platform 2: R programming
R programming, which is known for its statistical capabilities, is also equipped with the Apriori algorithm. Utilising the arules package, you can perform product bundle analysis. Read more about detailed step by step guidance at:
- Introduction to Association Rule Mining in R by Jan Kirenz
- Market Basket Analysis Retail Foodmart Example by Siva Karthikeyan Krishnan
Platform 3: Excel XLMiner
If you are more comfortable with spreadsheet software, Excel XLMiner provides a user-friendly interface for product bundle analysis. This tool allows you to apply the same principles of association rule mining without delving into code. Learn more about the detailed step by step instructions in:
- The Art of Effective Cross-Selling Using Market Basket Analysis in Excel by Lillian Pierson, P.E.
- Download XLMiner Analysis ToolPak
Resources for you: Mini Analytics Course | Power of Analytics Course for Beginners
Things to Take Note of
Before diving into product bundle analysis, please keep these points in mind:
- In terms of Data Format, different platforms may require varying data formats. Therefore, it is essential to ensure that your data is cleaned and formatted correctly before importing it into the analysis function.
- When it comes to Handling Similar Products, it’s important to note that the analysis does not account for identical products in a bundle (e.g., A → A). Consider incorporating this combination into your analysis and address it manually or employ coding techniques.
Now, armed with knowledge and insights and ready to take inspired action. Start to implement different bundling strategies tailored to your unique offerings and customer base. Dive into the statistics and embrace trial and error. Your experimentation with bundling will uncover what resonates with your audience, driving not only sales but also customer satisfaction.
In the ever-evolving landscape of Ecommerce, mastering the art of product bundling can be a game-changer for your business. As we have explored the fundamental principles, various bundling strategies, and platforms for analysis, it is clear that strategic bundling has the potential to not only enhance the shopping experience for your customers but also significantly boost your revenue.
More Resources for You:
- Mining Association Rules between Sets of Items in Large Databases by Rakesh Agrawal, Tomasz Imielinski and Arun Swami
- Introduction to arules – A computational environment for mining association rules and frequent item sets by Michael Hahsler, Bettina Grün, Kurt Hornik and Christian Buchta
- Arules – A computational environment for mining association rules and frequent item sets by Michael Hahsler, Bettina Grün and Kurt Hornik
- Arulespy: Exploring Association Rules and Frequent Itemsets in Python by Michael Hahsler
This article covers everything you need to know about product bundling strategy.
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