Bundle products dynamically: ecommerce hack #07

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Dynamic product bundles are an effective strategy for offering customers a customized shopping experience and increasing sales at the same time. Unlike static bundles, which contain fixed product combinations, dynamic bundles adapt flexibly to individual preferences and behavior patterns. Through these personalized offers, they create real added value by providing customers with a perfectly matched selection that exactly meets their needs. This article highlights the benefits of this strategy and provides practical insights into how both small and large e-commerce companies can dynamically design their product bundles to increase customer loyalty and sales.

What is a product bundle anyway?

A product bundle is a combination of several products or services that are sold together as a package. Compared to buying the products individually, a bundle usually offers a price advantage or added value for the customer. It is a strategy to promote the sale of several items at the same time by presenting them as a complete solution.

Product bundles can be static or dynamic:

Static product bundles: A fixed set of products is offered as a package. Customers cannot change or exchange the products included.
Dynamic product bundles:
These bundles adapt to individual customer preferences. They are put together in real time based on customer behavior, preferences and previous purchases. The aim is to offer customers a personalized and relevant package that better meets their needs.

Overall, product bundles serve to offer customers added value and at the same time increase sales by selling several products at once.

What is mixed price bundling?

Mixed bundling is a sales strategy in which a company offers products both individually and in bundles at a discounted price. This means that customers have the choice of buying a product separately or in a bundle with other products.

Characteristics of mixed price bundling are:

Flexibility: Customers can decide whether they prefer to buy a single product or a combination of several products.
Products offered in a bundle are usually cheaper than if they were bought individually. This makes buying the bundle more attractive for customers.
Companies can offer different combinations of products or services in a bundle to address different customer needs.

An example of this could be an electronics company that sells TVs and soundbars individually, but also offers them as a bundle at a discounted price. This way, customers who only need one TV or one soundbar can buy them individually, while customers who need both products prefer the bundle at a reduced price.

Dynamic product bundles- important aspects 


Dynamic product bundles are characterized by high adaptability by using real-time data to respond to customer interactions and preferences. With the ability to learn from this data, the bundles continuously adapt to individual needs and offer personalized recommendations. These adjustments increase the perceived value for customers by providing more relevant product combinations. As a result, the dynamic bundles increase the likelihood of repeat purchases and improve overall customer satisfaction, leading to higher sales and stronger customer loyalty.

Analysis of customer preferences and behavior:

Dynamic product bundles are characterized by high adaptability by using real-time data to respond to customer interactions and preferences. With the ability to learn from this data, the bundles continuously adapt to individual needs and offer personalized recommendations. These adjustments increase the perceived value for customers by providing more relevant product combinations. As a result, the dynamic bundles increase the likelihood of repeat purchases and improve overall customer satisfaction, leading to higher sales and stronger customer loyalty.

Increase in value:

Dynamic product bundles increase the perceived value of an offer by creating packages tailored precisely to the preferences and needs of customers. Suitable bundles that meet the individual tastes of customers significantly increase the attractiveness of the offer. The greater relevance of these personalized product combinations leads to increased conversion rates and a higher average order value. Customers perceive these dynamic bundles as more valuable because they contain exactly the products that reflect their current preferences and interests, making them more willing to buy more.

Cross-selling opportunities:

Dynamic product bundles offer considerable opportunities to increase sales through targeted up- and cross-selling. Products that complement each other are recommended together, encouraging customers to buy more than originally planned. This strategy increases interest in items that might not otherwise have been considered, as customers are made aware of relevant products through personalized recommendations. This creates a compelling shopping experience that encourages customers to engage with products that perfectly suit their needs and increase their order value.

A/B tests and optimization:

A/B testing and continuous optimization are key to unlocking the full potential of dynamic product bundles. Testing different combinations helps to identify the most effective bundles for different customer segments. By presenting different bundles in parallel and analyzing their performance, it is possible to identify which configurations lead to higher conversion rates and increased sales. This optimization strategy ensures that dynamic bundles are always relevant and appealing to the respective target group. By continuously adapting the bundles based on real-time data and customer insights, the strategy is better aligned to the specific needs and preferences of customers.

Automation and scalability:

Automated systems offer the opportunity to efficiently scale recommendation bundles for extensive product catalogs and diverse customer bases. Thanks to AI and machine learning, these systems can recognize patterns in customer behavior to create dynamic product bundles tailored to the specific needs and preferences of different target groups. This automation ensures consistent personalization and adaptability by leveraging real-time data and past purchase patterns. The result is recommendations that are not only accurate but also scalable, increasing customer appeal and boosting average order values.

Improved customer experience:

Dynamic Product Bundles significantly improve the customer experience by offering customized suggestions that make the shopping experience smoother. By precisely tailoring product combinations to customers' individual preferences and needs, they reduce the time normally spent searching for relevant products. This not only promotes customer satisfaction, but also increases the likelihood of repeat purchases, as the personalized suggestions inspire the customer in a pleasant way and offer added value that goes beyond the mere product offering.

Strategies for the effective implementation of dynamic bundles


Analyze your customers' preferences, buying habits and demographic data to identify different customer segments:

Behavioral data: Track your customers' purchasing behavior to understand product preferences and buying patterns.
Product data:
Analyze product features, categories and compatibilities to identify meaningful bundling opportunities.
External data:
Integrate external data sources such as market trends and seasonal demand to adapt dynamic bundling to current conditions.

This information helps you to create bundles that reflect the specific interests of your target groups.


Use customer data and machine learning algorithms to identify individual preferences and develop personalized bundles:

Customer profiles: Create detailed customer profiles that include purchase history, preferences and demographic information.
Real-time recommendations:
Use machine learning algorithms to suggest personalized product bundles in real time based on the customer's current shopping cart or browsing activity.
Segment your customers according to various criteria to create customized bundles for different target groups.

This allows you to generate product suggestions or combinations based on previous purchases or viewed items.


Develop a flexible pricing strategy that makes your bundles more attractive than individual purchases, note

Price-based bundling: Discounts on individual bundle products, higher perceived value, drop, tiered and “.99” pricing
Personalized pricing: consideration of customer value, price sensitivity and competition
Price flexibility: promotions and real-time changes

Offer discounts or bonuses for bundles tailored to specific customer needs to encourage multiple purchases


The technical implementation of dynamic product bundles requires a robust data infrastructure that captures customer data, uses machine learning to predict preferences and enables a flexible pricing strategy to offer automated, personalized product combinations in real time. Pay attention to:

Platform integration: Seamlessly integrate dynamic bundling capabilities into your e-commerce platform or mobile app
Recommendation engine: Implement a powerful recommendation engine that can generate personalized product bundles in real time.
Flexibility: Make sure your system is flexible enough to support different bundling rules, product attributes and data sources.


Communicate the benefits and discounts of the bundles clearly and check whether your customers are aware of them:

Customer education: Inform your customers about the advantages of dynamic bundles and how they can benefit from them.
Targeted campaigns: Use personalized marketing campaigns to promote dynamic bundles to relevant customer segments.
Social proof: Use customer reviews and case studies to prove the effectiveness of your dynamic bundling and the positive customer experience.

Your customers should be able to immediately recognize the added value they receive by purchasing a bundle.


Conduct continuous A/B tests to find out which bundle configurations work best:

A/B testing: experiment with different bundling strategies, product combinations and presentation formats to determine optimal performance.
Data analysis: Track the performance of your dynamic bundles and continuously optimize them based on data such as click-through rates, conversion rates and average order value.
Customer feedback: Gather feedback from customers to better understand their preferences for dynamic bundles and adjust your strategy accordingly.

Use this data to continuously optimize your bundles and pricing strategies.

Best practices for dynAMic product bundles


We're all familiar with these features, but we still think this pioneer in the use of dynamic product bundling is worth mentioning because they're so basic: It offers personalized bundle suggestions to its customers based on purchase history, browsing behavior and other factors. The “Customers also bought” and “Frequently bought together” sections are examples of the effective implementation of this strategy.


Nike uses dynamic product bundling to offer customers complete looks that combine shoes, clothing and accessories. The “Outfit Inspiration” function on the Nike website enables customers to visualize different outfits and buy them directly.


HelloFresh, a food delivery service that offers its customers recipe boxes with fresh ingredients and recipes, uses dynamic product bundling to create personalized boxes based on customers' dietary needs, preferences and cooking skills.

In B2B, SaaS platforms in particular stand out due to their dynamic pricing and bundling:


Salesforce offers dynamic bundling of its various cloud solutions. For example, customers can combine Sales Cloud, Service Cloud and Marketing Cloud to create an integrated platform for customer relationship management. Salesforce uses customer profiles and usage data to make relevant bundle suggestions.

Adobe Creative Cloud:

Adobe offers dynamic bundling of its various software products. For example, customers can combine Photoshop, Illustrator and InDesign to get a package with the most important tools for creative professionals. Adobe uses usage data and purchase history to create personalized bundle suggestions.

Microsoft 365:

Microsoft 365 offers dynamic bundling of its various subscription plans. For example, customers can bundle Microsoft Teams, Word, Excel and PowerPoint to get a package with the most important tools for team collaboration. Microsoft uses company size and industry to make relevant bundle suggestions.

Getting started with dynamic product bundles: How to get off to a good start

You should have the following steps ready as a checklist if you want to get started with dynamic bundles:

Analyze customer needs: Collect and analyze customer data to identify trends and preferences. Use analytics tools to understand purchasing behavior and find out which product combinations fit together best.
Target group segmentation: Divide your customers into different segments. This allows you to develop customized product bundles that are specifically tailored to the needs of the individual groups.
Define bundle criteria: Develop clear rules and criteria for how products are brought together in bundles. This can be based on product categories, seasonal trends or complementary products.
Define pricing strategy: Establish a pricing strategy that emphasizes the value of the bundle to the customer and offers attractive discounts or bonuses compared to individual purchases.
Integrate personalization tools: Integrate machine learning or personalization tools to enable personalized recommendations based on individual customer behavior. These tools should be flexible enough to support dynamic adjustments in real time.

Develop a marketing strategy: Develop a marketing strategy that clearly communicates the added value and benefits of the dynamic bundles. Use targeted campaigns, newsletters and social media to publicize the new offer.
Initiate test phase:
Conduct a test phase to test different bundling and pricing strategies. A/B testing and data analysis can help you identify the most effective combinations.
Gather feedback:
Collect customer feedback to find out how well the bundles are received. Use this information to further optimize your strategy.

By implementing these steps, you can ensure that the introduction of dynamic product bundles in your store is successful and offers your customers a great shopping experience.

Dynamic product bundles for small and medium-sized store systems

If you are running a small to medium-sized store solution, here are some tool tips to get you started:

Plugins using Shopify as an example:

Upsell Bundle: This allows you to create product bundles with discounts when customers buy multiple products.

Screenshot from Rebolt´s App Previews

Bundled Products: Provides advanced features for creating and managing product bundles, including automatic pricing and inventory management.

Frequently Bought Together: Automatically recommends products that are frequently bought together based on purchase history and customer behavior.

Screenshot from Frequently Bought Together´s App Preview

Additional components:

Provides personalized product bundle suggestions based on machine learning and real-time customer data.

Personizely: Enables the personalization of product bundles and other elements of the store interface based on customer profiles and behavior.

Ometria: Provides a comprehensive platform for marketing automation and customer personalization, including dynamic product bundling capabilities.

Dynamic product bundles for larger store systems

It can become complex if you want to use real-time data to adapt dynamic product bundles to customer interactions and preferences comprehensively and for large numbers of customers. When tailoring your technical solution, you should have considered the following key components:

Customer Data Platform (CDP):
A CDP centralizes customer data from various sources (e.g. website, CRM, marketing automation) and creates a unified customer profile.
Event streaming platform: Captures and processes customer events in real time, e.g. product views, clicks, purchases and search queries.
Data warehousing: Stores historical customer data and event data for analysis and machine learning.
Real-time analytics: Enables real-time analysis of customer data and event data to identify patterns and trends.
Machine Learning: Trains models to predict customer preferences and generate personalized bundling suggestions in real time.
Recommendation engine: Implements recommended product bundles on the website or app based on real-time analytics and customer profiles.


CDP: Segment, Adobe Customer Experience Manager, Salesforce Customer 360
Apache Kafka, Amazon Kinesis, Google Cloud Pub/Sub
Data Warehousing:
Snowflake, Amazon Redshift, Google BigQuery
Amazon Kinesis Firehose, Google Cloud Dataflow, Apache Spark Streaming
Maschinelles Lernen:
TensorFlow, PyTorch, Amazon SageMaker, Google Cloud AI Platform
Algolia, Salesforce Einstein Recommendations, Adobe Target

Conclusion: The added value of dynamic product bundles

Dynamic product bundles offer you a promising strategy for generating more sales and retaining customers. Their core principle is based on putting together personalized packages that are precisely tailored to your customers' preferences and behavior. Unlike static bundles, they allow you to make continuous adjustments by using real-time data to create a unique shopping experience.

By analyzing preferences and demographic information, you can create targeted product combinations that add value for your customers and increase the likelihood of repeat purchases. This allows you to take advantage of both cross-selling and upselling opportunities more efficiently. Bundles can be successfully marketed with intelligent pricing strategies, automated scalability and flexible marketing communication, and A/B tests help you to continuously optimize your offer.

Whether for small or large store systems - you can successfully introduce dynamic product bundles with personalization tools and a strong technical infrastructure. This allows you to offer a precise, personalized shopping experience that stands out from the competition while maximizing your sales and customer satisfaction.