The Ultimate Buyer’s Guide for Ecommerce Personalization Software in 2025

Personalization is baked into many of the digital experiences consumers encounter daily. Shoppers expect this. They want personalized experiences that speak to their unique preferences and needs. This is a tall order when you consider the multiple touchpoints, channels, devices, and behaviors inherent in a typical digital buying journey.

Ecommerce personalization technology helps retailers scale personalization efforts and meet consumers where they’re at (even if it’s in the car waiting for their child’s Parkour class to end) by combining a cocktail of technologies to serve up tailored product recommendations, relevant content, and customized search results. 

When done right, personalization creates meaningful connections with shoppers and brands. And, of course, consumers demand that buying journeys be relevant—and they don’t seem to mind when artificial intelligence is involved. According to Wunderkind’s 2025 US Consumer Insights Report for Personal Commerce, AI personalization “excites” 52% of Gen Z and 60% of Millennial consumers. 

Finding the right personalization software for your business requires careful evaluation of various platforms and their capabilities. This comprehensive guide examines leading personalization solutions, comparing their features, strengths, and limitations to help you make an informed decision for your organization.

Why Ecommerce Personalization Matters 

Consumers are opportunistic when it comes to buying what they want or need. Most use multiple channels to get from point A to point P (purchase). CapitalOne Shopping notes that 73% of retail customers are “omnichannel” shoppers. These shoppers interact with brands across an average of six touchpoints during their typical purchase journey, making personalization essential for creating consistent, relevant experiences.

Omnichannel shoppers are high-value shoppers. The CapitalOne research found that companies with high omnichannel customer engagement see a 179% increase in sales revenue compared to those without. Personalization connects the dots across the many touchpoints and channels shoppers are using, but it’s also a baseline expectation. It’s what’s come to define a good (or great) ecommerce experience. 

BCG data backs this up. In a recent BCG survey of 5000 consumers, over 80% respondents said they expect personalized experiences when shopping online. Both men and women rank availability of an item among their top considerations when making online purchases. Aligning product availability to individual shopper behavior requires personalized merchandising approaches—this is what ultimately leads to higher conversion rates, reduced cart abandonment, and happier shoppers. 

And for younger generations of shoppers, particularly Gen Z, personalization is all they know. Gen Z and Millennial consumers actively seek out and embrace AI-powered personalization in their shopping journeys. This puts the onus on retailers to choose a personalization platform that can create one-to-one personalized experiences that motivate and resonate.  

Factors to Consider When Choosing Personalization Software 

Modern personalization platforms need to work with your existing tech stack, so look for solutions that can integrate with your CMS, CRM, analytics tools, and data repositories. 

Here are some important criteria to consider when shopping for enterprise-ready personalization technology:

📈1. Scalability and AI-Powered Growth

The platform should grow as you grow, so consider the size of your catalog and customer base now and what it might look like a few years from now. Look for solutions that use AI to automate and facilitate many of the processes needed to scale as you scale. This includes data unification and management, machine learning, natural language processing, and large language models that analyze customer behavior and optimize experiences in real-time.

🧑‍💻2. User Experience and Interface

The solution you choose should be intuitive enough for marketing teams while offering advanced capabilities for technical users. Look for features like visual editors, drag-and-drop interfaces, and pre-built templates that make it easy to create and roll out personalized experiences without heavy reliance on IT resources.

📊3. Analytics and Reporting

Advanced analytics capabilities help you understand what’s working and what isn’t, but they also help identify trending products, new opportunities, and customer behavior patterns across the entire buying journey. Look for a platform that provides detailed journey analytics with insights around customer behavior, campaign performance, and ROI. You want to understand the entire buying experience which means you need direct access to data that demonstrates, with precision, the financial impact of your personalization approach.

💰4. Cost and ROI Considerations

While pricing varies by provider and implementation scope, focus on platforms that offer transparent pricing models and clear paths to ROI. Consider factors like implementation costs, ongoing maintenance, and the level of support provided. When in doubt, look to track measurable key performance indicators (KPIs). The right solution should demonstrate measurable impact on key metrics like conversion rates, average order value, and customer lifetime value.

Best Ecommerce Personalization Software Platforms

There’s no one-size fits all technology that exists to meet every retailer’s needs (if only). So, we’ve compiled a list of the best ecommerce personalization software—in our expert opinion—to help you get started on your own buying journey, starting with our own offering.

1️⃣. Monetate

We’ve listed Monetate as the premier choice for enterprise-level personalization because we lead with AI and machine learning—and this has been the case for over a decade. Monetate’s platform combines AI-powered discovery, testing, and personalization capabilities focused on helping shoppers find exactly what they need. 

Standout Features: 

• Personalized search which uses advanced NLP to connect shoppers with exactly what they want
• AI-driven product recommendations based on real-time data that uses adaptive ML to improve over time
• Dynamic testing capabilities for continuous experience optimization
• Automated personalization that uses integrated AI which adapt entire experiences to individual shopping patterns
• Journey analytics for deep customer behavior insights across the whole digital buying journey
• Audience analytics & insights for data-driven decision making to help you understand what moves and motivates shoppers. Monetate offers direct integration with tools like Snowflake, Tableau, and Power BI.

Key Differentiator:

Monetate’s unique strength lies in Orchid AI, our proprietary intelligence layer that combines a sophisticated blend of machine learning, natural language processing (NLP), and LLMs which analyze customer behavior and predict intent in real time. Monetate stands out from competitors by offering a truly unified approach to personalization that matches how people actually shop today—across multiple channels, devices, and touchpoints. 

2️⃣. Dynamic Yield by Mastercard

Dynamic Yield, which was acquired by Mastercard in 2022, is a mid-market personalization platform that provides basic experience optimization and recommendation capabilities.

Standout Features:

• Basic A/B testing and multivariate testing
• Visitor segmentation and targeting for different customer groups
• Real-time data segmentation
• Product recommendations with basic automation
• Content personalization for websites
• Limited mobile app personalization

Key Differentiator:

While Dynamic Yield offers solid personalization features for mid-market businesses, it lacks the enterprise-grade capabilities needed for true omnichannel experiences. The platform’s integration with Mastercard provides transaction data insights, but limitations in areas like testing depth, mobile SDK support, and journey analytics may require additional solutions to create unified customer experiences. Page load speed is notably slower than some competitors and they don’t offer mobile SDK support.

3️⃣. Optimizely

Optimizely is a developer-focused testing and experimentation platform that offers A/B testing along with some rudimentary personalization features. It’s best known for testing capabilities and is reliant on other tools for use cases outside of experimentation. 

Standout Features: 

• Advanced A/B and multivariate testing 
• Feature flagging for developers 
• Web content management  tools
• Real-time analytics and reporting

Key Differentiator: 

While Optimizely excels at experimentation, it lacks essential commerce features like personalized search, social proof, and product discovery. Its developer-centric approach and slower page load times (746ms) can impact both team efficiency and site performance. Most businesses need additional tools to create complete personalization programs.

4️⃣. Bloomreach

Bloomreach is a commerce experience platform focusing primarily on product discovery and content management. The platform emphasizes search functionality but requires substantial technical resources for implementation.

Standout Features:

• AI-powered product discovery engine
• Site search with merchandising controls
• Content management system (CMS)
• Basic personalization capabilities

Key Differentiator:

Bloomreach’s approach centers on content and search but lacks core personalization capabilities including multivariate testing, feature experimentation, social proof, and product badging. The platform’s steep learning curve, lengthy implementation cycles, and minimal customer support can challenge teams looking for quick deployment. Its limited commitment to clickstream data for personalization may impact the depth of customer insights.

5️⃣. AB Tasty

AB Tasty is a testing and personalization platform that focuses on website optimization and A/B testing capabilities. While it offers basic personalization features, implementation and ROI realization can take longer than some alternatives.

Standout Features:

• A/B and multivariate testing tools
• Visual editor for website modifications
• Basic content personalization
• Heat mapping analytics for easier personalization adjustments

Key Differentiator:

While AB Tasty provides solid testing functionality and simplicity for ease of use, its slower page load speed (461ms) and 5-minute reporting delay can impact site performance and decision-making. The platform lacks advanced commerce features like product badging and journey analytics, and its lengthy deployment time may delay optimization programs. Teams should consider these limitations when evaluating time-to-value requirements.

6️⃣. Constructor

Constructor is a product discovery platform that specializes in search. It also provides some limited product recommendation capabilities. While it offers foundational search capabilities, its rigid framework limits merchandising flexibility.

Standout Features: 

• AI-powered search and autosuggest
• Real-time behavioral recommendations
• Category page optimization
• Basic merchandising controls

Key Differentiator: 

While Constructor emphasizes AI-driven search and recommendations, it lacks essential enterprise capabilities like multivariate testing, product badging, and mobile SDK support. Its restricted automated configuration and basic recommendation functionality may not provide the flexibility modern retailers need for creating truly personalized shopping experiences.

7️⃣. Adobe Target

Adobe Target is an enterprise-level testing and personalization platform that integrates with Adobe’s Experience Cloud and Adobe Sensei, their AI and machine learning technology. While it offers robust A/B testing capabilities, its complexity and resource requirements can impact implementation timelines and total cost of ownership.

Standout Features:

• Advanced A/B and multivariate testing
• AI-driven personalization algorithms
• Integration with Adobe Experience Cloud
• Behavioral targeting capabilities

Key Differentiator:

Adobe Target provides sophisticated testing tools, though its implementation complexity often requires significant resources and third-party consulting support. The platform’s rigid framework often necessitates manual workarounds and inefficiencies. Without native personalized search and category page capabilities, and less robust product finder features, retailers may struggle to deliver the seamless commerce experiences modern shoppers expect.