Why your business needs a personalization engine today

Highlights

You’ll learn about the benefits of personalization engines:

• Enhanced customer experience: Create unique profiles and deliver personalized content based on real-time data
• Increased engagement and ROI: Tailored marketing campaigns achieve higher engagement rates and better ROI
• Valuable insights: Analyze customer behavior to refine strategies and improve targeting
• Dynamic adaptability: Adjust to changing customer preferences for continued relevance
• Scalability: Handle growing data loads and user interactions efficiently

Tap the full potential of your business with a personalization platform.

Keep reading to learn more!

How do you feel when receiving a customized and thoughtful gift created especially for your needs? Your digital customers crave the same experience. With 80% of customers likely to buy from a brand offering personalized experiences, you cannot ignore personalization.

To do well in offline and online battles, use a personalization engine. This provides you with the best experience for each customer at the right time. 

But why do you need a personalization engine?

When brands remember how long customers have been doing business with them or when they last purchased a product, they go above and beyond to enhance customer experiences and gain trust. To do this, you need to collect the right behavioral data and that’s where a personalization engine comes in.

A personalization engine is a must for any brand looking to scale its marketing operations. To know why these engines are worth the effort, read ahead and explore how they work, their benefits and what they can do.

What is a personalization engine?

A personalization engine is software that marketers use on their websites to gather information about customers and customize their experiences. Ideally, the engine would be be built directly into the CMS.

Personalization engines help marketers identify and deliver individual experiences based on their history, current context and predicted user behavior. These engines can handle loads of data from various customer interactions. As these engines use advanced artificial intelligence (AI) and machine learning (ML) algorithms, you understand:

• What customers like
• How they behave
• Who they are

You can personalize your messages and send recommendations that match each customer’s unique interests.

But how do these engines collect data?

A personalization engine monitors a customer's activity and uses the data to deliver personalized experiences. Many marketers recommend such an engine to search, choose and deliver personalized messages and recommendations across multiple customer touchpoints. With knowledge of your customers’ likes, dislikes and past activities, these engines change the content, recommendations and marketing communication. As a result, you witness improved customer satisfaction, conversion rates and engagement.

The higher the quality and volume of data a personalization engine collects, the more information you can use, improving customer satisfaction and engagement. 

Thanks to AI, these engines can process a large amount of data while generating intelligent business outcomes.

How a personalization engine works

Data collection and analysis

A personalization engine collects customer data, such as buying or browsing history, to provide insights about your customers in real time. 

AI and ML

The engine uses AI and ML to process the data collected, forecast user preferences and identify patterns. As you collect more data, you can send accurate and personalized recommendations. 

Filtering techniques

Most engines use various filtering techniques like:

• Collaborative filtering (gathers data based on customer’s interaction with a business)
• Content-based filtering (focuses on the keywords used to describe a service or product)

For higher accuracy, many engines use a combination of these techniques. 

Real-time personalization

As these engines adapt in real time to your customers’ interactions, you can update and change their profiles to enhance engagement. 

Constant learning

These engines use AL and ML to learn from customer responses and customer journey data. The more data they gather and analyze, the more accurately they predict the changing customer behaviors and preferences.

How a personalization engine benefits your business

Personalizes customer’s shopping experience

Your customers love personalized content but rarely receive it. Providing a personalized shopping experience every time they visit your website encourages them to return. These engines create a unique customer profile for each visitor depending on their real-time shopping and browsing experience.

The AI model uses data to adjust and create a website that customers like, increasing their visits and engagement. 

Better ROI on the marketing campaign

Personalized marketing campaigns usually see higher engagement rates, resulting in better ROI. Customizing messages based on the likes and behaviors of your audience helps you create more relevant messages and compelling content. This strategy increases engagement while building stronger customer relationships.

Provides insights about customer behavior

The personalization engine analyzes how customers use your website to understand their behavior. This helps marketers learn more about their audience and fine-tune their marketing approaches. These engines incorporate smart algorithms and machine learning to monitor customers' likes and actions.

Customized communication

Personalization engines collect and analyze information to create communication materials that draw visitors to your website and increase engagement. Sending personalized emails, newsletters and landing pages leads to more conversions and higher revenue.

Steps to build a personalization engine into your headless CMS of choice

1. Define your personalization goals

Set clear and achievable objectives for your personalization efforts. It’s important to know what you want to achieve. Your goal can be to increase customer engagement, improve conversion rates or enhance customer experience.

2. Select a headless CMS

Choose a headless content management system (CMS) that integrates with personalization tools. A CMS like Contentstack offers flexibility in delivering content and provides a strong foundation for personalization strategies.

How did Lessa drive personalization using Contentstack?

Leesa improved their website for speed and personalized user experience by choosing Contentstack’s headless CMS over Shopify. The company saw a 30-fold increase in organic traffic and improved SEO. Content management became efficient, allowing personalized customer journeys and faster website performance. The transition reduced the development time. Moreover, Contentstack's integration capabilities, ease of use, and exceptional customer support helped Lessa with a seamless transition.

After using Contentstack, Richard Bilton, Director of Technology at Leesa, said: 

“It wasn’t convenient. We wanted to work with Shopify, but we needed the freedom to produce our own content the way we wanted, and to speed up the website and gain flexibility.”

Read the case study here.

3. Assess personalization tools

Take the time to assess different personalization software. Look for one that fits well with your goals and integrates with your chosen headless CMS. Evaluating the different personalization tools helps you choose one that meets your personalization efforts.

4. Integrate personalization engine

Work with your development team to integrate the selected personalization engine into your headless CMS. A smooth integration delivers personalized content without hitches.

5. Data collection and analysis

Establish mechanisms to collect and analyze customer data. Understanding customer behavior and preferences helps you deliver tailored content.

6. Create personalization rules

Define clear rules for delivering personalized content. Consider customer segments and behaviors to ensure the right content reaches the right audience. The better your rules, the more relevant your content will be.

7. Content tagging and taxonomy

Develop a tagging system to categorize your content. Good taxonomy helps you deliver accurate, relevant and personalized content.

8. Dynamic content delivery

Configure your CMS to adapt content based on customer interactions and personalization signals. This will ensure customers see content tailored to them, enhancing their experience and providing dynamic content delivery.

Best personalization engines for 2024

Contentstack

Contentstack is a premier headless CMS offering personalization software. The CMS facilitates smooth integration with various systems, ensuring dynamic and scalable content delivery. With Contentstack, you use data from various sources to create personalized experiences based on your customer preferences. 

The platform provides in-depth insights into customer behavior and preferences. Using real-time data, you can optimize customer journeys and enhance customer retention, engagement and conversion rates.

Dynamic Yield

Dynamic Yield is a personalization engine that uses machine learning algorithms. It offers product recommendations to customers and each solution complies with your customers' activity. Dynamic Yield uses real-time personalization capabilities and analyzes the information to deliver customized experiences at each stage. But, some advanced features of Dynamic Yield are more complex and challenging for new users.

Salesforce Marketing Cloud

Salesforce Marketing Cloud offers tools designed to personalize your marketing efforts. The marketing cloud offers superior data capabilities and insights into your customer behavior. The AI-driven engine provides hyper-personalized content and recommendations. But, Salesforce Marketing Cloud is expensive, making it suitable only for large-sized businesses.

Insider

Insider is another personalization platform dedicated to delivering cross-channel personalized experiences. The platform uses predictive segmentation and real-time behavioral targeting to send messages that connect with your customers. Insider works with many marketing channels, but you may need help with less common platforms.

Braze

Braze offers real-time customer engagement using personalized messaging across various channels. Using the platform's segmentation capabilities, you create targeted account-based campaigns. As Braze supports multi-channel communication, you provide personalized messages using email, push notifications and in-app messages. But, the user interface of Braze is complex and challenging for new customers.

Choosing the right personalization engine

Easy to integrate with existing systems

Integrating your personalization engine with your CMS should not be challenging. Once integrated, the engine should suggest similar products that other customers of the same profile use. 

Data-driven insights and analytics

Find a personalization engine that helps you collect customer data from various sources. With this data, you can build customer profiles, understand demographics, track transaction history and other relevant business data.

Level of personalization

Pick an engine that offers the right level of personalization to achieve your business goals. Whether you need simple segmentation or advanced one-on-one experiences, your engine should meet your requirements. 

Ability to scale

As your product catalogs grow and customer behavior changes, scalable personalization engines can help. Such engines can handle increased data loads and customer interactions. It's important to choose a solution that offers flexibility, reliability and real-time processing to meet your customer’s changing needs.

Ease of use

Opt for tools offering an intuitive interface for managing different personalization rules and content. The engine should offer clear instructions, simple navigation and strong support for your target audience. 

Supported channels

Make sure the engine can handle all the channels where you want to provide personalized content, such as mobile apps, websites, email and social media.

Challenges of personalization engines

When using a personalization engine, you might face the following challenges:

Data management

Brands using personalization engines face two challenges

• Poor quality data
• Too much data

Poor-quality data slows personalization efforts. Likewise, having too much data is another challenge. When you collect too much customer information, managing it becomes a unique challenge.

Dynamic customer preferences

Your customer preferences change with time—they like a product today and dislike it tomorrow, making it challenging to predict their requirements. You need to update your personalization strategies to stay relevant.

Limited user adoption

Another hurdle for personalization engines is getting users to use them. Even with all the potential perks, your customers may not use them because of privacy issues or a lack of understanding. Plus, if your recommendations aren't spot-on, they may consider personalization intrusive. 

FAQs

What does a personalization engine do?

A personalization engine analyzes data to provide customized content and experiences based on customer behavior and preferences.

What is personalization software?

Personalization software includes tools for creating tailored user experiences. It analyzes data and automates the delivery of personalized content.

How large is the personalization engine market?

The personalization engine market is expanding as more businesses understand the importance of personalized customer experiences in driving engagement and conversions.

Learn more

A personalization engine helps you stand out and connect with your audience. You can enhance customer experiences and drive customer engagement and loyalty using personalization. From large enterprises to e-commerce stores, these engines are a must-have. Talk to us today to see how personalization engines can transform your business.