What is Personalized Marketing?

Personalized Marketing is a data-driven strategy that tailors marketing efforts to match the individual needs and expectations of each customer. By analyzing customer data collected over time, brands can develop products, services, and campaigns that feel uniquely relevant to each person. Effective personalized marketing begins with consistent and ongoing data collection, which serves as the foundation for crafting customized strategies that genuinely resonate with the target audience.

In today’s digital era, where consumers are overwhelmed by information and ads, mass marketing is losing its effectiveness. Modern consumers seek experiences that reflect their unique needs and preferences. Studies show that 80% of consumers are more likely to purchase from brands that offer personalized experiences, while 72% engage only with marketing messages tailored to their interests. This shift has given rise to Personalized Marketing—a strategy that leverages data and technology to craft individualized experiences for each consumer. From global brands like Netflix recommending shows based on viewing habits, to Thai brands like Central Group offering tailored promotions through The 1 Card, these are all prime examples of successful personalized marketing in action.

Types of Personalized Marketing

1. Segmentation

Personalized marketing begins with collecting data from target audiences and customers, which is then analyzed and segmented—such as by purchase frequency, product preferences, or spending habits. The more granular the segmentation, the more accurate and effective the marketing becomes. However, brands must also be mindful of the associated costs. Clear planning and well-defined objectives are essential to ensure a strategic and sustainable approach.

2. 1-to-1 Personalization

1-to-1 personalization focuses on crafting truly individualized experiences by leveraging behavioral data—such as browsing history and product views—alongside contextual data like location and time. These insights are analyzed through tools like CRM systems, data analytics, marketing automation, and AI to deliver highly tailored, intuitive experiences for each customer.

3. Personalized Content Marketing

Personalized content marketing involves creating tailored materials—such as articles or webpages—designed specifically for individual customers. For example, a sportswear brand might use customer data to identify a favorite football team and recommend products featuring that team’s logo or colors. By aligning content with customer interests, brands can create memorable experiences and increase the likelihood of word-of-mouth promotion.

4. Personalized E-Mail Marketing

Email marketing remains a powerful yet challenging channel, as customers receive countless emails each day. Personalized email marketing—such as including the recipient’s name, sending birthday wishes, or offering a thank-you discount—can significantly boost open rates and encourage customer engagement.

What is Hyper-Personalized Marketing?

Hyper-Personalized Marketing takes personalized marketing to the next level by leveraging more detailed and in-depth data—such as real-time online behavior, recent search and purchase history, as well as contextual data like location and time. It relies on advanced technologies like AI, machine learning, and big data analytics to deliver highly accurate and timely marketing messages that truly align with each customer’s current needs and preferences.

Hyper-Personalized Marketing VS Personalized Marketing

Hyper-Personalized Marketing and Personalized Marketing Although both approaches share a similar underlying concept of creating personalized experiences for customers, they differ significantly in terms of data usage and technology.

Personalized Marketing typically relies on basic data collected from customers, such as demographic information (age, gender, location) and purchase history, to analyze and create offers that cater to the needs of specific customer segments. For example, sending promotional emails with recommendations for products the customer has purchased or shown interest in the past, or suggesting products that are likely to appeal to a certain customer group based on basic categorization.

In contrast, Hyper-Personalized Marketing takes personalized marketing to the next level by utilizing deeper, real-time data through more sophisticated technologies such as Artificial Intelligence (AI), Big Data Analytics, and Machine Learning. These technologies allow brands to accurately analyze individual customer behaviors, such as tracking website activities, search data, past purchase behavior, and specific contextual information like location and timing. By leveraging this in-depth data, brands can create highly tailored experiences, such as recommending products or content that meet the customer’s needs at the right moment, or even delivering messages aligned with the customer’s current interests and emotions.

The clear distinction between the two approaches lies in the level of accuracy and depth of the data used. Personalized Marketing allows brands to adjust content and offers for broader target segments, with general categorization. In contrast, Hyper-Personalized Marketing focuses on meeting individual needs at a deeper, more timely level by integrating a variety of data to gain a detailed understanding of customer behaviors and preferences.

Hyper-Personalized Marketing enables brands to leave a deeper impression, as customers feel that the brand truly “understands” and “knows” them. While Personalized Marketing provides a satisfactory level of customization, it does not achieve the same depth as Hyper-Personalized Marketing. The synergy between in-depth data and advanced technology is the key factor that drives the effectiveness of Hyper-Personalized Marketing to a higher level.

Steps for Implementing Personalized Marketing:

1. Collect Customer Data – Gather data on purchasing behavior, interests, and demographic information
2. Analyze the Data – Analyze the collected data to segment customer groups and better understand their needs.
3. Plan the Strategy – Use the insights from the analysis to design tailored marketing offers that align with the needs of each customer segment.
4. Execute and Optimize – Launch the marketing campaign and continuously refine it based on the results and feedback.

Tools for Implementing Personalized Marketing

When it comes to Personalized Marketing or Hyper-Personalized Marketing, utilizing the right technology and tools is crucial for effectively analyzing data and connecting with customers. Here are some popular tools that help brands enhance their ability to execute personalized marketing:

1. CRM (Customer Relationship Management)
   • Salesforce: A CRM system that manages customer data and tracks interactions, helping brands enhance relationships and boost sales opportunities.
   • HubSpot CRM: A tool for managing customer data and tracking sales team performance, with features that support Personalized Marketing.
2. Data Analytics
   • Google Analytics: A website analytics tool that helps brands understand user behavior and provides insights such as traffic sources, visit duration, and content engagement.
   • Adobe Analytics: A tool for in-depth data analysis that helps brands identify trends and better understand customer behavior.
3. Marketing Automation
   • Mailchimp: An automation tool for email marketing, allowing brands to design campaigns tailored to customer behaviors and needs effectively.
   • ActiveCampaign: An automation tool that manages marketing campaigns and creates workflows designed to respond to customer actions, such as sending emails based on website visit behaviors.
4. AI and Machine Learning
   • IBM Watson: An AI system that analyzes real-time data and creates highly accurate, personalized experiences tailored to individual customer needs.
   • Amazon Personalize: A Machine Learning service that enables brands to create highly personalized product and content recommendations based on individual customer interests.

Examples of Global Brands Successfully Using Personalized Marketing

Global Brands Example:

• Nike – Nike utilizes the “Nike By You” platform, allowing customers to design their own shoes, from selecting colors to adding names and choosing materials and styles. Additionally, Nike analyzes users’ app behavior, such as running and exercising patterns, to recommend relevant products and fitness equipment tailored to each individual’s needs.
• Warby Parker – Warby Parker creates an online eyewear shopping experience that closely mimics an in-store experience with their “Home Try-On” system. Customers can try five pairs of glasses at home for free. They also offer an AR feature in their app for virtual try-ons and analyze eyewear preferences to recommend styles that best match the customer’s taste.
• Sephora – Sephora’s “Beauty Insider” program collects data on purchases, makeup styles, skin tones, and shopping behavior to suggest personalized beauty products and makeup tips. Additionally, their “Virtual Artist” app allows customers to try on makeup virtually by taking a photo, further enhancing the personalized shopping experience.

Thai Brand Example:

• Central Group – Uses The 1 Card to track purchases and customer behavior, enabling personalized promotions. This led to a 45% increase in coupon usage compared to generic promotions.
• AIS – Uses mobile and internet usage data to offer packages tailored to user behavior, resulting in a 23% increase in package renewals.
• SCB – Developed the SCB EASY app with screens and features personalized to each user, leading to a 35% increase in user satisfaction.

Cautions in Personalized Marketing

Personalized marketing is a powerful tool for building strong customer relationships and boosting conversion rates. However, there are key cautions to consider to avoid potential pitfalls, as follows:

1. Data Management

• Collecting high-quality, sufficient data for analysis.
• Cleaning and organizing data to ensure usability.
• Regularly updating data to keep it current.

2. Privacy and Data Protection

• Complying with the Personal Data Protection Act (PDPA).
• Obtaining customer consent for data collection and usage.
• Ensuring the security of customer data.
• Maintaining transparency in data usage.

3. Operational Considerations

• Costs related to system and technology investment.
• Skill development for effective implementation.
• Training teams to understand and use technology efficiently.
• Coordination across teams such as marketing, IT, and data analytics.
• Managing resources and time throughout the project.

4. Customer Experience

• Balancing privacy with personalized offers.
• Avoiding customer irritation from excessive communication.
• Maintaining communication quality even in personalized marketing.

Return on Investment (ROI) in Personalized Marketing

Studies and data from various organizations show that personalized marketing can deliver strong, worthwhile returns:

Sales and Revenue

• Increase in email open rates by 29%.
• Increase in email link click-through rates by 41%.
• Average sales growth of 20-30%.
• Average cart value increase by 40%.

Customer Relationships

• Increase in customer satisfaction by 35%.
• Decrease in service cancellation rates by 25%.
• Increase in repeat purchase rates by 50%.
• Increase in word-of-mouth referrals by 45%.

Future Trends in Personalized Marketing

The use of more advanced AI and machine learning. AI technology will enable more accurate analysis of customer data and behavior, allowing for predictions of customer needs and the ability to offer products or services before customers even realize they want them.

Integrating Online and Offline Channels. Omnichannel personalization that connects both in-store and online customer experiences. For example, using online data to enhance in-store services.

Voice and Visual Search. Voice and visual search will play an increasingly important role, prompting brands to adjust their personalization strategies to accommodate new search behaviors.

Real-time Personalization. Real-time content and offer adjustments based on customer behavior, such as modifying website pages based on current browsing activity.

Privacy and Transparency. Brands must place greater emphasis on transparency in customer data usage and provide customers with control over their personal information.

Personalized Marketing and Hyper-Personalized Marketing are strategies that effectively strengthen the relationship between brands and customers. In the digital age, where customers have abundant information and choices, brands that can market with a deep understanding of their customers gain a competitive advantage. However, personalized marketing must strike a balance between creating a positive customer experience and respecting privacy. It also requires preparedness to face challenges in technology, personnel, and data management to ensure sustainable success in customer-centric marketing.