How to use data to drive personalization

We all prefer brands that understand us, cater to our needs, and share our values. It is crucial for a brand to build a data personalization strategy. Personalization becomes a key selling point. The potential for your business growth through data personalization is not just significant; it's exciting. In this post, we will answer this question and focus on data-driven personalization and its implementation for business growth.

How personalization enhances brand marketing and advertising

Let’s start with a quick look at personalization trends in 2024. AI-powered monitoring, short-form video, and story-driven visualization are the most popular trends. According to the latest annual report by RSW/US, AI-powered personalization is the hottest trend. This is not surprising, given the impressive power of AI-powered analytics tools in analyzing and predicting consumer behavior.

However, for these powerful tools to work, you must feed them massive, high-quality data assets. In other words, you need to be a data-driven business.

Being a data-driven business means using data to make informed decisions. Having access to data is just the beginning. To make the data useful, you must go through several steps. You have to collect and organize high-quality data and ensure the data is stored and handled safely and compliantly. By employing a data-driven operation, your business gets many benefits, like enhanced decision-making, when each of your steps is backed up by solid facts and research.

This leads to better operational efficiency and budgeting. What’s more, a data-driven approach allows you to build seamless user journeys and achieve better personalization. This gives a data-driven business a great competitive advantage.

What data to track to create personalized content

Now that we agree that data personalization is a must let’s clarify what data needs to be tracked to create personalized marketing content. It's not just about collecting data; it's about understanding your customers' needs and preferences to build a more empathetic and connected marketing strategy.

User identification data

It gives you basic demographic information about the customers.

Examples:

• Name
• Email address
• Phone number
• Physical address
• Birth date
• Gender
• Purchase history
• Demographic information
• Loyalty program membership

Descriptive data

Such data categorizes and characterizes customers based on different attributes. It helps businesses understand who their customers are, divide them into groups, and market to these groups accordingly.

Examples:

• Workplace
• Salary range
• Lifestyle/hobbies
• Habits
• Values
• Opinions
• Personality traits

Contextual data

Contextual data offers insights into the specific circumstances and conditions surrounding a client's interaction with a business. This data helps to understand in what environment the message reached the customer.

Examples:

• Device type
• Location
• Time/Date
• Weather
• Browser

Behavioral data

Behavioral data provides insights into customers' actions and behaviors. This type of data collected allows businesses to understand how customers interact with the brand, its products, and its services.

Examples:

• Frequency of purchases
• Repeated purchases
• Use of offers
• Clicks
• Newsletter interaction

All the above-listed data and personalization, based on it, can have a massive impact on your business. Let’s move to the next point - how to track and use data for personalization efforts.

How to track and use data for personalization

Before moving to data tracking, you must have a precise plan of what data you want to track and what platforms you want to track it on (everywhere possible is not a good answer since you can’t create a generalized campaign and expect it to succeed across different platforms evenly), and why you want to track specific data (to create better-targeted ad campaigns, to check if the product meets client expectations, etc.).

Let’s review the basics of how you can collect the necessary information about your customers to create a data & personalization connection that can boost your business revenue growth.

Collect data from various sources

Collecting all the data assets you can get isn’t the way to go here. You want to collect only high-quality customer data that can be utilized for fine-tuning business operations.

Here are the best examples of data sources to use:

Those are the top sources for collecting customer data for personalization. Your list of sources could be different based on your business.

Segment data

After collecting the data, you need to segment your audience to understand clearly who your customers are. For instance, if you are a clothing brand, you would need to figure out how your brand is doing in a particular region. You might want to know what age group your visitors who are interested in a specific product category fall into, their gender, and how they learned about your product. With this information, you can cater your ads to customers looking for a product but have yet to purchase.

Based on the peculiarities of your business, you could have different segmentation criteria. Usually, you want to segment your user data based on:

• Demographic characteristics (age, gender, location, language).
• Behavior (browsing behavior, purchase history, frequency of visits, and interaction patterns).
• Psychographics (interests, values, lifestyle choices inferred from behavior).
• Technographic (device type, operating system, browser type).
• Engagement (level of engagement with the website or service, like active, inactive, or returning user).

Analyze and optimize personalization

After you’ve collected and segmented user data, you can move on to fine-tuning personalization. You need to evaluate your Key Performance Indicators (KPIs) to measure how your personalized ads are doing. For instance:

• Engagement
• Conversion rates
• Click-through rates
• Average order value
• Customer retention rate
• Customer lifetime value

When you track the same key metrics before and after implementing personalization, you can see how the KPIs change and tweak your personalization strategy accordingly.

Prioritize first-party data

Personalization is only possible with first-party data. First-party data refers to information collected directly from your customers through your channels. This data includes all insights gained from interactions with your clients using your business's tools and platforms.

This data lets you understand how customers engage with your services or products. No level of market research and cross-website cookie tracking can give you as much valuable information about your customers as they can do themselves.

How to collect first-party data and use it:

• Use first-party user data with the help of sGTM
• Encourage your customers to create accounts
• Ask for feedback and study it

• Make polls, surveys, quizzes, and questionnaires
• Use the power of CRM systems
• Set up server-side tracking

Let’s talk about server-side tracking and first-party data a bit more here. 

One of the best ways to use first-party data effectively is to implement server-side tracking. Many platforms already support offline conversions, and you can integrate offline conversion tracking using the server Google Tag Manager container. This integration works because server-side Google Tag Manager (sGTM) can interface directly with the APIs of marketing and analytics platforms.

You can configure webhooks from your CRM or POS systems to send data to sGTM, disseminating information on offline conversions for use in analytics and ad networks. Implementing offline conversions through sGTM offers a real-time, cost-efficient solution.

Even if web tracking is restricted, server-side monitoring allows you to continue transmitting user data as long as you have the necessary consent. This capability enables advertising platforms to identify the user type and accurately assign conversions to your business. As a result, server-side tracking helps advertisers gain deeper insights into their target audience and build more precise remarketing lists.

With Stape, you can set up Facebook offline conversions, Google Ads offline conversions, Snapchat Conversions API, LinkedIn Conversion API, and more.

Data privacy concerns and personalization

One of the most vital concerns regarding data personalization efforts is user privacy. When a business gathers, processes, and uses personal data to tailor users' experiences, it navigates different security and legal challenges. 

More customers are unhappy and intimidated by their data being handled by third-party vendors, sometimes without their consent or even knowledge. More users choose to use tracking prevention software and ad blockers and opt out of cookie consent (based on a Ruler Analytics study, the average cookie consent rate in 2023 was as low as 31%).

The ethics of ad personalization is also a significant factor to consider. Look at the following stats displaying how users perceive different types and levels of personalization.

So, apart from complying with all the data privacy regulations, you also need to make sure your Datta tracking policy is ethical and the data you collect and process is safe with you. After all, your brand's reputation is at stake, and we all know cases when brands have barely recovered from data leakages.

Ensure compliance with data protection regulations

Certain regulations and laws have already been established in response to data privacy concerns. However, the strategies that govern user privacy and data collection continue to evolve.

First, there are regulations like CCPA, GDPR, and the ePrivacy Directive that every business processing personal data should comply with. There is also HIPAA, a U.S. law that primarily aims to protect patients' privacy and data security concerning their medical information and health records.

User consent

To establish data-driven personalization, one of the most important things to do is to develop clear data consent communication with your customers. Consent management is obtaining customers' permission before collecting and utilizing their personal data. This concept emerged as a necessity for organizations in the healthcare sector, where it was crucial to secure patients' consent regarding who could access their protected health information. Further on, with the emergence of data privacy regulations such as GDPR, CCPA, and others, consent management became relevant for every company handling personal data.

Here are the main steps to establish a straightforward and effective consent management process:

• Explain data processing practices to your customers clearly. When a customer visits your website or app for the first time, they should see a pop-up explaining what data your company collects and how the data you collected will be processed and used.
• Give your customers consent options (accept all cookies, accept only strictly necessary cookies, etc.).
• Get user consent to store their data. Usually, when users share their data and click the consent box to sign up for a newsletter, they receive an email confirming they intend to receive this information from the brand.
• Give options to withdraw consent. Customers should be informed that they have the right to revoke their consent and request the deletion of their data from the records at any time.

Review and update your consent policy. Audit your data consent policy to ensure compliance with relevant regulations and inform consumers about changes that could impact their data privacy.

Ways in which server-side tracking can help with personalization and privacy compliance

Server-side tracking is a great tool that can help businesses customize user experiences without compromising privacy. 

Below is an overview of the benefits server-side tracking can offer for data-driven personalization. From better data tracking and collection to better compliance and control, we see no reason why a business should miss out on the opportunities it offers.

Pseudonymization

To use Google Analytics in a GDPR-compliant way, you should implement two main things: an EU proxy server and pseudonymizing user data before the export. User data pseudonymization occurs inside the GA4 tags in the web and server GTM container.

At Stape, we are implementing a list of features to help you remove user data automatically. We don't have strict rules on which data should be removed; it's up to you to determine your company's security level. For instance, you can remove or mask the user's IP address. While parameters like country, language, and browser alone may not uniquely identify users, combining them could lead to identification.

There’s no debate about removing parameters like client ID or URL queries, as these can uniquely identify users, especially with unique Google IDs. For example, suppose you need to analyze mobile vs. desktop traffic or browser-based conversions. In that case, you must decide whether to remove all data that could lead to fingerprinting and user identification or just some of it. Can you retain information like browser and device while removing other identifiers?

Consult with your legal team or Data Protection Officer (DPO) to ensure compliance and protection against regulatory scrutiny. For enhanced security, remove all identifiers that could enable fingerprinting and re-identification.

HIPAA Compliance with GA4 + server-side tracking + Anonymization

Google Analytics is not inherently HIPAA compliant. This is primarily because it's not designed to handle Protected Health Information (PHI) as outlined under HIPAA guidelines. For example, Google Analytics 4 was not compliant for a while when the Privacy Shield wasn’t there. The only compliant ways to use Google Analytics were server-side tracking and pseudonymization. 

To be HIPPA-compliant, you cannot use GA4 alone at this point. You need to anonymize the user data that you collect. You can do it with the Stape Anonymizer. Its main goal is removing or anonymizing user data from Google Analytics 4. We filmed a video guide on removing user data from Google Analytics with the help of Anonimyzer.

Conclusion

Using data personalization is a game-changer for businesses wanting to connect with their customers more personally. It helps brands deliver personalized experiences that truly resonate, boosting customer loyalty and driving growth.

To really maximize data personalization, it's essential to switch to server-side tracking. This approach not only provides more accurate data insights but also helps you comply with privacy laws, keeping your customers’ trust safe. By adopting server-side tracking, you can easily combine data from both offline and online sources, target your audience more effectively, and uphold strong ethical standards in data handling.

Switch to server-side tracking to stay competitive with Stape and meet your customer's ever-changing needs with the help of data-driven personalization. Contact us if you have any questions left or need help setting up server-side tracking.