A practical guide to get started with content personalization

Personalization is on the agenda for many companies. With 89% of business leaders believing personalization is crucial to their success in the upcoming years, and 86% of executives reporting that their marketing strategies demand more advanced personalization than their current capabilities allow.

Though you might want to take those stats with a small grain of salt, as they both come from surveys sponsored by personalization technology vendors, there’s no denying that there’s a high bar for content personalization. People are now very familiar with having algorithms pick the perfect content (TikTok, YouTube, Netflix, etc), and businesses are having to ramp up personalization strategies to meet expectations.

#What is content personalization?

Content personalization is too often thought of as just the marketing tactics used to get people in, and back into, the digital door. With one Forrester survey finding that while 92% of B2B companies used personalization in marketing, only 54% personalized customer engagement.

Like with any courtship, putting more effort into the first impression than into maintaining the long-term relationship generally isn’t the best recipe for success. The most effective strategies use personalized content all along the customer journey.

This could be content that keeps people engaged after the first click, such as:

• persona-based messaging on hero banners and calls-to-action (CTAs),
• product recommendations based on browsing behavior,
• customer logos and testimonials that match their industry.

Content that makes purchasing decisions easier, such as:

• product pages that highlight attributes they care about (ingredients, sustainability, compatibility, warranties, etc),
• a feature comparison table populated by products they’ve engaged with,
• service recommendations based on their conversation with a chatbot.

Content that keeps loyal customers coming back, such as:

• an email with how-to guides featuring products they bought last week,
• product recommendations in their preferred styles and price points,
• notifications when their wish-listed items go on sale,
• custom B2B catalogs for logged-in users.

As well as all the content adjustments that make the experience “run as it should” that customers might not even recognize as personalization, such as:

• only showing products and services that are available in their region,
• adapting the experience to their browser and device,
• sending push notifications about their order status.

#Why invest in content personalization?

In a 2023 survey from Twilio, 8 in 10 business leaders said that personalization leads to an increase in consumer spending, reporting that customers spend an average 38% more when their experience is personalized.

The business benefits of personalization increase as your strategies get more advanced. In a survey of 500 B2C executives, companies were categorized based on their personalization maturity level. When comparing personalization leaders with low-maturity brands (each group representing a quarter of respondents), the leaders were:

• 48% more likely to have exceeded revenue goals in the previous year
• 67% more likely to report increased purchase frequency
• 71% more likely to report improved customer loyalty

However, there can be a gap between the personalization expectations of brands and consumers. In one study that looked at how both sides define success, while 92% of retailers surveyed believe they effectively offer personalized experiences, only 48% of consumers agree.

So what do customers want out of personalization? According to Forrester’s October 2024 Consumer Pulse Survey:

• 62% want economic value (money saved or rewards earned)
• 36% want function value (useful products and services)
• 28% want experiential value (pleasant interactions and easy transactions)
• 15% want symbolic value (feeling appreciated and respected)

#Degrees of personalization

Content personalization is the overarching strategy of transitioning from a static, one-size-fits-all customer experience to dynamically delivering the best-suited content to each user. Many personalization strategies combine a range of tactics that sit all along that spectrum.

So while some people (and personalization technology vendors) are sticklers for differentiating between tactics like customization, segmentation, and personalization, they all have useful applications and are going to impact each other in the overall path to personalization.

Customization vs personalization

In general:

• Customization is the way that users are able to modify the experience or product themselves, like adjusting notification settings, changing their region, bundling their own items, or favoriting products.

• Personalization is the adjustments that are made automatically.

Suppose a person goes out of their way to customize the experience. In that case, they’re sending very valuable signals, and it would be a waste not to use that information for further personalization. If they choose the vegan delivery box, or sign up for notifications about a team’s betting odds, or repeatedly place a particular brand’s products on their wishlist, then the content shown to them across the website, app, emails, and any other channel should reflect those preferences.

Personalization vs segmentation

In general:

• Segmentation groups people based on a distinct list of parameters or characteristics, typically controlled by manual rules and settings. The data used for segmentation is generally slow to change, like demographic data.

• Personalization targets an individual user and is typically controlled by automated rules and algorithms. Personalization can take advantage of fast-moving data, like browsing behavior, to adapt to changing user intent in real time.

Segmentation builds the foundation for a personalization strategy. Defining key user groups helps teams better understand the customer journey, hone marketing messaging, and decide what content to invest in. It’s also a good first step because you can get started with very minimal data (e.g., new and returning visitors) and gradually ramp up to much more complex strategies with users in multiple segments.

Some common ways to segment customers are by using:

• Demographics / Firmographics. The general characteristics of a person (demographics) or the company they work for (firmographics). Such as age, gender, location, interests, occupation, or company size, industry, and revenue. This is often third-party data purchased from advertisers or other data services.

• Context. How, where, and when customers interact with your brand. Such as the date, time of day, device, channel, and the referral URL or marketing campaign that led them to you.

• User Behavior. The information learned about users as they interact with your channels. This could be segments like “frequent cart abandoner”, “repeatedly viewed product page but hasn’t converted”, or “high average order value”. As well as groups based on preferred brands, product lines, styles, and price points.

• Buyer Journey Stage. Where customers are in the sales funnel, such as awareness, evaluation, purchase, or loyalty. Typically based on a lead scoring system where key actions and engagements with certain content are given a point value to track how users move along the funnel.

• Personas. Groups that take a more holistic look at users’ values, goals, and what factors drive them to convert. Personas are very specific to your customer base and are determined by a mix of demographics, user behavior, and your own industry knowledge. They could be groups like “parents who shop for children”, “fantasy football power players”, or “sustainability-focused skincare enthusiasts”.

Segmentation paints the broad strokes of the experience, and then personalization comes in to do the fine details. Using automated rules and algorithms to tailor the experience to each person and adapt it in real-time as user intentions change across a session.

There are many tools on the market that offer different approaches to content personalization. From rules-based solutions (if X, then Y), to recommendation models that combine user preference with global data, to AI-driven personalization engines that predict the likelihood of specific actions (propensity to buy, engage, churn, etc) and adjust the experience accordingly to encourage a desired outcome.

#Examples of content personalization journeys

A new visitor enters a home goods eCommerce shop

• It is a Friday afternoon in the summer, so the homepage hero banner features the “weekend outdoor furniture” marketing campaign. Based on their current location, the visitor is added to the “urban” segment, so they see the banner image variant that shows a balcony.

• As they browse the site, the personalization engine takes in information about the content and products they engage with to learn their preferred product categories, price range, colors, and design styles. The “similar items” carousel at the bottom of product pages reflects these preferences.

• When applicable, the product page also features editorial content. The personalization engine sends a request to the CMS for content that matches the product category (bookshelf) and the user’s design style segment (minimalist), and the user is shown a thumbnail that links to the blog “6 design tips for a decluttered bookshelf”.

• They choose a bookshelf and go to checkout. The product recommendation block on the checkout page shows the message “These would look great on your shelf!” and displays products that have been tagged as “shelf size” and match the customer’s preferred design style and colors.

• Immediately after purchase, the customer receives a thank-you email with a how-to video about assembling their new bookshelf.

• Two weeks later, they received a follow-up email asking them to share their decorating style. The email is automatically populated with other customer-submitted images that match the product category of the item(s) purchased.

A user logs into the customer portal of a packaging materials manufacturer

• The homepage shows an article about the upcoming changes to recycling regulations in their country, and which packaging materials comply with it.

• They get a pop-up notification that one of their commonly ordered materials has been restocked and is now available again.

• Their company is in the segment “has a premium product line,” so they are shown the marketing campaign banner about the launch of a new line of textured paper labels.

• Since their company is in the segment “food and beverage,” the product pages show image variants tagged as “food and beverage” when available, and otherwise show the default images.

• When they search for label materials, the product lines that are suitable for food and beverage, are in their typical price range, and use adhesive that is compatible with their previously purchased packaging materials, are boosted to the top.

• Product availability and delivery estimates are based on the region.

• Based on the company’s typical order frequency for different product catalogs, they are sent an email reminder to reorder previously purchased materials.

#Data for personalized content

There are three main roles of data in content personalization:

• the WHO: The data used to profile and segment users. This could be third-party demographic data from advertisers and data brokers, as well as first-party data you collect as customers interact with your own channels. It’s common to use a Customer Data Platform (CDP) to build up a unified customer profile from different data sources.

• the WHAT: Advanced personalization needs highly structured content data to be able to dynamically choose and deliver different variants to each user. The Content Management System (CMS) should store content in a modular way and make it easy to manage rich content metadata that can be read by any personalization engine.

• the WHEN: The contextual data used to pick the best content in context, such as individual browsing behavior or global user trends. There are many types of tools that can be used to collect and act on this data like marketing automation platforms, A/B testing tools, and personalization engines.

Centralized data

Companies use an average of 6 tools to assist with personalization efforts, and the data and content from these tools need to be unified and accessible. If teams have to jump in and out of platforms or, worse, have to copy and paste information between systems, then it’s going to be very hard to maintain and scale personalization strategies.

This is where a headless content system really shines. With a headless approach, content is created and stored in a very structured way so that it can be delivered to and adapted for any digital channel (the “heads”).

In general, this makes it easy to manage content for all your channels, brands, regions, and customer segments in one place. For personalization in particular, the API-based approach of a headless CMS means that teams can integrate content with their preferred data platforms and personalization engines.

Managing content in a neutral, API-first structure also means you aren’t locked into one way of doing content personalization. If you want to experiment with more advanced personalization tools, or even completely swap out your data platform, you can do so while still leveraging all the content you’ve already invested in.

User privacy

Personalization is becoming more and more an earned strategy, with changing regulations and industry shifts giving users more control over how their data is used.

The GDPR and ePrivacy Directive already let European users opt out of non-essential cookies, and nearly half of US states have introduced data privacy legislation that will give people the right to opt out of data processing for profiling and targeted advertising purposes.

Internet browsers are also giving people more choice about privacy. While Google quietly reversed its plans to require cookie opt-ins, Chrome does now give users the option to block third-party cookies - as do most other popular browsers.

So what does this mean for companies wanting to personalize content?

Respect the data skeptics…

As it becomes easier for consumers to control their data privacy, businesses will have to be ready for more anonymous users. Only 15.83% of iPhone users opted in to app data tracking in Q4 2024, and when EU cookie consent banners have a legally compliant design (i.e., the reject all option is on the top level and not hidden behind a gauntlet of clicks), cookies are rejected in 60% of visits.

While many people aren’t comfortable with a catch-all agreement to hand over their data, as they get to know your brand, they might better respond to gentle, transparent requests to share certain data for specific use cases (i.e., zero-party data). Such as:

• Would you like to take this style quiz to receive personalized product recommendations?

• Should we set your default city to Colorado for future event notifications?

• Speak with our chatbot for personalized advice on which services best suit you.

• Join our loyalty program to receive personalized offers and discounts.

In the end, however, there are some people (30% of them, according to Forrester) that are simply never going to be motivated to share more data - and that’s ok. Companies can leverage global user trends and the inherent relationships between content items to ensure that these anonymous users continue to find helpful information, even if their experience isn’t technically “personal”.

… and spoil the data sharers

51% of US consumers are willing to share their data for a more personalized experience, and that’s a very valuable group!

In a 2024 Deloitte survey, respondents were split into four groups based on their affinity for personalization. The group most open to personalization (the fanatics) were willing to spend at least 30% more as a result of a personalized experience, and when compared to the group with the lowest affinity (the skeptics), they were:

• 7x more likely to recommend a brand

• 9x more likely to consider purchasing

• 15x more likely to post positive ratings and reviews

When users are willing to trade their data for value, the brands that make good on that promise will be rewarded accordingly.

#Where to start with content personalization

1. Define the business goal

Choose the high-level goal that you want personalization efforts to work towards, like “improve customer retention”. Agreeing on a specific focus helps teams decide what content and tools to invest in and how to best measure the return on that investment.

2. Identify high-value customer actions

Looking at the customer journey related to this business goal, what are the key steps a customer would take to signal success? Such as:

• first purchase
• account creation
• email sign up
• open promotional email
• loyalty program sign up
• redeem loyalty reward
• app download
• increase order frequency
• purchase of a new product category
• share a referral code
• provide a positive review

3. Uncover drivers and drop-offs

What are barriers to these high-value actions? Are there common traits and behavioral signals of users that convert and those who don’t? Which points in the journey are customers most likely to drop off? How do drivers and paint points differ between key user segments?

Diving into existing analytics data can help answer these questions. We also asked sales and customer service teams about how they solve challenges for different customer groups.

4. Pick personalization tactics

How can personalized content be used to overcome barriers and incentivize the desired high-value actions? This could be tactics like:

• localized homepage content
• highlight product features relevant to personas
• boost preferred styles in search results
• custom product bundles
• banners that highlight loyalty benefits
• exclusive loyalty reward offers
• recommend editorial content related to past purchases
• restock reminders of favorite items

5. Choose success metrics

What concrete measurements can you use to monitor progress? Such as:

• sales per customer
• repeat purchase rate
• order frequency
• churn rate
• loyalty program sign-ups
• net promoter score

6. Find the right data

Once you know the personalization tactics and measurements you want to implement, work backwards to figure out the data sources, workflows, and resources you need to make it happen. Determine what can already be accomplished with your existing systems, and where it makes sense to invest in new ones.

#Personalizing content at scale

Implementing personalization is an investment and, like with any good investment, the reward should outweigh the effort. It’s especially critical that efforts are maintainable as personalization strategies ramp up and serve more complex use cases.

Some of this comes down to smart strategies that don’t try to personalize every piece of content but focus on the elements that are going to make the most impact. Some of it comes down to having the right tech.

A CMS that can support large-scale personalization efforts offers:

• a modular approach to content that allows core content to be reused across channels, regions, and personas with the flexibility to personalize specific content blocks strategically.

• structured content that can be integrated with a team’s preferred data systems and personalization engines.

• editing tools, user permissions, and content tagging capabilities that make it easy for global content teams to create and manage content variants without the help of IT.

If you’re interested in how a modern CMS can help advance your personalization strategy, we’d love to have a chat.