The importance of personalization in marketing (w. examples)

“No longer will people accept viral marketing. What consumers are expecting – and craving – is a more personalized, curated experience.” – Penny Wilson, former CMO of Hootsuite

In fact, a McKinsey study backs this quote up, saying that “71% of consumers expect companies to deliver personalized interactions. And 76% get frustrated when this doesn’t happen”.

Just goes to show just how important personalization really is and why your revenue marketing strategies, including digital marketing, should take this into account.

Personalization is back (or never left)

The goal of personalization in digital marketing is to tailor messages to individual customers based on their preferences, behaviors, and needs. This approach leads to higher levels of engagement, retention, conversion, and revenue.

But this isn’t new talk.

Back in 2015, research published on Harvard Business Review found that personalization can:

Reduce acquisition costs by up to 50%,
Boost revenue by 5-25%, and
Increase the efficiency of marketing spend by 10-30%.

And most people see the value of personalization in marketing.

For example, recommendation engines (tools that suggest products and services based on data and algorithms), which are a key element of personalization, are set to reach 12.03 billion USD by 2025 – clearly, improving customer experiences is a must.

Benefits of 1-to-1 personalization in digital marketing

Personalized content and recommendations resonate more with individual customers, capturing their interest and encouraging interaction, as well as customer engagement. This leads to higher CTRs (click-through rates), boosting the likelihood of conversions.

On-site recommendations based on browsing history and past purchases (like Amazon’s “customers who bought this also bought” feature) can go a long way. Sending personalized suggestions via email can increase the chance of users making a purchase.

Personalized promotions and discounts are effective because they’re based on past behaviors and tastes, making targeted offers much more impactful. They reduce the amount of time and effort required for users to convert.

Segmenting customers by purchase frequency and offering special discounts to people who buy from you often can help you boost those sales. For example, send people a discount code when they abandon their shopping cart.

You can also use data about your customers’ behavior and purchase history to adjust the pricing of your products. For instance, offering a discount to someone who’s shown interest in a product but hasn’t bought it yet. This can increase the likelihood of repeat purchases.

You can provide better customer service by using data to offer tailored support. For example, if you have a record of past purchases and interactions, your customer support team can offer assistance that is highly targeted and relevant to consumers.

AI in marketing is becoming increasingly widespread, which includes chatbots. They can offer personalized responses and product recommendations based on user queries and behavior.

In fact, Sundar Pichai, Google CEO, also said that search will become even more personalized, as the platform seeks to help users find what they’re looking for, with AI playing a big role in that.

“Customer expectations have changed since the mid-20th century, when accessibility of product was the key to capturing markets. Today, customers want to stand out while being a part of a crowd. The desire to own a product that carries personal signature is conspicuous. Marketers discovered this latent need and the concept of personalization germinated with the proliferation of technological advancement.” – Chandra et al, Personalization in personalized marketing: Trends and ways forward

Loyalty programs are another element you shouldn’t discount. They can be tailored based on individual preferences and behaviors – e.g., you can offer points for actions that are most relevant to consumers.

You can also use data to understand and map out individual customer journeys, providing personalized content and offers at each stage. This allows you to more easily develop strategies based on those target users which leads to a boost in acquisition and retention.

Personalized product recommendations can help you to upsell and cross-sell, too, increasing the value of your transactions.

And who can forget user-generated content? This tactic can be used for social proof, such as reviews and testimonials that align with people’s interests. So, make sure to encourage and showcase content created by your customers, since this can build a sense of community and trust.

Website personalization strategies

Dynamic content

This refers to the customization of your site or email content based on user data. For example, changing headlines, images, and product recommendations to align with a user's past behavior, preferences, or location.

So, when your users visit your website, dynamic content adjusts in real time based on their previous interactions. A returning customer might see product recommendations based on their past purchases or browsing history.

When it comes to email, you can use dynamic content to personalize subject lines, offers, and product suggestions. People who browse certain categories may receive an email with promotions tailored to those categories.

Personalized content makes them feel understood and valued, which improves their overall experience with your brand.

Behavioral targeting

Behavioral targeting is all about using data about a user's online behavior to deliver tailored ads and content. This can be based on browsing history, search queries, or past interactions with the brand.

Cookies are one way to do it. They track user activity across websites, allowing you to understand which pages people visit, how long they stay, and the actions they take.

Ad retargeting also falls under the umbrella of behavioral targeting. Users who visit your site but don’t complete a purchase might see retargeted ads for those specific products on other sites.

The benefits of these is that they’re more relevant to the user’s interests and behaviors, which can lead to higher conversion rates.

Customized landing pages

These landing pages are tailored to specific segments of users based on their previous interactions or demographic information. They’re created in such a way that they match the people’s needs and interests more closely.

For example, people who clicked on a particular ad might be directed to a landing page that highlights the features and benefits of the product they showed interest in.

The content, images, and CTAs (calls-to-action) on the page can be customized based on user data. A returning customer might find a welcome message and special offers.

Landing pages that align with people’s interests are more likely to convert visitors into leads.

Remarketing

Remarketing is used to re-engage users who’ve previously interacted with your brand but didn’t complete a desired action; e.g., filling out a form or buying a product.

By tracking user behavior through cookies and pixels, for instance, you can create targeted remarketing lists that deliver personalized ads.

This means people are receiving messages that are relevant, improving user engagement and driving conversion rates.

How does personalization in digital marketing work?

As mentioned, personalization in marketing is all about leveraging customer data and tech to create tailored messages, content, and experiences.

Here’s how the process can look like:

1. Data collection

When a user visits your website, you’re able to collect data on their browsing behavior, such as the product categories they view, the products they click, and the time they spend on each page.

Information like gender, age, location, purchase history, interests, time of day, etc., all of this can be collected, allowing you to create a full picture of the people visiting your site.

Besides analytics, you can also gather customer data through surveys and feedback forms, and social media monitoring.

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Unsure which tools to use to collect data? Check out the ones outlined in our Tools of Choice Report, including Seamless.ai, Lead411, and Adapt.

2. Segmentation

Based on the user’s behavior, you can categorize them into segments – groups of customers that fall into predefined categories based on shared characteristics.

It’s important that you update segments as new data comes in.

3. Recommendation engine

The next step is to identify patterns in customer data to predict future behaviors. You’d also recommend products that other people have bought or content that other people have viewed based on what users are interacting with, etc.

4. Personalized recommendations

This means modifying the site, email, or app content in real-time based on profile and behaviors. Users get personalized messages featuring the suggestions the engine recommended, which are tailored specifically to them.

It’s crucial to ensure a seamless personalized experience across all channels, not just the site.

For example, NA-KD, a Swedish fashion brand, was able to increase customer lifetime value by 25% by providing personalized experiences across their site, mobile app, email, SMS, and push notifications. They also increased their ROI by 72x in 12 months.

5. Purchase

The user buys the product that was recommended to them.

6. Feedback

Based on user and buyer feedback, you’ll know which areas need improvement and which are working as they should. You can then adjust your personalization tactics based on this, as well as on evolving customer preferences.

7. Performance measurement

This involves A/B testing to see which content resonates better with your users and buyers, and tracking metrics like engagement rates, customer lifetime value, and average order value.

AI and machine learning for scaling personalization

AI and machine learning analyze vast amounts of data to uncover patterns and insights that humans might miss, from customer behavior to engagement metrics.

They process data from various touch points (such as website visits, purchase history, and social media interactions) to better understand users.

Then, algorithms can segment customers into specific groups based on certain attributes, which allows you to create strategies tailored to those segments.

AI tools like chatbots and virtual assistants can handle customer inquiries, provide recommendations, guide users along their journey, and more, saving you time and effort.

This type of AI uses natural language processing to understand and respond to customer questions in a natural way, and can also remember interactions and context to deliver better answers (a.k.a., more personalized).

You can also use AI to predict future behaviors and trends based on historical data. AI can identify patterns that indicate a customer might churn, for example, which allows you to focus on retention strategies.

It’s also worth noting that AI and machine learning can be used to automate the customization of marketing messages and campaigns. They can make adjustments in real time and apply personalization techniques to hundreds, thousands, and millions of users simultaneously – while ensuring each individual receives a relevant and engaging experience.

The challenges preventing you from implementing and scaling personalization

Implementing personalization isn’t always easy and often comes with its own challenges.

Data collection: You have to handle data from many sources, which are often in isolated systems, making it hard to create a unified view of your customers. To overcome this, you can implement customer data platforms and tools to integrate and collate data from multiple sources.
Privacy and compliance: You must adhere to regulations like GDPR and others, which vary by region and tend to be quite complex. But this also helps to build consumer trust, so be transparent about it.
Content creation: Personalized marketing means creating a large amount of content catering different groups. It can be tough to maintain brand consistency as well. And, though automation is crucial for this process, you have to avoid losing a more human and personal touch.
Cost and resource allocation: You may end up using a lot of resources and spending a significant amount of money, so you must ensure ROI for all your personalization initiatives, which can be a challenge.

Real-life examples of personalization in marketing

Do you know how renowned companies have successfully used personalization in their marketing campaigns?

We want to leave you with a few examples that illustrate everything we’ve talked about.

Netflix

Netflix’s revenue has grown by almost 30 billion USD since 2007, when they switched to a subscription-based video streaming service.

Everyone who subscribes to Netflix (and even those who don’t) is aware that the platform offers recommendations based on users’ viewing history, ratings, and preferences – meaning they’re able to suggest TV shows and movies tailored to individuals.

They achieve this by using an advanced algorithm and data analysis. The result? This personalization allows them to boost user engagement levels, as well as satisfaction, helping Netflix to increase loyalty and customer retention.

Another thing Netflix did was A/B test its personalized recommendations, which allowed them to understand what viewers wanted to see.

Spotify

“Personalization is at the heart of what we do at Spotify – just think of fan-favorite playlists like Discover Weekly, or our annual Wrapped campaign.” – Spotify Newsroom

Spotify really hit gold with their ‘Spotify Wrapped’ campaign. It provides music listeners with a personalized year-in-review that showcases the songs, artists, and genres they listened to the most.

What this does is promote sharing. People love to share their Wrapped summaries, whether on social media or in-person, leading to brand loyalty, user engagement, and word-of-mouth marketing.

Other companies have adopted this method, creating their own version of Wrapped (e.g., Strava’s Year in Sport and Duolingo’s Year in Review), which shows the widespread power of this marketing strategy.

But that’s not all. Spotify also released an AI DJ, which is a “personalized AI guide that knows you and your music taste so well that it can choose what to play for you. This feature (...) will deliver a curated lineup of music alongside commentary around the tracks and artists we think you’ll like in a stunningly realistic voice.”

Due to their choices, including their focus on personalization, Spotify is set to grow to $33.97 billion USD by 2027.

Coca-Cola

The ‘Share a Coke’ campaign was a huge success for the brand due its heavy reliance on personalization. By adding popular names, they encouraged consumers to find bottles with their names, or the names of their loved ones.

It sounds simple, doesn’t it? But a lot of work went to make this campaign happen. According to the brand, it required:

150 submissions to their marketing approvals committee
25 risk assessment meetings
4,000 hours of talking to Coca-Cola stakeholders individually
225 trademark searches
40 hours to get the right red
2,302 original artworks
4 weeks to find a machine that could print the names on the cans
303,669 point-of-sale pieces
5,287 words they didn’t want on the cans

By doing this, Coca-Cola fostered a personal connection with buyers, leading to a boost in sales and massive social media sharing. All the hard work paid off.

In short

Personalization in digital marketing is not a luxury but an absolute necessity. Companies like the ones mentioned in this article really showcase just how powerful personalization in marketing can be.

Ultimately, successfully implementing personalization strategies can set you apart from your competition, and help you to build those all-important relationships with customers to drive growth.

We touched briefly on AI and one thing’s for sure: personalization would be 1,000x more difficult without it.

If you’re looking to save some time and money but still get the results you want out of your marketing, check out our ebook “From data to dollars: How generative AI transforms revenue, digital, and growth marketing” – and learn how to optimize your campaigns.

The importance of personalization in digital marketing (with examples)

Teresa Garanhel