A Complete Guide to Personalization Engines

The modern-day consumer expects some level of personalization when they interact with a brand. In fact, 80% of consumers say that personalized experiences are at least somewhat important when making purchases. For example, they might want brands to remember how long they’ve been a customer or when they last bought a particular product—or, at the bare minimum, receive emails that address them by name.

However, in order to keep up—or exceed expectations—brands need the right technology to scale this level of personalization. The truth is that those basic levels of personalization aren’t going to be enough to win brand loyalty and stand out in competitive markets. Brands need to go above and beyond to differentiate their customer experiences and really engage with their audience to gain their trust and their love. Doing this requires collecting the right data in an ongoing way and using it to personalize for individual customers on a 1:1 level.

For brands that sell anything, a personalization engine is essential for the growth of their business and in this article, we’ll explain what personalization engines are, their benefits, how they work, and what they can do. We’ll also show some real-life examples of a personalization engine and customer engagement platform (CEP) at work to demonstrate the fantastic results that can be achieved when this technology is introduced.

Key topics we’ll cover:

• What is a personalization engine?
• How does a personalization engine work?
• Types of personalization
• Eight benefits of a personalization engine
• Real-life examples of personalization engines at work
• FAQs
• Final thoughts
• Featured resources

What is a personalization engine?

A personalization engine is a piece of software that businesses use to collect and analyze data about their customers to create a personalized customer experience. A good customer engagement platform—especially one with out-of-the-box personalization tools powered by artificial intelligence (AI)—would be a highly-effective personalization engine.

A personalization engine typically gathers behavioral information, such as purchase history and on-site interactions, alongside demographic information, brand loyalty data, and information from other departments such as the customer service or sales teams. The higher the quality and the volume of the data a personalization engine collects, the more it is likely to be able to leverage that information, resulting in better outcomes. It sounds like a tall order, but there are things brands can do to help automate the process. By incorporating AI, personalization engines can synthesize large amounts of data and make intelligent outputs that improve outcomes.

For example, Braze AI Item Recommendations uses artificial intelligence to create personalized recommendations based on purchase history and individual attributes. The recommendations can be seamlessly integrated into Braze-powered messages and help to personalize product recommendations at scale, delivering recommendations to the customers that they are most likely to resonate with. This engine can surface the next best product, content, or item to every customer—at scale—helping your customers find more value from your brand.

Beyond that, a tool like Braze Personalized Paths allows marketers to match each customer with the message copy, creative, channel, offer, etc. that they’re most likely to engage with in a given journey—all with a simple toggle.

With the right customer engagement platform, brands can automate personalizations, allowing their teams to learn more about their customers and then take action on that data to increase engagement, revenue, and loyalty.

How does a personalization engine work?

A personalization engine continually learns from the data it collects and the human behaviors it is analyzing. It does this, in part, with AI or other advanced automation capabilities. It then suggests relevant content or predicts a user's next actions so marketing teams can create relevant content to match the customer’s needs.

A personalization engine can know when a customer is likely to make a purchase, and can send them the right message at the right time on the right channel, encouraging them to finish the transaction. It also can tell when a customer is likely to churn, and catch them before they do with messages that will resonate with them and encourage them to stick around.

For example, with personalization engines like BrazeAIᵀᴹ, brands can:

• Personalize experiences at scale
• Recommend the right items for every customer
• Automate routine tasks and drive greater value
• Feel confident in each campaign they send
• Test and optimize every step of every customer journey

With the right suite of AI tools, marketers can work smarter to craft, scale, and adapt memorable experiences that foster stronger consumer/brand relationships. By using AI to leverage comprehensive first-party data to tailor compelling content, custom recommendations, and unique journeys, brands can build a much deeper relationship with their audience and gain their trust and loyalty.

Types of personalization

When we talk about personalization, we’re also talking about relevancy, and not every type of personalization is relevant to all customers. Indeed, the very idea of personalization means that it’s customized and not a one-size-fits-all approach.

Let’s look at six of the most common types of personalization and when brands might use them.

1. Name-based

The one we’re all the most familiar with. When we receive a message that says “Hi John”, or “Hi Laura”, instead of just ”Hi”, or “Hi customer”, it feels more personal. It is however, the basic level of message customization—and, unfortunately, many brands don’t go much further. This is the least that customers expect and there’s so much more brands can offer.

2. Location-based

Using the physical location of a recipient, this type of personalization can target customers in a particular place or region (e.g. California or London’s Hackney neighborhood), without bothering other customers that the message might not be relevant to. For example, an offer that only applies to people at one store location can be communicated to those nearby and not those too far away for it to be of use.

3. Language-based

An essential type of personalization for global companies where messages can be sent in different languages. All the variants can be added and then, for example, an English version sent to English speakers and a French version to French speakers. It’s a great way to keep offers from getting lost in translation.

4. Event- and attribute-based

Each customer is unique and their preferences and behavior are individual to them. Event- and attribute-based personalization allow brands to add other customer-related attributes to their messaging. For example, knowing their shoe size may trigger a push notification when a certain size pump is back in stock. Or maybe they’ve abandoned a cart with the same product three times this week, so the brand can let them know that it’s on sale or offer a one-off discount.

5. Dynamic content

When brands want their messages to be responsive and adapt to external events or something outside of your data or control, dynamic content is a dream come true. Say there’s a storm on the way for a certain part of the country and brands want to be able to pull in that information so that the messages they send are more suited at that moment. Dynamic content—or Connected Content as we call it—allows for power, flexibility, and complexity in their communications.

6. Delivery time

High-engagement times feel less intrusive and this type of personalization means brands can send messages at times when a customer is more likely to open them. Each user can be different, so that might mean one person gets a given message on their morning commute at 8:15 am and another when they’re home for the day at 8 pm.

Benefits of a personalization engine

Personalization is no longer a “nice to have” in business. It’s a necessity. When done right, it can uplift the average revenue by 10-30%, increase brand engagement, and support stronger customer relationships. There are so many benefits to working with a personalization engine and they each have an impact on the bottom line.

Here are eight advantages to using a personalization engine:

1. Maximize profit with intelligent recommendations

AI makes personalization possible at scale. It can predict customer preferences and suggest relevant and timely solutions, sometimes before the customer even realizes they need them. AI helps brands to truly understand their customers and provide for them in the best way possible.

2. Drive better experiences with your brand

Whether it’s email, text message, Whatsapp, in-app messaging, or push notification, being able to talk to customers through various platforms will give brands more opportunities to reach them. But being able to send them relevant messages on the right channel at the right time is particularly impactful. For example, a location-based push notification for a special offer when their customers are near their store represents true personalization and creates a stronger bond with their customers.

3. Unlock recommendations that are directly integrated in your tech

A personalization engine, when paired with the right personalization tools and technologies will not only collect and analyze customer data, but do so in a continuous manner and track performance. This means that data is up to date when you need it—so making decisions and adjusting your marketing plans becomes a whole lot easier. Campaigns can be added, amended, and designed with access to the latest information to ensure they are particularly relevant. They can be sent to different customers to support increased relevancy and this can all be implemented quickly and efficiently.

4. Break down team silos to improve efficiency and performance

A common gripe of modern marketing teams is that departments are working in silos—each one with its own set of data and goals. A personalization engine helps to bring all of the information together and, when used as part of a customer engagement platform, brings everything into one place for use in different ways and for different goals. This creates a single source of truth that can support a more aligned working process, and also leads to more cohesive experiences for customers that enhance brand equity.

With AI and advanced automation, the elements that would take a long time if done manually can now be done in an instant and at scale. This ability to act quickly on real-time data is one of the stand-out benefits of a personalization engine.

5. Drive revenue with personalized messages to customers

Personalization engines allow brands to create thoughtful, relevant messaging that provides real value to the people they’re trying to reach. Ineffective personalization can carry a heavy cost. Research by Accenture found that companies worldwide are losing a collective $1 trillion in annual revenue because their communications are not consistently relevant enough.

6. Creating more engaging customer experiences

Finding new ways to keep an audience engaged and successfully encouraging them to stick around is hard. A personalization engine enhances the customer experience. When customers feel they don’t have to try to get a brand’s attention or that they can pass between platforms and channels with ease and without the loss of relevancy or detail, their desire to come back increases.

7. Optimize customer journeys to drive the highest likelihood of conversions

Key moments in the customer journey can be automated to create a highly personalized experience. Using a personalization engine and integrated tools, these key moments can be optimized. With Personalized Paths, for example, marketers can easily match each customer with the message copy, creative, or channel they are most likely to engage with at any step in a given journey. Marketers can also leverage Braze Canvas to build dynamic and responsive customer journeys—without having to write code. This is a way of orchestrating and visualizing the conversation they’re having with each one of their customers.

8. Drive next-best actions

With a tool like Braze Predictive Suite, brands can automatically identify users that are at risk of performing any future action—such as when they churn—and engage them before it’s too late. Identifying not just when it’s happening but how and why it’s happening means that brands can take a proactive approach to personalizing their messaging and help to turn the tide.

Real-life examples of personalization engines at work

Now that we’ve explored what a personalization engine is, as well as the enhanced benefits of a full customer engagement platform, let’s look at how four different brands utilized some of those benefits to drive excellent results:

• With Predictive Insights on Likely Buyers, 8fit Improves Conversions and Customer Engagement
• NZME’s OneRoof Boosts Email Engagement by 23% With Braze Intelligent Timing
• How Majid Al Futtaim’s SHARE Rewards Programme Did Even More With Their Direct Communications
• Pizza Hut Adds Key New Channels and Drives a 21% Increase in Revenue With Machine Learning

FAQs about personalization

Will a personalization engine help with customer retention?

Yes, a personalization engine can improve customer retention rates. Using improved communication, targeted recommendations, and other creative messaging campaigns, brands can use personalization to encourage customers to return and make additional purchases and interactions with them.

Does a personalization engine work for any type of business?

Personalization can benefit most businesses, but the impact it has really depends on what your goals are and whether you have customers you need to regularly interact with. This may determine how much or how little personalization you use—but, as a general rule of thumb, the better you know your customers, the more you’ll know what they want and need. The more you understand that, the easier it will be to give it to them. This will help you to attract new customers and retain old ones.

Can personalization engines work across multiple platforms

Yes, but for the best results, you’ll want to look at a customer engagement platform that can pull in data from multiple channels and house it in one place. That way, you won’t have to juggle multiple tools to do a single job and can reduce the risk that you’re serving up fragmented experiences to customers.

Final thoughts

Personalization engines, especially ones powered by AI, play a vital part in providing better experiences for your customers. Using a personalization engine within a customer engagement platform, brands can truly leverage the power of their data, seize every opportunity, and optimize their campaigns for dynamic and personalized experiences at scale.

A brand looking to make the most of the information they hold and keep up with the demands of today’s savvy consumer should embrace new technology and take a future-focused mindset to not only give customers the experiences they want and need, but also to provide what they don’t even know they need yet. With BrazeAIᵀᴹ, brands can engage real customers with artificial intelligence, recommend the right items for every customer, and automate routine tasks to drive greater value.

Want to start seamlessly tailoring recommendations for each customer, unlocking sophisticated personalization and prediction at scale, generating authentic content, and driving the most high-value actions from each customer? Check out BrazeAIᵀᴹ.

Featured Resources

• 2024 Global Customer Engagement Review
• Personalization: The Key to Your Digital Transformation
• The Nuts and Bolts of Braze Connected Content
• The Power Behind the Message: Effective Personalization