Instead of approaching personalization as a complex project, breaking it down into stages can help brands effectively integrate personalization into their digital strategy and see measurable results at each stage.

Personalization has emerged as a key priority for brands looking to deliver meaningful experiences to their consumers through digital channels. By understanding your consumers, and personalizing their online experiences with relevant content and recommendations, your brand can encourage consumer loyalty and maintain a competitive edge.

Many brands approach personalization as complex multi-year projects, which means that it takes many months or even years to see results. While delivering personalization is quite complex, breaking the journey down into stages can help brands effectively integrate personalization into their digital strategy and see measurable results quickly and at every stage.

Why Personalization is Complex

Implementing personalization has been proven to improve marketing spend efficiency from 10 to 30 percent and increase revenue by 5 to 15 percent. For example, when BevMo!, the largest alcohol retailer in the US, personalized experiences across their website, email, and SMS campaigns, they generated $125 million in new sales revenue, increased ecommerce sales by 5.3 percent during the pandemic, and improved year-over-year sales by 51 percent.

These kinds of results are hard to ignore and difficult to scale by any other means. To deliver personalization like this, it’s important to have a strong foundation of data science and to understand what personalization means.

Personalization is not limited to segmenting your audience further (i.e the more audience segments that marketers can create, the more personalized the experience can be). While this is a good starting point, true personalization comes from being able to personalize experiences for individual consumers at scale. It’s difficult to go from demographic segmentation to this level of personalization, but there’s many things you can do along the way. For example, dynamic segmentation allows you to leverage real-time behaviors and historical data, as well as to understand changing consumer behavior. This sets up the foundation for personalization at scale.

Aside from building personalization capabilities on strong data science foundations, the key to achieving personalization at scale is understanding where you are on the personalization journey and choosing the right tools to help you progress. Marketers can’t analyze data and personalize consumer experiences at scale because it would require too much manual curation  — that means using AI-driven solutions that can find patterns humans can’t. This frees up marketers to focus on what’s important –  how to act on insights quickly to meet consumer needs instead of spending their time parsing through rows of data. In order to build engagement and connection, it’s important to use your data effectively to give consumers exactly what they are looking for at the right time.

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Personalization is a Journey, Not a Project

With tech giants like Amazon, Google, and Netflix using “predictive personalization” to provide their consumers with next level digital experiences that are timely and relevant, brands are anxious to replicate these efforts. But these kinds of personalization capabilities are not built in a day. By starting simple, like making sure you’re using data effectively, or delivering simple personalization that optimizes consumer journeys, eventually it is possible to deliver more dynamic and predictive Netflix-like experiences for your consumers that help you connect at intent-rich moments.

Every brand is at a different stage of their personalization journey. In fact, even different brands within the same company might be at different places depending on their budgets, as well as the amount of data they have access to or the tools they use. What is important is understanding where you currently are on this journey and where you would like to be eventually. Breaking it down from here can help ensure that progress is being made quickly and consistently.

Brands who approach personalization in this way are able to deliver experiences that are scalable and improve their marketing ROI. It’s also much less overwhelming in terms of execution. At each stage, marketing teams should identify key business goals and challenges to overcome. This makes it easier to identify different ways to achieve these goals and possible solutions to challenges at each stage.

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The Three Stages of Personalization

While the personalization journey isn’t necessarily a linear process, the three main stages are:

1. Collecting data and extracting actionable consumer insights

Personalization can help brands make the seemingly intangible aspects of consumer behavior more tangible, like changing interests or the impact of external events and time on purchase decisions. That’s why effective personalization is built on a strong foundation of data science practices. It’s not just important to have data, but equally important to collect, tag, and manage it in a systematic way so that actionable consumer insights can be extracted.

At this stage of the personalization journey, marketers might want to ask themselves:

• What are the business objectives that personalization can help us achieve? What are some questions that I need answered about my consumers? This helps identify actionable insights to build use cases for personalization.
• What data is required in order to achieve these objectives? This data could be consumer behavior on specific marketing channels, consumer demographics, or external factors like seasonal trends or location.
• What is our current technology stack? What data do we already have access to and how is it tagged and managed? These questions can help you make decisions when exploring the use of technology-driven personalization tools.

2. Optimizing the consumer journey with simple personalization

Once you’re successfully collecting and systematically tagging data, it’s time to figure out how to put the data to use. At this stage, brands should identify specific use cases that can help them optimize consumer journeys on one or more marketing channels. This is what we call simple personalization, because it allows you to purposefully curate digital experiences for your consumer in a small, but measurable and impactful way.

When you reach this stage, marketers  should be thinking about:

• What are our short-term goals related to digital consumer experiences that optimization can help us meet? Figuring out these goals can provide an important foundation for continuously learning about your consumers and finding opportunities to meet their needs.
• Another benefit of optimization is that it allows you to focus on certain aspects of the digital experience while still having rules when curating experiences. What are some guidelines that you might want to create for digital experiences at this stage?

3. Enabling predictive and dynamic personalization at scale

Predictive personalization is the final stage of the personalization journey. At this stage, personalization isn’t just limited to certain segments of your marketing channels, but it is the backbone of your digital channel.

For example, if simple personalization is optimizing a “You May Also Like” carousel with product recommendations, predictive and dynamic personalization enables your entire website to adapt to individual consumers’ changing preferences and behaviors. This means every consumer that visits your website could experience a different combination of layouts and content that is relevant to their needs at that time.

AI-driven technology plays a vital role in delivering this level of predictive personalization at scale. Once you have the appropriate technology stack in place, you should be well equipped to use dynamic content across channels like email, SMS, and your website. Again, the key to success is tying personalization efforts to specific business goals and having the answers to the following questions:

• What business goals will personalization help us achieve? Realistically, there should only be two or three prioritized goals that tie into personalization. Technology can only help when you understand why you are using it.
• What are the non-negotiables in terms of the brand experience you want to provide consumers?
• What are the different marketing channels you want to personalize for consumers? At this point, predictive personalization should work across channels, but it is important to identify where consumers cross over.

AI-driven personalization not only captures opportunities for conversion and engagement that are impossible for us humans to see — it also helps you create relevant, meaningful relationships with your consumers. If you understand where your  brand is on the journey to personalization and approach it in a systematic way, in digestible stages rather than a complicated multi-year project, you can take big steps today towards improving the consumer experience and driving ROI.

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