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The What, Why, and How of Dynamic Web Store Personalization

by | Mar 22, 2022 | eCommerce

Intro to Personalization: Journey before destination

The journey IS the destination! Maybe it sounds cliché, but it is sound advice for life – and business projects like these.

When it comes to dynamic web store personalization: it’s a journey. Your team doesn’t need to optimize and personalize all attributes of your website – and omni-channel touch points – from the get-go. Rather, you simply need to just get started, and then you can iterate over time. 

As you learn, you can be creative in layering on more valuable and intricate personalized optimization tactics. 

Referencing a white paper by International Data Corporation highlights some important facets of personalization for us to consider:

“The idea of personalization should influence everything about the customer relationship and the practice of marketing. With the changes in iOS and Android advertiser IDs and [cookie deprecation], marketers need to rethink their data relationships with their audiences. The era of data as a commercial entitlement is ending, and the era of earning identity with value is dawning.” 

“Earning identity” can be done when your brand provides valuable products and resonates with consumer values, but it can also come from connecting to that user in personal ways through web, digital-communication, and non-digital touchpoints.

This guide will walk through website personalization from start to finish. But remember that it’s a journey, and it should be fun!

Check out the full guide here: How to Dynamically Personalize Your Shoppers’ Website Experiences

What is website personalization? 

Generally when we personalize, we are designing to meet someone’s individual requirements or preferences. 

Website personalization is the act of enabling your website to be customized and changed based on the person who is looking at your web page. Simply put, you update web components to match the current visitor.

This means we are recasting elements of the web page(s) to represent a particular person’s known – or predicted – preferences, interests, style, values, wishes, demands, and beyond. 

Applying personalization to web stores has actually become rather ubiquitous – given it is relatively easy to implement and has well-recognized business impact.

How does it work?

Website personalization is actually implemented via the interaction of multiple tools. Some act as data collectors; some store information; some let you customize different visual components; and at the core you have the personalization engine itself – the brain.

The technology uses either rules-based logic or a machine learning engine for decision making, based on the website visitor profile. For each individual, the personalization tool will rework a website component – such as some call to action text, or an image on your landing page. 

The software uses back-end processing to determine what version of the website experience or content should be displayed for that profile. Once that determination is made, the code pushes that content onto your website – but only on that specific person’s web browser.

This personalization determination comes from logical processing over data sets – often internal to your company’s history. It can also come from external, 3rd party sources for certain types of optimization.

The data contains the information about different customer profiles, and how each profile correlates to preferences, affinities, past purchases, products, messaging, and more. 

These correlations are the epicenter of personalized web experiences.

Personalization can be done in a somewhat manual way: creating custom content versions, manually analyzing the data to split the customer profiles into segments, and then assigning each segment to a content version that will get applied for those profiles’ web visits.

However, typically it’s automated: software automatically processes and determines the best content, products, or CTA to put in front of the customer to maximize the likelihood of achieving the outcome you want. Typically those outcomes are: clicking, filling lead forms, viewing more products, converting with higher AOV, and becoming repeat customers. 

Why does it work?

Simply put, most people prefer to be treated as individuals. By tailoring content to each person instead of treating all people uniformly with generic messages, you give them an experience that makes sense for who they are.

While that is more of a philosophical take, a more tactical explanation would be as follows. 

Individuals do indeed have specific preferences. If you display a message or product that they care about – versus one that doesn’t interest them – their attention and engagement is more likely to be captured.

However, there’s another way to answer this question of “Why does personalization lead to better results?” 

This idea is that… we don’t know why it works, but we do know that statistically some inputs lead to some outputs very reliably. A simple example might be: almost every time I do a short workout before bed, the next morning I am not hungry for several hours. 

There’s likely some kind of biological or physiological reason for this (which is much more dependable than the psychology of human cognition around eCommerce purchasing preferences). However, the point is: I don’t need to know “why” – I just know that I can reliably plan tomorrow’s breakfast without a problem if I know that I’ll workout tonight.

Now, if we’re planning to turn many types of different website shoppers into happy customers, it would be foolish not to use natural heuristics and human intuition to select the content that will lead to expected results (for example: matching gender identity to the gender tag on clothing).

But we can and should also analyze the data to determine what inputs predictably create those good results. (A silly but realistic example: if my website’s background is red instead of blue, I get more purchases. I don’t know exactly why, but I can use that correlation to optimize my website.)

The benefits of website personalization

At this point it’s probably relatively obvious: personalization supports better results.

The primary metrics that benefit from web optimization toward specific individuals or granular audience segments are as follows. 

Improved Bounce Rates

When customers land on your website, instead of seeing a generic message and products, they will see content that is statistically more likely to engage them. As a result, more of them will stay on the page to poke around and engage with that content instead of bouncing!

Improved Conversion Rates

That personalized experience is engaging more shoppers, which will lead a larger percentage of the website visitors on your store to: click through to different relevant pages you are recommending; fill out forms for call to actions you predicted they would like; and buy more products that you suggested they might enjoy! 

Improved Revenue

More purchases from more engaged shoppers means more dollars in the bank!

Improved Repeat Customers, Loyalty, and Retention

With a personalized website, you are also able to provide the known customers with more of what you know they like. Previous purchases can be reflected on the website with a call to action for re-purchasing, similar items, or even the simple reference that you know what it is they like. Beyond just web personalization, known customers can be emailed or texted with personalized offers to generate repeat purchases and loyalty.

Improved ROI for Web Traffic (Ads, etc)

When more of your paid, ad-driven web traffic is converting into more leads and purchases: you are growing the revenue generated across those sources. So the ROAS for your Snapchat, Instagram, or Google Ads spend is going to grow – making for a more efficient use of ad dollars.

Improved Lead Quality

Leads that fill out forms or show interest will be the ones that were more engaged by the content you personalized for them. Because you have some data about their profile and your effort increased their likelihood to become a lead, they will also more likely become good customers  that resonate with your products, brand, or messaging.

Improved Customer Experience

The customer gets to experience content that is more relevant. It’s more engaging, they like what they see, they feel more affinity towards your brand for giving them customized content. This isn’t as quantitative – but is a benefit nonetheless!

Personalizing your website: getting started and defining strategy

1. Set Goals! (It always adds value)

It’s stated as the first step in any plan you read about… but truly defining your goals and overarching objectives is extremely valuable. It helps ensure you and your team are approaching the problem, projects, and tasks from the same shared understanding.

Not only does this involve setting the high level description of the mission and aim, but here is where you can discuss what metrics and KPI’s you’ll look at most heavily. 

Don’t be afraid to spend some time writing out more in your “Goals” section. It never hurts to have brainstormed about purpose and priority

2. Understanding the tools and technology

Various categories of marketing technology are involved in personalization. Let’s discuss the core.

Data aggregation and analysis tools are a category that allow you to centrally store, query, and visualize your data. This can be helpful for understanding your results, segmenting your audience, and determining correlations that lead to good results.

A customer data platform (CDP) or other data warehouse can make it easy to activate all that information by situating it as pre-processed, combined, and primed.

Intelligence engines – focused on personalization – will be the core powerhouse behind the calculations and predictions that generate your personalized experiences. 

In these systems, data is aggregated and run through machine learning models, statistical simulations, and live experiments. This will literally generate the output that you can use directly to dynamically update your website.

Jarvis ML is an intelligence engine powered by machine learning with infrastructure to deploy extremely fast and accurate personalization at scale. 

Your website is the vessel where that output is deployed of course. Other core business systems are also involved, but we’ll look at those under the next section.

3. Understanding data

The data your org creates and stores comes from a variety of sources and systems. To do website personalization, the clear priority for data is website traffic and activity.

Google Analytics – or a similar web analytics tool – is the primary source for extremely usable information. It is especially useful for any anonymous web traffic – which makes up a majority of your daily site visitors. Check out this guide to learn about what data can be used to optimize conversions for those unknown shoppers. 

Your eCommerce platform – Shopify, Woo Commerce, BigCommerce, Magento, Commerce Cloud, etc – is the other core data source. This will have all of your product SKUs and their attributes. It should also keep a record of transactions and the metadata surrounding those purchase events. It may also have customer information stored, although full historical customer data is a separate category that you should utilize.

A CRM is extremely valuable to find those deeper correlations about customers from multiple touchpoints, purchase history, communication history, stored surveys, and any other centrally aggregated information. If you use a separate CRM apart from just the eCommerce platform, it’s immensely helpful to connect more robust data to the top-of-funnel interactions.

Beyond these core systems, some personalization engines will allow you to integrate additional data sources to feed more data in for further optimization calculations. For example, your marketing automation platform and email service provider – which can help to provide information about customers who engaged with your campaigns.

4. Assemble the Team

It’s hard to go at this alone, so work with others and ensure someone takes on the role of project manager.

Ideally there are a number of folks involved:

  • Strategists: Directors, Managers
  • Creatives: Designers, rest of team
  • Marketers: Marketing managers, digital optimization, eCommerce associates
  • Technical: Data analysts, data scientists, web developers
  • Top-down Buy in: Executive leadership sponsors

You don’t need the whole company, but with a more complex eCommerce operation, extra hands on deck go a long way to ensuring successful deployment.

5. Brainstorm website components you can personalize

Check out this guide on 8 website components that you can personalize to each shopper.

This should be a fun experience: think of as many areas and aspects of your site that can be personalized. Brainstorming is about volume: quantity over quality at this stage!

Then go a step deeper into how you might personalize those elements for users of different categories. Why would a certain shopper like that personalized message? 

Take good notes on where you can apply leverage. Ideas surface and change quickly over time, so keep a log of what comes to mind – ultimately you’ll have a great list of options to work with moving forward.

In this section, also build out some outlines for the shopper journey throughout your website. How should it look for different audience categories? Make sure to refer back to these outlines as you start executing to ensure the personalization you deploy is also mapping back to an intentionally designed experience.

6. Create personalized content

This is a necessary step for some types of personalization, but not necessarily others.

For example, doing hyper-personalized product recommendations on your landing page or product detail page doesn’t require creating new content. Same goes for re-ordering navigation quick-links or doing search-bar preview predictions. 

In those examples, the “content” already exists: the products in your database, or the navigation hyperlinks and buttons on your website.

However, if you want different messaging and wording for separate call to actions – these different versions will need to be defined, designed, and written out. This will be a process that is supported by automation – so don’t worry about writing 10,000 versions of the same CTA!

It’s conceivable that certain personalization software can help to automate most of the content generation, at least for many core website components. 

An example of this “totally out of the box” use case would be with Google Ads, where you are able to give over control to their system. You provide the Google Ads platform your goals, your landing page URL, and maximum cost per acquisition; in return Google will not only target the right audiences, but also create the ad copy itself based on materials from your landing page – generating multiple versions to test and iterate. Google has powerful machine learning capabilities!

7. Audience curation

Generally speaking, understanding your audience is super important – and should be part of the process of defining what personalization elements match what types of customer profiles.

One big takeaway is simply understanding what attributes make up your customer base. Who are the shoppers that buy from you and are loyal to your brand? What types of profiles come to your website and then drop off, versus fill a lead form? What types of attributes should you prioritize your personalization efforts around?

While the audience curation process can be important for exploration and understanding, it also acts as a selection process to map audiences to messages. However, mapping person-to-message manually in cohorts will require some additional steps prior to moving forward: further audience segmentation and tagging, plus logic-building exercises. 

We don’t cover the manual path here. With an automated machine-learning approach the system will do this granular mapping work as part of the core functionality. This is where those correlations are really starting to do meaningful work.

8. Deploy and iterate

You’re creating a dynamic web personalization experience powered by an intelligence engine. At this point, you plug in the data sources; upload personalized content; input your goals and preferences; and select what type of personalization tactics you want to deploy.

The system will analyze, test, train, and then launch on your website. The “training” process is where your historical data is used to determine the complex underlying relationships between all of the customer profiles, product attributes, website interactions, conversions and purchases. 

The statistical modeling works to understand what type of personalized content has the highest probability of conversion, maximizing LTV, or other desired goals.

After training, your store will have various components being dynamically tailored to the viewer – live within your website! 

With each instance of personalization (which is: for every single website visitor), the system ingests new data: about the shopper, their browsing behavior, and what they ultimately do or don’t do. This new data gets factored into the models so that your personalization engine is learning continuously: testing high-probability hypotheses and iterating based on new findings.

Challenges facing personalization efforts

While a breakdown like this may make the process sound easy, that’s not to say there isn’t work and significant thought and planning involved.

Not only does it take effort, but there are some historical challenges to making personalization like this work across websites: quickly, accurately, and at scale. I’ll list a few of them below and the current status of how those challenges are being confronted.

Challenge: Data was siloed and difficult to connect into a journey from top of funnel to bottom.

There are plenty of methodologies and tools available to support modern data needs: piping it from one place to another; joining higher-funnel website interactions with CRM touchpoints and repeat transactions; and priming and cleansing data to be used by an intelligence engine.

This is the easiest to solve nowadays. Not only do full platforms exist for aggregating customer data, but personalization engines can also natively ingest data from any source.  

Challenge: Heavy technical (and non-technical) resources were needed to develop the personalized strategy.

In a perfect world, everyone would know how to code dynamic websites. Instead, complexities that previously required a developer are built in intuitive UI’s that non-engineers can work with. Website personalization has evolved the same way.

Further, it’s no longer necessary to have in-house data scientist to define statistically relevant audience cohorts to target and optimize. That can be done with machine learning models.

While a strategy still needs to be designed and implemented, the heavy lifting is no longer necessary.

Challenge: Combining a high volume of prospects +  tons of data generated every minute + changing preferences = scalable, robust processing power and infrastructure.

This problem is always underpinning the complex, large-scale implementations we want running – especially over the internet. But it’s a widely experienced challenge and it is being addressed through more foundational work across many businesses. 

It’s also being directly supported with the build-out of some intelligence engines. For example, the Jarvis ML platform infrastructure is being designed by the same group that supported the infrastructure for deploying machine learning at Google. The point is: a strong technical foundation could be a challenge, but it’s being addressed. 

Challenge: Technical architecture must support easy and direct integrations between systems: to share & process data, and to deploy the intelligence.

In the past it was harder to get systems to work together, but most tools are accessible bi-directionally through API to send and retrieve information for easy processing and sharing. 

Your data sources need to provide historical and real-time data to the personalization engine tools. Those in turn need to be accessible by your website and other systems used for optimization or tracking. 

This necessity is now a business standard!

Wrapping up website personalization, for now

The effort of personalizing a website should be a bit clearer now, after outlining some of the building blocks and considerations.

If you and your team aren’t already prioritizing custom tailored experiences for your shoppers, it’s a topic worth exploring further. 

If you’re already making considerable progress in personalizing, then you’ve likely started facing some of the newer challenges that come with this type of growth.

While there is a lot more to dig into about personalizing web experiences, we’ll leave those for future guides. 

Other relevant topics may include:

  • The myriad types of data that are best used for personalization
  • Different creative ways to personalize your website and other marketing touch points
  • The role of A/B testing during a 1:1 hyper-personalized website experience
  • Facing predicted challenges for the future of personalization: from cookies to consumer sentiments 

By combining a thoughtful strategy with the right set of data sources and personalization tools, you can build very compelling experiences for the shoppers that you work so hard to earn. 

It makes sense to prioritize conversions, given how expensive website traffic is. The best ways to do so are through brand building, high quality products, and digital experience optimization. Optimizing through personalization is just one tactic; but it’s becoming business critical to keep pace with consumer preferences.

Check out the full guide here: How to Dynamically Personalize Your Shoppers’ Website Experiences

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