Featured Image

September 2, 2025

Adobe Target in Single-Page Applications: Real-World Challenges and Solutions

Many of the websites you use every day, for example Gmail, Facebook, or Twitter, can feel so seamless, fast and smooth. You click, and content just appears, without the whole page blinking and reloading. That's the magic of a Single Page Application (SPA)! These web experiences are designed for speed and fluidity, but they introduce unique challenges when it comes to personalization tools like Adobe Target.

In this post, Santosh Kumar, Principal Consultant at Accrease, shares two real-world challenges that we faced when implementing Target in an SPA, and how our team developed scalable solutions.

What's an SPA?

Imagine a website that's not a series of separate pages, but rather a single, smart canvas. When a user first visits, the browser loads the essential HTML, CSS, and JavaScript. After that, interactions update only the parts of the page that change, without reloading the full page.

Why are SPAs so popular and powerful today?

Faster performance: Because only small chunks of data are exchanged and rendered, SPAs feel incredibly quick and responsive. This results in a significantly faster user experience.

Smooth navigation: The absence of full-page reloads eliminates the jarring "white flash" and makes the navigation feel continuous and fluid, almost like using a native mobile application.

Enhanced Efficiency: With less data being transferred between the server and the client, SPAs reduce server load and bandwidth consumption, leading to more efficient performance overall.

Modern Development: Developers leverage powerful, cutting-edge JavaScript frameworks like React, Angular, and Vue.js to build SPAs, making the development process more organized and the applications more robust.

For the user, this means a fluid, modern web experience. But for personalization platforms like Adobe Target, it breaks the traditional pattern of reloading and re-evaluating content at each navigation.

The challenge with Adobe Target and SPAs

Adobe Target is a leading personalization and A/B testing tool that empowers businesses to deliver tailored content and experiences to their website visitors. It's all about showing the right message to the right person at the right time.

However, SPAs present a unique challenge for traditional personalization tools. Normally, when a user navigates to a new page, a "hard reload" occurs, and Adobe Target's main script (alloy.js, used for Adobe Web SDK) is re-executed, triggering a new "mbox call" to check for personalized content. In an SPA, this only happens on the very first page load. After that, all subsequent navigations are "soft reloads", dynamic content updates without a full page refresh. This means Target doesn't automatically get the signal it needs to re-evaluate and deliver new personalized experiences.

To address this, Adobe Target uses a concept called "views." A view is simply a named state or screen within your SPA. Think of it like a virtual page, even though the browser isn't actually reloading. For example, "homepage," "product-details," "shopping-cart," or "checkout" could all be defined as distinct views. When a user transitions to a new view, we manually tell Adobe Target, "Hey, the user is now on the 'product-details' view!" This manual trigger allows Target to deliver the appropriate personalized content for that specific screen, even without a full page reload.

Illustrating the "View" concept:

Picture from: Adobe Experience League.

Solving real-world scenarios with Adobe Target in SPAs

While the "views" concept is foundational, we encountered a couple of significant real-world challenges when trying to implement Adobe Target for more complex personalization scenarios in an SPA environment.

Challenge #1: Personalizing across thousands of similar pages (The "Marketer's Nightmare")

Take a large hotel booking site. It might have thousands of unique hotel detail pages, each representing a different property. In an SPA, each of these pages would typically have its own unique "view" name (e.g., "hotel-london-view," "hotel-paris-view," "hotel-tokyo-view"). Now, imagine a marketing team wants to change a small, universal piece of text, perhaps a call-to-action button or a promotional banner, that appears on every single one of these thousands of hotel detail pages. If they had to set up thousands of individual personalization rules in Adobe Target, one for each unique view name, it would be an incredibly time-consuming, impractical, and unscalable "marketer's nightmare."

Our approach: The generic view name trick

To solve this, making personalization scalable, we implemented a generic view strategy. Instead of sending unique view names for each individual hotel detail page, we sent a single, generic view name (e.g., "hotel-page" or "en: hotel page") for all hotel detail pages. This simple yet effective "trick" means marketers only have to set up one personalization rule in Adobe Target for the "hotel-page" view, and it automatically applies the desired change to all thousands of hotel pages. This dramatically simplifies campaign management and deployment.

Supporting marketers with our Accrease Custom Chrome Extension

Even with a generic view name, Adobe Target’s Visual Experience Composer (VEC) can still be difficult to use in SPAs. The VEC often defaults to the most recent view triggered, which may not be the one marketers want to edit.

To solve this, we developed a custom Chrome extension! This tool is extremely helpful for marketers working with SPAs. It listens for all the "view" names triggered by alloy.js on a page and populates them into a simple dropdown list within the extension. Marketers open the extension, select the exact view they want to work with (such as "hotel-page"), click "Activate." Then that specific view becomes visible and editable in Adobe Target's VEC.

The extension also includes a custom text box, allowing marketers to manually enter and activate any view name, even if it hasn't been implemented in the tag manager yet. This is incredibly useful for planning and setting up campaigns in advance. This tool significantly reduces manual effort, improves efficiency, and accelerates campaign creation for SPA-based sites, particularly for marketers who may lack in-depth technical knowledge.

Here is a closer look at the extension:

Here's a visual representation of how our Chrome extension “Accrease SPA Helper” helps:

Behind the extension:

Building such an extension may sound straightforward, but it requires both strong front-end development skills and a deep understanding of how Adobe Target operates. As Adobe Experience Cloud experts, we combined that knowledge with modern development tools to accelerate the process. AI-assisted coding helped us move faster, but it still took multiple iterations, testing, and refinement before we reached a polished and reliable solution. The end result is what you are seeing today, a tool that makes personalization in SPAs far more accessible for marketers, delivered with both speed and quality.

Challenge 2: Inaccurate goal tracking in A/B tests goal (The conversion discrepancy)

While personalization was now scalable, we noticed another issue: conversion tracking in Target wasn’t aligning with Adobe Analytics data.

For example, in an A/B test where the goal was a visit to the thank-you page, Analytics showed far more completions than Target.

The root cause:

After a thorough investigation, we pinpointed the problem. Since our site is an SPA, most users navigate between pages using "soft reloads." During these soft reloads, the main "mbox call" (which is crucial for Adobe Target to register user actions, evaluate goals, and track conversions) was not being sent automatically. Target was only recording a goal completion if a user happened to perform a full "hard reload" on the "thank you" page. This explained the small number of conversions we were seeing in Target compared to Analytics.

The fix:

We escalated this issue to Adobe Client Care, who involved their engineering team. After several rounds of analysis and communication, they confirmed our findings and recommended a crucial adjustment to our tag manager setup, specifically, the order in which Target calls were being fired.

Before (The problematic setup):

On Hard Reload:

  1. mbox call (decisionScope = __view__)
  2. view call 1
  3. view call 2
  4. view call 3

On Soft Reload:

  1. view call 1
  2. view call 2
  3. view call 3
    (No mbox call here)

As you can see, the critical mbox call was absent on soft reloads, preventing Target from registering goal conversions.

After (The solution: Adobe's suggested Fix):

The fix involved ensuring the mbox call was always present, even on soft reloads, and crucially, fired after all view calls.

On Hard Reload:

  1. mbox call (decisionScope = __view__)
  2. view call 1
  3. view call 2
  4. view call 3

On Soft Reload:

  1. view call 1
  2. view call 2
  3. view call 3
  4. mbox call (decisionScope = __view__) ✅

By adding the mbox call at the end of soft reloads, Target is now able to evaluate goal conversions correctly, regardless of whether the user navigates via a hard or soft reload. This simple but vital change ensures accurate conversion tracking for all A/B tests.

What does this mean for marketers?

SPAs deliver the modern experiences users expect, but they also require rethinking how personalization and testing are implemented. Our work with clients has shown that:

  1. Scalability matters. Using generic view names transforms personalization from unmanageable to efficient.
  2. Ease of use is critical. Tools like the Accrease SPA Helper extension empower marketers to manage personalization without heavy technical support.
  3. Accuracy is non-negotiable. Ensuring conversions are tracked correctly builds trust in testing results and enables data-driven decisions.

At Accrease, we bridge the gap between technical implementation and marketer usability. The result is personalization that’s not only possible in SPAs, but also scalable, reliable, and effective.

SPAs are here to stay, and personalization tools must adapt. By rethinking view management and conversion tracking, our team at Accrease has helped clients work the full potential of Adobe Target in SPA environments.

If your organization is facing similar challenges, we’d be happy to share our approach and explore how to make personalization more scalable and marketer-friendly in your setup. Contact us here

Acknowledgements

About the Author
Santosh Kumar, has more than a decade of experience in Digital Marketing and the Adobe stack. He holds more Adobe certifications than is humanly possible. When no one else can fix it, you call for Santosh.

A special thanks to Kurian George for his support in investigating these challenges, co-developing solutions, and ensuring smooth implementation. His expertise was essential in making these results possible.

Published by Santosh Kumar in Insights
Tags: Accrease, Adobe, Adobe Target, personalization, Single Page Application
Featured Image

August 20, 2025

Find Your Winning Products: Martine’s Adobe Analytics Rockstar Tips

We believe data should do more than inform... it should inspire action. That’s exactly what Martine, our Senior Consultant, set out to demonstrate at the latest Adobe Analytics event in London. With years of experience in Adobe Analytics, Customer Journey Analytics (CJA), and the Adobe Experience Cloud, Martine shared two practical tips that can help businesses quickly identify their top-performing products and focus their resources where they matter most.

In this short recording she shares the same tips she presented live at the event in London. Whether you’re an analyst, marketer, or business leader, these strategies will help you visualize performance more clearly and focus your efforts where they deliver the most impact. Scroll down and click the link to see the tips in action.

The Event:
The Adobe Analytics Rockstar session brings together industry experts, practitioners, and data enthusiasts to share best practices and innovative approaches. It’s a space where actionable insights take center stage and Martine’s session was a clear highlight.

Shortly on tip 1: Visualizing Product Performance with a Growth Matrix
Martine showed how a growth matrix, paired with a scatter plot in Adobe Analytics, can categorize products into strategic quadrants based on market share and growth potential. This visual method helps decision-makers quickly spot where to invest, adjust strategy, and align with long-term business goals.

Shortly on tip 2: Applying the 80/20 Rule for Revenue Optimization
The Pareto Principle, that 80% of results often come from 20% of efforts is a powerful framework for product analysis. Martine demonstrated how to identify the top 20% of products generating 80% of revenue using Adobe Analytics data enriched with Excel. This approach allows for targeted marketing and smarter resource allocation, ensuring your team focuses on the biggest drivers of business success.

Why It Matters:
These are practical frameworks you can integrate into your analytics workflows today. By combining strategic thinking with Adobe Analytics capabilities, businesses can cut through the noise and act faster.

Let’s Talk:
Want to see how these strategies could work for your business? We help organisations unlock the full potential of Adobe Analytics and the wider Adobe Experience Cloud, turning complex data into clear, actionable steps.

Get in touch with us today and start finding your winning products in minutes.

Check out the on-demand mini masterclas👇

Published by Vide Blomdahl in Insights, Mini Masterclass
Tags: 80/20 rule, Adobe, Adobe Analytics, Adobe Analytics Rockstar, Customer Experience, Customer Journey Analytics, Growth Matrix
Featured Image

May 21, 2025

Managing Consent in Adobe Web SDK: How to fix it with Dynamic Datastreams 

When migrating a client to Adobe’s Web SDK, we encountered a specific challenge that required creative problem-solving, and we believe it’s worth sharing. 

If you’ve ever had to deal with GDPR or cookie consent in a setup involving Audience Manager (AAM), you’ll know how tricky it can be to keep your tech compliant while still sending the right data. In this article, you will learn how we tackled it. 

Sampsa Suoninen, Principal Consultant

The problem: Web SDK doesn’t support conditional data forwarding 

In our project, we needed to use AAM, but only if the user had given consent for marketing. That sounds simple, but there’s a catch. 

In the old setup (using AppMeasurement), we could use a flag to control when data should be forwarded to AAM. Easy. 

But Web SDK doesn’t have that option. Once it’s configured to send data to AAM, it just... does. Even if the user hasn’t given marketing consent. 

This meant we needed a way to dynamically control where the data goes, depending on the user’s consent, without writing custom code or compromising on compliance. 

The workaround: use Adobe tags + multiple datastreams 

Our solution was to use Adobe Tags (formerly Launch) and create two versions of every datastream: 

- One with AAM enabled (for users who say yes to marketing) 

- One without AAM (for users who don’t) 

So instead of 3 Datastreams (for dev, staging, and production), we created 6 in total, doubling up to cover both consent scenarios. 

Then we used Data Elements inside Tags to switch between them based on consent. Here’s how. 

The setup: step-by-step 

This solution doesn’t require any custom coding and can be managed directly in Adobe Tags. 

1. Create static data elements for each datastream 

Make a separate static Data Element for each Datastream. This makes it easy to update Datastream IDs later without digging into code. 

2. Create “conditional” data elements per environment 

These will check the user’s consent and return the correct Datastream ID. For example: 

- If consent for marketing is true, return the AAM-enabled ID 

- If consent is false, return the AAM-disabled ID 

To do this, we used four supporting Data Elements: 

- Marketing Allowed – checks if the user gave marketing consent 

- Marketing Allowed Value – what value counts as “yes” (e.g., true) 

- Datastream – Prod – AAM Enabled – the ID with AAM 

- Datastream – Prod – AAM Disabled – the ID without AAM 

You can do the same for other environments (dev/staging) as needed. 

3. Apply these in the Web SDK extension 

Go into the Web SDK settings in Tags, and change the Datastream input to "Enter values" instead of selecting a fixed Datastream. 

Then, reference your conditional Data Elements here. 

This allows the Web SDK to dynamically choose the right Datastream based on the user's consent status at the time. 

One more thing: handling page loads and SPAs 

There’s one limitation with Web SDK: the settings are locked when the library loads. So if the user gives or changes consent after the page loads, the SDK won’t automatically switch to the right Datastream. 

This is especially problematic in single-page applications (SPAs) where the library might only load once per session. 

To solve this, we also added the same conditional logic in the “Configuration override” section of the Web SDK rules that send data (like “Send Event”). 

This ensures that even if the SDK doesn’t reload, the data is still sent using the correct Datastream, based on the user’s current consent status. 

The outcome 

With this setup, we’re now able to: 

- Fully respect the user’s consent choices 

- Ensure data is only sent to AAM when allowed 

- Avoid unnecessary custom code. 

- Adapt to changes mid-session (even in SPAs) 

If you’re working with Web SDK and dealing with consent-driven data routing, this approach is a flexible, scalable solution that can save time and keep your setup compliant. 

Want to see this implemented in a live setup or need help applying it to your environment? Contact us we’re happy to walk you through it. 

Published by Sampsa Suoninen in Insights
Tags: Adobe, Audience Manager, consent, Dynamic datastreams, GDPR, Page Load, WEBSDK
Featured Image

March 26, 2025

Adobe Summit 2025: Unleashing the Full Power of AI for Customer Experiences

It’s been a week since Adobe Summit 2025 concluded in Las Vegas, and after digesting the wealth of announcements and insights shared, it's clear we're entering an exciting new era, one driven by intelligent automation and seamless collaboration.

As expected, Adobe Experience Platform (AEP) once again took center stage, but the depth of innovation this year was remarkable. Adobe has accelerated the transition from assisting marketers to orchestrating entire workflows through AI, bringing practical applications front and center.

Let’s dive into the most impactful announcements and explore what they mean for your business.

Agentic AI: Meet Your New Virtual Team

One of the most exciting announcements was the introduction to Adobe’s Agent Orchestrator in AEP, complete with 10 specialized AI agents. Imagine automating your content production, web optimization, audience segmentation, and journey management, all with AI "team members" managed from a single interface. These pre-built, compliance-ready agents simplify tasks previously requiring significant manual effort or technical expertise, allowing marketers to focus on strategic initiatives.

Adobe Brand Concierge: Conversational AI Made Personal

Another groundbreaking innovation is Adobe Brand Concierge, a powerful conversational AI that creates immersive, personalized customer interactions. Built directly into AEP, this tool not only engages customers but coordinates seamlessly with your existing customer data and content. From answering product questions to scheduling follow-up actions, Brand Concierge is poised to redefine how businesses engage across digital channels.

Experimentation Accelerator: Optimizing Journeys with AI Precision

Adobe Journey Optimizer received a major upgrade with the new Experimentation Accelerator. This AI-driven feature takes the guesswork out of optimization by recommending the next best actions based on real-time, cross-channel data analysis. Businesses can now systematically test and improve customer journeys, significantly boosting marketing efficiency and ROI.

Enhanced Content Supply Chain: Faster, Smarter, Better

The announcements around Adobe GenStudio and Firefly expansions are equally transformative. GenStudio Foundation streamlines content creation and delivery into a single cohesive workflow, while Firefly now supports advanced generative AI capabilities for video and 3D content. These advancements enable marketers to quickly create and localize content at scale, dramatically shortening production cycles and amplifying content effectiveness across all markets and channels.

Strategic Partnership: Adobe Meets Amazon & AWS

One strategic partnership stood out. Adobe’s deeper integration with AWS and Amazon Ads. This collaboration unlocks powerful first-party data matching and targeting capabilities, streamlines ad creative workflows directly within Adobe Creative Cloud, and simplifies the deployment of Adobe Experience Cloud applications within AWS environments. It’s a strategic leap towards better performance, compliance, and seamless cross-platform experiences.

Adapting to the AI-driven Era

Beyond technology, the Summit emphasized the significant shift businesses must embrace to fully leverage these innovations. As AI continues to redefine workflows and customer expectations rise, marketers and IT teams must collaborate more closely. Adobe stressed the importance of clear executive ownership, cross-functional agility, and ongoing experimentation to navigate this rapidly evolving landscape successfully.

Key Takeaways for Businesses

  1. Leverage AI agents to scale personalization effortlessly
  2. Embrace conversational AI for richer customer engagement
  3. Adopt systematic, AI-driven experimentation to optimize customer journeys
  4. Streamline content workflows with advanced generative AI solutions
  5. Utilize strategic partnerships to enhance data-driven advertising and deployment flexibility

Final Thoughts

Adobe Summit 2025 was a testament to Adobe’s bold vision of integrated, AI-driven customer experiences. The advanced tools announced promise exciting opportunities for marketers and businesses ready to embrace these innovations. However, success hinges not just on adopting new technologies, but on fostering a culture of agility, collaboration, and continuous improvement.

To explore these innovations and their implications further, we recommend joining upcoming Adobe events or scheduling a session with our specialists at Accrease. The future of customer experience is here, so let’s navigate it together. Contact us here 😉

Kasper Andersen, Partner

Published by Kasper Andersen in Insights
Tags: Accrease, Adobe, Adobe Analytics, Adobe Experience Platform, Adobe Summit 2025, AEP, Customer Experience, Marketing Automation, Partnership
Featured Image

February 19, 2025

Top Picks for the Adobe Summit ’25 from Our Experts

Adobe Summit 2025 is almost here, and we're sorting through all the sessions and announcements to keep our clients ahead of the curve.

With 306 in-person sessions and 28 online, there's a ton to choose from. And if you can't make it in person, no worries. The sessions should be recorded, just like in past years.

Not sure where to start? Whether you're looking to sharpen your Adobe Analytics skills, explore AI-powered personalization, or fine-tune your omnichannel engagement, this year's lineup has something for everyone.

To help you make the most of your time, we asked our experts to share the sessions they're most excited about. Here are their top picks:

Emma Walderlo

Emma is our data-driven Paid Search expert who is always turning insights into high-performing campaigns. With experience from Avanza Bank, she’s all about smart strategies and sharp analysis.

Session: 
Adobe Analytics: Using Advanced Metrics to Level Up Your Reporting [OS115]

Reason: 
I’m looking forward to attending the session on calculated metrics in Adobe Analytics. This session feels especially relevant to me as it gives me the opportunity to learn more about how to create more precise metrics and gain a deeper understanding of how I can flexibly generate tailored insights, conduct more accurate analyses, and extract better insights from data.

No matter how much experience you have with Adobe Analytics, there’s always something new to learn and smarter ways to work. I believe that this session will provide me with the right tools to do just that. If you, like me, want to optimize your analyses and take your work in Adobe Analytics to the next level, I highly recommend checking out this session.

Jonas Nielsen

Former Consulting Manager at Adobe and Founder of Accrease. Jonas is a Swiss army knife for the Adobe stack, particularly AEP, and often finds himself by a whiteboard drawing the client's architecture around AEP.

Session: 
2025 Adobe Analytics Rockstars: Top Tips and Tricks [S101]

Reason: 
This is the session I always attend at every Summit I have attended, and that is quite a few. It is a super fun format, and I love the passion.

Session: 
Adobe Journey Optimizer Roadmap and Innovations [S520]

Reason: 
AJO is one of the solutions we see generating a lot of value for our customers. It allows us to use all of the data we have available in AEP to communicate something relevant to the customer, no matter the channel and wherein the customer's journey the person is. So, learning more about the roadmap and innovations will be super interesting.

Session: 
Building Personalized Connections at Scale: T-Mobile’s Adobe Journey [S733]

Reason: 
Because Accrease is already working with many leading telcos worldwide, I would love to learn more about how T-Mobile delivers personalized customer experiences using Adobe technology.

Session: 
Nordea Bank’s Journey to Power Customer Engagement [OS533]

Reason: 
To succeed with Adobe solutions, you need to invest in building the right teams to work with the solutions. Nordea has always impressed me with building good teams to support Adobe technology, and I always love to see one of our customers present at Adobe Summit.

Martine Jørgensen

Martine is our Adobe Analytics and CJA expert, as well as a Danish champion in bench press! Data or dumbbells, she lifts it all.

Session: 
2025 Adobe Analytics Rockstars: Top Tips and Tricks [S101]

Reason: 
A must-watch for any Adobe Analytics user looking to master the latest tips and tricks from industry experts. Learn insider techniques to optimize your analysis, uncover deeper insights, and make the most of your data.

Session: 
The Customer Journey Analytics Tips and Tricks Arcade [S103]

Reason: 
From this, you will get many practical tips and unlock advanced analysis techniques for those looking to level up their CJA skills.

Session: 
Accelerate Your Revenue Marketing and Sales Cycle with Customer Journey Analytics B2B Edition [S108]

Reason: 
This can be very insightful for Analysts and B2B marketers. This webinar dives into how Customer Journey Analytics can drive revenue, optimize sales funnels, and improve lead conversion. A must for anyone looking to connect marketing efforts with business growth.

Session: 
Adobe Analytics: Using Advanced Metrics to Level Up Your Reporting [OS115]

Reason: 
This one goes through AA reporting and shows how advanced metrics can transform Adobe Analytics dashboards. I would say this is ideal for analysts who want to elevate their storytelling and level of insight with data and drive smarter decision-making.

Martin Björklund

Martin is an expert in digital analytics—mastering tracking, measurement, and setting up Analytics. And yes, he’s a big fan of Excel, believing it’s one of the most fantastic tools out there!

Session: 
The Customer Journey Analytics Tips and Tricks Arcade [S103] & 2025 Adobe Analytics Rockstars: Top Tips and Tricks [S101]

Reason: 
I typically like the hands-on sessions, and customer journey analytics is the future of analytics tools, so from that perspective, the class is very promising. One of the most difficult things is to show relevant insights so that everyone understands how brilliant they are. This session will give you some tools to master later the ability to tell a clear and good story about your most valuable insights!

Samuel Rajkumar

Marketo specialist unlike any other. Experienced in building digital strategies using technologies like CDP and combining them with Marketing Automation.

Sessions: 
Hands-On: Troubleshooting Adobe Marketo Engage Like a Pro [L221 ] 

Reason: 
Performance optimization is a recurring challenge in Marketo, and this session offers hands-on insights directly from Adobe field engineers. From Smart List inefficiencies to campaign processing time, it covers the core elements that can impact system performance.

I find this session particularly valuable because performance bottlenecks often go unnoticed until they impact deliverability, scalability, and reporting. Learning how to proactively optimize Marketo setup, identify inefficiencies, and mitigate bot-related data pollution is critical for maintaining a clean and efficient instance.

Sessions: 
Hands-On: Crafting Interactive Webinars with Gen AI in Marketo Engage [L223]

Reason: 
Webinars continue to be a core part of marketing strategies, but leveraging Gen AI for enhanced engagement and personalization takes it to the next level. This session dives into end-to-end webinar creation in Marketo, including promotion, delivery, and post-event follow-ups.

I find this particularly relevant because recorded webinars often lose engagement over time, and using AI-powered tools to personalize on-demand experiences and repurpose content dynamically makes a huge difference. Learning how to integrate webinar insights into Marketo for improved lead quality and nurturing aligns well with how B2B marketers can maximize ROI.

Mette Riis Bach

Whether it’s navigating the post-cookie world or optimizing customer journeys, Mette knows how to connect the dots and make things happen.

Sessions: 
Driving Impact with Adobe Real-Time CDP Collaboration [L516]

Reason:
 I find it interesting to hear more about how companies and agencies can work together in a post-third-party cookie world. Both in terms of ensuring privacy focus and at the same time being able to fully leverage all the benefits of having an RTCDP. Personally, I find this session interesting because it provides insights into how companies can work seamlessly with external partners to enhance advertising and co-marketing efforts across channels like Connected TV, commerce media, and walled gardens. Something I know for sure can be an obstacle for many companies.

Sessions: 
Adobe Journey Optimizer Roadmap and Innovations [S520]

Reason:
Today, it is inevitable to talk about personalized, omnichannel engagement strategies without mentioning Adobe Journey Optimizer, which fully allows us to put the customer at the centre of the experience. My second recommendation is this roadmap session, which I believe would help anyone better understand the direction of the product and allow us to be on top of new features. 

Kasper Andersen

Former Manager at Adobe for Proof of Concepts in EMEA & JAPAC. He has been working with Adobe Analytics since it was known as SiteCatalyst; however, his favourite solution is still and always will be Adobe Target.

Session: 
AI-Powered Personalization: Prudential's Secret to a 135% Engagement Boost [S530] & Moving Beyond Buzzwords to Proving ROI with Adobe Mix Modeler [S413]

Reason:
Obviously there's a lot of focus on AEP solutions and this is of course the direction Adobe would like everyone to move in. However, a lot of customers are still using Adobe Target and Adobe Analytics, so I was excited to see that the solutions listed for the Prudential case were the good old AA and AT.

Combine that with AI personalization and a lift of a whooping 135% and you got yourself a perfect Summit session...if you ask me.

Which session is my runner-up, you ask? Okay, nobody asked, but I'm telling you anyway. As mentioned the solutions within AEP is getting a lot of focus and at Accrease we have a lot of clients migrating from AA to CJA. So keeping it within that space, then Mix Modeler is a really interesting solution and there's been some incredible cases with huge ROI.

Alright, that's our take for now. Check back after Summit, and we'll summarise the biggest and most important takeaways.

Published by Vide Blomdahl in Insights
Tags: Adobe, Adobe Analytics, Adobe Awards Accrease, Adobe Experience Platform, Adobe Marketo Engage, AEP, CJA, Customer Journey Analytics, Marketing Automation, Partnership, Summit
Featured Image

February 11, 2025

Are Collapsed Customer Profiles Hurting Your Marketing? How Identity Optimization Can Fix the Problem.

Imagine pouring endless hours and resources into designing personalized marketing campaigns only to discover they’re based on flawed customer profiles….It’s like throwing darts in the dark. In today’s multi-device, hyperconnected world, this is an all-too-common scenario.  

Shared devices and fragmented data inputs can lead to “collapsed profiles,” where behaviours and preferences from multiple users are mistakenly merged into one. The result? Wasted marketing budgets, diluted brand experiences, and missed opportunities to connect meaningfully with your audience. 

But how can your businesses rise above this challenge? In the following blog post, Senior Consultant Santosh Kumar will show you the hidden cost of collapsed profiles and how advancements in  Identity Stitching are revolutionizing the marketing game. 

The cost of collapsed profiles 

The challenge of maintaining accurate customer profiles has long been a headache for marketers striving for precision. Consider this: A father and son share a tablet. The father’s browsing history includes luxury watches, while the son spends his time looking up video games. If these distinct behaviors are collapsed into a single profile, the resulting data is an unhelpful mix. This misrepresentation makes it nearly impossible to deliver truly personalized marketing messages, leading to missed opportunities and diminished customer engagement. 

Understanding collapsed identity graphs 

To visualize the issue, let’s look at two types of identity graphs: 

Healthy identity graph: 

In a well-maintained graph, each CRM ID (customer identifier) is correctly associated with multiple ECIDs (device/browser identifiers). This ensures all behaviors across devices are tied to the same individual. 

Collapsed identity graph: 

In contrast, a corrupted graph features multiple CRM IDs and ECIDs tied to the same profile. This creates confusion and undermines the foundation of personalized marketing. 

Breaking through with Advanced Identity Stitching 

The good news? Advancements in identity stitching are revolutionizing how we understand and engage with our audiences. With Adobe’s Identity Optimization algorithm, marketers can finally combat profile collapse and regain control over their data. 

A new era of identity stitching 

Adobe’s innovative algorithm leverages both deterministic (exact match) and probabilistic (best guess) techniques to create accurate identity graphs. This hybrid approach ensures each individual is represented by a singular, reliable profile no matter how complex their digital footprint. 

Key features driving its success include: 

  1. Unique identifiers 
    By prioritizing stable identifiers like CRM IDs over transient ones like cookies, businesses can dramatically reduce the likelihood of corrupted profiles. 
  1. Adaptive algorithms 
    Adobe’s machine learning-powered system continuously evolves, refining its ability to differentiate between users and devices over time.
  2. Data hierarchy
    Marketers can define the priority of various identifiers, ensuring the most reliable data sources take precedence when building profiles.

Real-Time insights for dynamic marketing

One of the standout features of Adobe’s Identity Optimization is its real-time functionality. Marketers can adapt campaigns on the fly, leveraging up-to-date profiles that reflect current user behaviors. This agility is critical in a competitive digital landscape where timely and relevant messaging can make all the difference. 

Implementing Adobe’s Identity Optimization 

Excited to take your marketing efforts to the next level? Adobe’s Identity Optimization is currently in Limited Availability, but here’s how you can get started once it’s rolled out in full: 

Step-by-Step Guide 

  1. Understand your identities. 
    Navigate to AEP > Sandbox > Customer > Identities > Browse. Identify key identifiers like CRM IDs and ECIDs. The rest of the default identities are not in use.  

2. Simulate the graph.  

Optionally you may navigate to “Graph Simulation” tab and play with the configuration to understand how the new solution help not corrupting the profiles. The order of the things you do is highlighted in the screenshot below. 

3. Set up the graph. 
Finally, go back to the "Browse" tab and click the settings button in the top right corner to access the setup options. Here, start by ordering your cross-device IDs, such as CRM ID, phone number, etc. Next, specify whether each identity is unique. In this example, we've marked the CRM ID as unique to ensure only one CRM ID is added to the identity graph, preventing profile collapse. 

4. Adjust browser identities.  

Once completed, scroll down to see the list of browser identities, such as ECID, which also need to be ordered. 

You can use your mouse to click and hold an identity, then drag it up or down to adjust its position in the list. Note that cookie namespaces cannot be marked as unique within a graph, as it's not feasible in real-time scenarios.

5. Save and activate. 

In the final step, review the order of your identities and click the "Finish" button. After saving the configuration, it may take some time for the changes to activate. 

Challenges and opportunities 

While this innovation is a game-changer, it’s not without its limitations.  

Historical collapses: Past corrupted profiles won’t be automatically fixed. Businesses may need to work with Adobe to clean up legacy data. 

Data representation gaps: Underserved user groups highlight the need for diverse, comprehensive data collection. 

However, these challenges present an opportunity for growth. Businesses that invest in refining their data strategies today will be well-positioned to leverage these advancements fully. The payoff? Highly personalized customer experiences that drive engagement and loyalty. 

What this means for marketers 

For marketers, identity optimization represents a game-changing opportunity to: 

Enhance personalization: Craft messages tailored to individuals, not blurry profiles. 

Boost ROI: Stop wasting budget on inaccurate targeting. 

Build trust: Deliver relevant experiences that show you truly understand your audience. 

Let’s discuss. 

Have you encountered challenges with collapsed profiles? We’d love to hear your thoughts and help you out. 

About the Author
Santosh has more than a decades experience in within Digital Marketing and the Adobe stack. He holds more Adobe certifications than what's human possible. When no one else can fix it, you call for Santosh.

Troubleshooting & FAQs

As you implement Adobe’s Identity Optimization, you will wihtout a doubt run into questions or technical challenges. Check out Adobe’s official documentation or contact us and request to get passed through to Santosh 😉

Published by Santosh Kumar in Insights
Tags: Adobe, AEP, Customer Experience, Identity Optimization, Identity Stitching, personalization
Featured Image

January 29, 2025

How to Debug the Adobe Web SDK for Analytics and Target

Do you want to learn how to pinpoint, troubleshoot, and resolve common data issues in the Adobe Web SDK?

In this 20-minute Mini Masterclass, our very own Sampsa Suoninen will walk you through how to spot errors early, resolve them efficiently, and keep your data collection on track.

Why should you watch this Masterclass?

Many organizations are embracing the Adobe Web SDK or migrating from Adobe Analytics (AA) to Customer Journey Analytics (CJA).

When data streams are disrupted, reporting and insights can suffer.

Who should attend?

Developers, analysts, and marketers who use or plan to use the Web SDK.

Teams preparing to migrate from AA to CJA, looking for a seamless data collection process.

What you will learn:

Core concepts: Understand how the Web SDK combines data collection for Analytics, Target, and other Adobe products.

Troubleshooting method: Follow a clear, step-by-step approach to prevent and fix data flow issues.

Essential tools: Learn how to use the Adobe Experience Platform Debugger to track network requests and verify setup.

Data safeguards: Discover ways to record requests and maintain integrity, even when errors occur.

Real-world scenarios: See how other teams tackled common challenges and kept their data flowing.

Who Should Attend?

Developers, analysts, and marketers who use or plan to use the Web SDK.

Teams preparing to migrate from AA to CJA, looking for a seamless data collection process.

Bonus: In the session, you will be able to download a concise PDF checklist outlining the key debugging steps for the Web SDK—your quick reference guide whenever issues arise.

Check out the on-demand mini masterclas👇

Published by Vide Blomdahl in Mini Masterclass
Tags: Accrease, Adobe, Adobe Analytics, Adobe Target, Debugging, WEBSDK
Featured Image

November 28, 2024

Activate Engagement Scoring to Drive Business Impact

What if you could pinpoint your most engaged users, understand what makes them tick, and tailor your strategies to boost conversions and retention?

In this webinar, our very own Jude Felix, Data Scientist at Accrease will show you how to activate an engagement score and drive significant business impact. Discover how engagement scoring can turn your customer data into actionable insights that fuel growth and improve outcomes.

Here's what you can expect:

How Can Engagement Scoring Impact Your Business? Understand why engagement scoring matters and how it directly contributes to driving meaningful results for your business.

Introduction to Engagement Scoring: Learn what engagement scoring is, its role in analytics, and why it's crucial for effective decision-making.

Role of Adobe Analytics & Customer Journey Analytics: Compare key features and benefits of Adobe Analytics (AA) and Customer Journey Analytics (CJA), and understand how these tools help bring engagement scoring to life.

Data Requirements: Identify relevant data sources, understand the types of data needed, and address data quality and integration challenges.

Building Your Engagement Scoring Model: Learn the steps to define key metrics, collect data, develop, and validate an effective engagement scoring model.

Implementing and Activating the Model: Discover how to integrate your engagement scoring model into AA and CJA, and how to monitor and adjust it for maximum impact.

Takeaways

Bonus: As an added bonus, all attendees will receive a complimentary pre-counseling offer! This includes a free one-on-one consulting session with Jude to help you get started. This offer is for those who use Adobe Analytics and are ready to activate their data for engagement scoring.

Check out the on-demand mini masterclas👇

Published by Vide Blomdahl in Mini Masterclass
Tags: Accrease, Adobe, Adobe Analytics, Customer Experience, Customer Journey Analytics, Engagement Scoring, Webinar
Featured Image

November 18, 2024

Building an Engagement Scoring Model for Analytics Data: A step-by-step guide

What if you could pinpoint your most engaged users, understand what makes them tick, and tailor your strategies to boost conversions and retention? With Adobe Analytics (AA) and Adobe Customer Journey Analytics (CJA), you already have a wealth of data on user behaviour. The real challenge lies in distilling that data into clear, actionable insights.

An Engagement Scoring Model helps you do just that. By assigning scores based on user interactions, you’ll quickly identify your top-performing audience segments, understand which behaviours drive the most value, and prioritize efforts to maximize business outcomes.

In this guide, Jude Felix, Senior Consultant at Accrease will show you how to build an Engagement Scoring Model step by step. You’ll learn how to transform raw analytics data into a powerful tool for targeting, personalization, and optimization, giving you a clearer view of what drives success—and how to replicate it.

Jude Felix, Senior Consultant

What is an Engagement Scoring Model? 

An Engagement Scoring Model is a framework that assigns a numerical score to users based on their interactions with your digital properties. By scoring user engagement, you can: 

- Identify which user behaviors or interactions are most valuable. 

- Segment users based on their engagement levels. 

- Make data-driven decisions for targeting, personalization, and optimization. 

The process for creating this model combines both gut-based intuition and data-driven analysis to determine which metrics matter most for your business goals. Below are the steps to make the model.

Steps to create the Engagement Scoring Model

Creating an effective engagement scoring model is a powerful way to understand and quantify user behavior. It helps businesses tailor strategies and drive more meaningful customer interactions. Following a structured approach, you can identify key engagement metrics, analyze their impact, and assign appropriate weights to create a robust scoring system. 

In this process, we will walk through 7 key steps, starting with defining the data timeframe, selecting relevant metrics, and conducting correlation analysis. We’ll then benchmark metrics, assign weights, and create an engagement score formula. Finally, we validate the model to ensure it accurately reflects user engagement and drives real business results. This systematic approach helps you gauge engagement effectively and provides actionable insights to refine customer experience and strategy for better outcomes.

1. Decide the data time frame 

The first step is to decide how much data you want to include in your model. The last 30 days is typically a good starting point, as they capture recent user behaviour without including too much stale data. However, depending on your business or campaign needs, you may choose a different timeframe (e.g., last 7 days or last 90 days). 

2. Select key metrics 

Selecting the right metrics is the most important step in building the engagement model. There are two main approaches to choosing these metrics: 

The intuition-based approach: Based on your experience and knowledge of your customers, you can choose metrics that you believe are important for driving engagement. Some of the metrics might include:

- Page views

- Time spent on site

- Number of sessions

- Product views

- Purchases

- Revenue

The data-driven approach: If you want a more empirical approach, you can identify the metrics most correlated with achieving a specific goal, such as purchasing or signing up for a newsletter. You can do this through statistical correlation analysis, which we will discuss in the next step. 

3. Perform Correlation Analysis 

To validate and refine the chosen metrics, you can use statistical methods to find out which ones are most closely associated with user success or your defined goals. The goal here is to understand which metrics have the greatest impact on user engagement. 

How do you conduct the correlation analysis in Excel? 

Gather your data: 

- Export relevant data from AA or CJA for your selected metrics over your chosen timeframe (e.g., the last 30 days). 

Enable Analysis Toolpak in Excel: 

- Go to File > Options > Add-ins. 

- In the Manage box, select Excel Add-ins, and click Go. 

- Check the box for Analysis Toolpak, and click OK. 

Run the correlation analysis: 

- Organize your data in columns, with each column representing a metric. 

- Navigate to Data > Data Analysis and choose Correlation. 

- Select the range of data and choose Output Range to display the correlation matrix. 

Analyze the results: 

- The correlation matrix will show you the correlation coefficients between each metric and the goal metric (e.g., purchases, signups). 

- A correlation coefficient ranges from -1 to 1, with 1 indicating a perfect positive correlation, -1 indicating a perfect negative correlation, and 0 indicating no correlation. 

Figure 1 below shows the results of a correlation calculation in Excel based on a few selected metrics.  

Figure 1 Correlation calculation in Excel. 

4. Benchmark a Score Using the Correlation Coefficients 

Once you have your correlation coefficients, the next step is to decide which metrics to include in your engagement model. To do this, you can benchmark a threshold score by calculating the average correlation coefficient across all metrics. 

- Metrics with correlation coefficients equal to or above the average should be included in the engagement model. 

- Metrics below the average threshold may not significantly contribute to engagement and can be excluded. 

Based on the coefficients of correlation from the Figure 1 we can create a benchmark chart like in Figure 2. The metrics number 3, 5, 6, 7 and 8 are he metrics that is highly correlated. 

Figure 2 Benchmark chart 

5. Assign weights to the metrics 

Now that you have selected the most relevant metrics, you need to assign them weights. These weights determine how much influence each metric will have on the overall engagement score. 

Normalizing Correlation Coefficients to Assign Weights: 

Take the correlation coefficients from the previous step and normalize them so that they add up to 100%. This can be done by dividing each metric’s correlation coefficient by the total sum of all selected metrics’ correlation coefficients and multiplying by 100. 

For example, if you have three metrics with correlation coefficients of 0.8, 0.5, and 0.3, you can calculate the normalized weights as follows: 

- Total correlation = 0.8 + 0.5 + 0.3 = 1.6 

- Normalized weight for metric 1 = (0.8 / 1.6) * 100 = 50% 

- Normalized weight for metric 2 = (0.5 / 1.6) * 100 = 31.25%                       

- Normalized weight for metric 3 = (0.3 / 1.6) * 100 = 18.75% 

These normalized values become the weights for each metric, ensuring that the metrics most closely associated with user engagement have the greatest impact on the score.

6. Create the Engagement Score Formula 

Now that you have both the metrics and their respective weights, you can calculate the engagement score for each user. The formula will look something like this: 

𝐸𝑛𝑔𝑎𝑔𝑒𝑚𝑒𝑛𝑡𝑆𝑐𝑜𝑟𝑒 = (𝑀𝑒𝑡𝑟𝑖𝑐𝑠1 × 𝑛𝑜𝑟𝑚𝑎𝑙𝑖𝑠𝑒𝑑𝑊𝑒𝑖𝑔ℎ𝑡1) + (𝑀𝑒𝑡𝑟𝑖𝑐𝑠2 × 𝑛𝑜𝑟𝑚𝑎𝑙𝑖𝑠𝑒𝑑𝑊𝑒𝑖𝑔ℎ𝑡2) + (𝑀𝑒𝑡𝑟𝑖𝑐𝑠3 × 𝑛𝑜𝑟𝑚𝑎𝑙𝑖𝑠𝑒𝑑𝑊𝑒𝑖𝑔ℎ𝑡3) + …

 [A1] 

For example, if you score based on Page Views, Time Spent on Site, and Purchases, figure 3 shows how this can be created in AA or CJA. 

Figure 3 Calculation of engagement score 

7. Validate the Engagement Model 

After building the engagement scoring model, it’s crucial to validate it by applying the model to a sample of users and comparing the scores with actual business outcomes. As shown in figure 3, we can Do higher engagement scores correlate with higher conversions or more purchases? 

If the scores don’t align with real-world outcomes, you may need to revisit the metrics or re-run the correlation analysis to fine-tune the model. 

If the model accurately reflects user engagement and correlates with success, it’s ready to be deployed. 

Why use an Engagement Scoring Model? 

An engagement scoring model provides businesses a tangible way to measure and track user engagement over time. Here’s why it matters: 

Identify high-value users: By scoring users, you can quickly identify your most engaged users, allowing you to focus your marketing efforts where they’ll have the greatest impact. 

Target personalization: Use engagement scores to deliver personalized experiences based on the level of user engagement, creating a more tailored and relevant experience for your audience. 

Optimize user journeys: By understanding which behaviors drive engagement, you can optimize your website, app, or marketing efforts to encourage those behaviours, improving overall customer satisfaction and conversion rates. 

Conclusion 

Building an engagement scoring model using Adobe Analytics or Customer Journey Analytics data is a powerful way to turn raw user interaction data into actionable insights. By following a data-driven approach backed by statistical analysis, you can create a model that accurately reflects user engagement and drives better business outcomes. 

This method combines both intuition and rigorous analysis, ensuring that the metrics you choose are grounded in actual data and that the engagement scores you generate align with your business goals. Whether you’re focusing on retention, acquisition, or conversion optimization, an engagement scoring model provides the foundation for smarter, more effective marketing and product strategies. 

Start building your model today to maximize your Adobe Analytics data.

Want to dive deeper? Join Jude Felix for a 20-minute Mini Masterclass: 'How to Activate Engagement Scoring to Drive Business Impact.' In this session, Jude will walk you through building and activating engagement scoring models using Adobe Analytics and Customer Journey Analytics (CJA). Don't miss out, sign up here: Mini Masterclass

Published by Jude Felix in Insights
Tags: Accrease, Adobe, Adobe Analytics, Customer Experience, Customer Journey Analytics, Engagement Scoring, User engagement
Featured Image

October 7, 2024

Enabling scroll depth tracking in Adobe Analytics with the new WebSDK Plugin 

Tracking how much of a webpage users actually view is crucial to understanding engagement with your content. Whether you’re analyzing long-form articles, product pages, or campaign landing pages, scroll depth provides direct insight into how far users are going before leaving the page.

For years, the getPercentPageViewed plugin has helped marketers track scroll depth in Adobe Analytics. However, with the adoption of Adobe's new WebSDK, the old plugin is no longer compatible, leaving organizations that rely on modern architectures with a gap in their analytics setup.

We’ve developed a new scroll depth plugin specifically for Adobe’s WebSDK, offering a more robust, flexible, and scalable solution for tracking user engagement. In this post, we’ll explain the problem with the legacy plugin, demonstrate how to visualize scroll depth data, and guide you through the implementation of the new WebSDK-based solution

How to use scroll depth data in Adobe Analytics to identify drop-off points

One of the most valuable insights scroll depth tracking offers is identifying where users drop off on your pages. For landing pages and key CTA pages, this is critical, as it reveals whether visitors are engaging with your content long enough to reach the main calls to action.

Pinpointing drop-off points

Scroll depth data allows you to see exactly how far down the page users scroll before they exit or lose interest. If a significant portion of your visitors drop off before reaching the key messaging or CTA, this indicates a potential issue in your content flow, page design, or CTA placement. By identifying these drop-off points, you can take action to reduce friction and keep users engaged.

Consider screen size: percentages vs. absolute values

When analyzing scroll depth, it’s important to take screen size into account. Users on mobile devices may experience your page differently from desktop users, as content is displayed in a more compressed format. For this reason, it’s often helpful to measure scroll depth both in percentage terms (how far down the page they’ve scrolled) and absolute values(such as pixels or viewport units).

  • Percentage-based tracking: This helps normalize data across devices, making it easier to see the relative point where users drop off, regardless of screen size. For example, if 50% of mobile and desktop users are dropping off at around the same percentage mark, this provides a clear signal about engagement issues.
  • Absolute value tracking: This gives you more granular control over understanding specific user behaviors, especially when dealing with longer pages or dynamic content that may load differently across devices.

Mobile vs. non-mobile device analysis

Analyzing scroll depth data separately for mobile and non-mobile (desktop or tablet) devices is crucial for understanding the full picture. Given the different user behaviors and screen sizes, you may find that mobile users drop off sooner due to the nature of scrolling on smaller screens, while desktop users may scroll further before disengaging.

By segmenting your data, you can:

  • Mobile devices: Adjust content and CTA placement to ensure critical information is visible early on smaller screens, where users typically scroll faster.
  • Non-mobile devices: For desktops or larger screens, you may have more flexibility in content layout, allowing for CTAs to be placed further down the page, provided engagement levels remain high.

Example: improving CTA engagement on a landing Page

Imagine you’re running a campaign with a dedicated landing page designed to collect sign-ups. After reviewing the scroll depth data segmented by device type, you notice that the majority of mobile users drop off at 20%, while desktop users continue scrolling to 37%, but your sign-up form and CTA button are placed at 70%.

By moving the form higher, say around the 15% mark for mobile users and 35% for desktop users, you ensure that more visitors see the CTA before they drop off. This significantly increases the likelihood of conversions across both device types. Scroll depth tracking helps you make these data-driven adjustments, optimizing the performance of your landing pages for all users.

How to Implement the New Scroll Depth Plugin in Adobe WebSDK

Now that we've covered how scroll depth data helps identify drop-off points and optimize your landing pages, let’s look at how to implement the new plugin in Adobe WebSDK.

Step 1: Add the following code snippet at the end of the "send event" action in your page view rule:

//clear previous page data

_satellite.cookie.remove('initialPercent');

_satellite.cookie.remove('highestPercent');

// Function to set a cookie with an optional expiration in minutes

function setCookie(name, value, minutes) {

    var expires = "";

    if (minutes) {

        var date = new Date();

        date.setTime(date.getTime() + (minutes * 60 * 1000));

        expires = "; expires=" + date.toUTCString();

    }

    document.cookie = name + "=" + (value || "") + expires + "; path=/";  

}

// Function to calculate the percentage of the page viewed

function getScrollPercent() {

    const scrollTop = window.pageYOffset || document.documentElement.scrollTop;

    const scrollHeight = document.documentElement.scrollHeight - document.documentElement.clientHeight;

    return Math.min(Math.round((scrollTop / scrollHeight) * 100), 100);

}

// Function to calculate the initial viewport percentage

function getInitialViewportPercent() {

    const viewportHeight = window.innerHeight || document.documentElement.clientHeight;

    const scrollHeight = document.documentElement.scrollHeight;

    return Math.min(Math.round((viewportHeight / scrollHeight) * 100), 100);

}

// Function to track page view data

function trackPageViewData() {

    // Set the initial percent viewed on page load

    if (!_satellite.cookie.get('initialPercent')) {

        // Calculate the initial viewport percentage

        const initialPercent = getInitialViewportPercent();

        _satellite.cookie.set('initialPercent',initialPercent);

        _satellite.cookie.set('highestPercent',initialPercent); // initially set with initial percent value, once user scrolls the page it gets updated.

    }

    // Get the current scroll percent

    const currentPercent = getScrollPercent();

    // Update the highest percent viewed

    const storedHighestPercent = parseFloat(_satellite.cookie.get('highestPercent') || 0);

    if (currentPercent > storedHighestPercent) {

       _satellite.cookie.set('highestPercent',currentPercent);

    }

}

// Initialize page view tracking

trackPageViewData();

// Initialize page view tracking

window.addEventListener('scroll', trackPageViewData); // Track on scroll events

window.addEventListener('click', trackPageViewData); // Track on click events

Step 2: Create a data element that reads the initialPercent and highestPercent values from cookies and builds a string:

var initialPercent = _satellite.cookie.get('initialPercent');
var highestPercent = _satellite.cookie.get('highestPercent');
if(initialPercent!= null && initialPercent!= 'undefined' && highestPercent != null && highestPercent != "undefined"){
  return "initialPercent="+initialPercent + " | "+ "highestPercent="+ highestPercent;
}
else{
  return "";
}

Step 3: Map the data element to the desired field in the XDM object in the same page view tracking rule.

Step 4: Build your changes in your development and make sure the eVar is captured with the desired value.

Step 5: Create rule-based classifications to separate initial percent and highest percent values into separate dimensions and then create sub classifications to bucket them if needed.

Considerations for scroll depth tracking

Scroll depth tracking offers valuable insights into how users engage with your content, but there are a few important considerations to be aware of when implementing this feature in Adobe WebSDK. 

Scroll data isn’t captured for users who bounce

Currently, our scroll depth plugin does not fire if a user bounces, meaning scroll depth data won’t be captured if a visitor leaves the page without interacting further. This could lead to missed insights, especially on high bounce-rate pages.

Testing before implementing to ensure a smooth rollout

Before implementing the scroll depth tracking plugin in a live environment, it's crucial to conduct thorough testing to ensure it works as expected and doesn't introduce any issues that could affect performance or data accuracy.

Maximizing insights with no additional cost

Scroll depth tracking provides invaluable insights into how users engage with your content and where they drop off, especially for landing pages and key CTA sections. However, it’s important to be mindful of factors like server calls, bounce data, and fast-scrolling behavior when implementing this functionality.

If you are looking to capture real-time scroll data or need help optimizing your scroll depth tracking, we’re happy to help. Contact us for guidance on the best approach for your business and to ensure you’re getting the most out of Adobe Analytics while keeping costs and performance in check.

Santosh would be happy to help! Reach out, get started and ask your questions to: [email protected]

Published by Santosh Kumar in Insights
Tags: Adobe, getPercentPageViewed, Scroll depth tracking, WEBSDK
Older Posts ›
Accrease logo

Bring your data to life with Accrease - Adobe Solution Partner Gold.

linkedin

CONTACT

[email protected]
DK: +45 89 871 101
SE: +46 8 446 891 01
NO: +47 75 98 71 01

 

CONTACT

[email protected]
DK: +45 89 871 101
SE: +46 8 446 891 01
NO: +47 75 98 71 01

 

HEADQUARTER

Accrease ApS
Store Kongens Gade 40G 4 1264 København K Denmark

 

© 2025 Acrease ApS | All rights reserved    |    Privacy policy   |   CVR: 37539082