Customer expectations are not just rising; they are skyrocketing. By 2026, the brands that create real customer loyalty won’t be the ones that send clever emails or spruce up their loyalty programs. They’ll be the ones who can almost read their customers’ minds, anticipating needs before customers have to ask. I think of it like this:

If Great CX in 2025 were a skilled short-order cook, it would have expertly filled every customer’s order as it came in. Great CX in 2026 is the master chef who knows your favorite dish before you even sit down, having already prepped the ingredients and timed everything perfectly for your arrival.

This leap from reacting to anticipating is already underway, and it is about to redefine what “Great CX” really means. With this post, I plan to explore what predictive engagement looks like, why it matters for your business, and how you can start cooking up this future today.

The Big Shift: From answering questions to reading minds

For ages, customer experience has been about responding. We’re answering questions, fixing hiccups, gently nudging conversions, and recommending next best actions. Predictive engagement changes everything. Instead of waiting for customers to reach out, we’ll use smart data and AI to understand what is coming and act with intention. Imagine a couple of predictive scenarios:

A customer’s delivery is running a bit late. Instead of them anxiously checking, tracking, or calling support, your system detects the delay, automatically offers alternative options, and sends a friendly, proactive update.

A customer is thinking about leaving for another brand. Predictive models can spot those early signals and trigger tailored, helpful offers before customers even consider shopping elsewhere. This proactive approach transforms customer relationships into something far more intuitive and supportive.

Four big ideas shaping CX in 2026

Given the ever-shifting nature of customer expectations, I tried to pinpoint what I think will cause the biggest changes for CX teams in 2026.

1. Hyper-Personalization Gets Real. Personalization still, oftentimes, means sending different messages to different defined segments. In 2026, it means real-time, adaptive journeys explicitly tailored to each person. Generative and predictive AI will power “next-best-experience” decisions, making every interaction feel incredibly relevant and perfectly timed.
2. Conversational AI Becomes Your Best Server. Chatbots are no longer just for FAQs. They are becoming intelligent assistants that can resolve issues, escalate with all the right context, and learn from every chat. The best experiences will combine smart automation with real human empathy, so customers always feel understood.
3. Service Fixes Itself. Predictive insights will flow into operations, allowing systems to fix problems before they even impact customers. Think of billing errors being corrected automatically or parts being replaced before they fail. This minimizes disruption and keeps things running smoothly.
4. Trust Becomes Your Brand’s Superpower. As AI takes center stage, transparency and ethics matter more than ever. Customers expect clear explanations of how their data is used and confidence that decisions are fair. Brands that build trust into every experience will truly shine.

Building your smart CX kitchen

Delivering predictive CX is not about adding just one more gadget. It is about creating a unified, event-driven ecosystem. This includes:

• A solid data foundation that brings together customer profiles and real-time signals.
• An AI and decisioning layer to predict intent and recommend the most helpful next steps.
• Experience orchestration to trigger proactive outreach across all your channels.
• Operational automation for those self-healing processes.
• Governance and trust controls for transparency and clear explanations.

How to start cooking up the future

• Map your most important customer journeys. Start by identifying those key signals that hint at intent, risk, or value.
• Build smart decision-making logic. Set clear boundaries for automation and when to bring in human help.
• Perfection is the enemy of progress. Pilot a few proactive ideas that move the needle from a CX perspective, things like helpful delivery updates or churn prevention, to get started.
• Scale your conversational AI to make sure customer context follows them across all channels.
• Measure what works and keep optimizing and experimenting.
• Make trust a core ingredient by using transparent notices and carefully overseeing your AI models.

Looking ahead – answering the question before it’s asked

Predictive CX is not just a nice-to-have for customers; it is a game-changer for your business. It boosts retention by catching churn risk early, reduces service costs by preventing avoidable contacts, and drives revenue by surfacing the right offer at the perfect moment. Plus, it makes your operations far more efficient by avoiding downstream issues.

Customer experience is shifting fast. In the next year, anticipation will be a customer expectation. The brands that win will combine data, predictive intelligence, and automation built on trust and transparency. Begin laying the groundwork today so you can deliver experiences that feel effortless and intuitive.

In my previous blog, Unlocking Advanced Personalization in Sitecore XM Cloud with Sitecore Personalize, I explored how the integration between Sitecore XM Cloud and Sitecore Personalize unlocks advanced personalization capabilities – enabling cross-channel decisioning, custom audiences, and real-time variants. In that post I explained the architecture, the run-time flow, and why the default embedded personalization in XM Cloud may not suffice for developers looking to implement deep, business-specific personalization logic.

In this follow-up, we will dig deeper and focus on how to extend personalization in XM Cloud by creating custom conditions in Sitecore Personalize. We will walk through the step-by-step process: defining a use case, writing condition logic, testing and publishing it, and then applying it to a real experience. By the end of this blog, you will be equipped to build your own developer-written conditions that marketers can reuse in their audience builder – taking personalization beyond the out-of-box and into true business-driven differentiation.

What Are Conditions in Sitecore Personalize and Why Custom Conditions Matter

• Out-of-the-box conditions- prebuilt by Sitecore (geolocation, device type, visit behavior, etc.).
• Custom conditions – where you define your own logic, often using JavaScript (or assisted by AI if you enable the Code Assistant), to handle business/custom data and decisioning.

How Conditions Work – The Mental Model

When you write a custom condition in Personalize:

1. You define input parameters (if any) – these become configurable by authors when applying the condition.
2. You write logic (in JavaScript) that reads visitor/session/guest data (or external data if you fetch it), evaluates your business rule, and returns a boolean (true/false) or a structured object depending on the expectation.
3. You define a friendly output – a human-readable sentence (with placeholders for input parameters) that authors see when selecting the condition for an experience or experiment.
4. Once you save and publish the condition, it’s available alongside other conditions (out-of-the-box or custom) in the conditions library, and can be applied by marketers without coding.

Because Personalize and SitecoreAI are connected already, all the custom conditions created here are automatically available in the Page Builder – so authors can use it in experiences without needing developer deployments.

How to Create a Custom Condition – Step by Step

Here’s the standard workflow:

1. Navigate to Developer center → Conditions in Sitecore Personalize.

2. Click Create, or duplicate an existing condition and modify it as needed. The out-of-the-box (OOTB) conditions are very useful – you can review their JavaScript code for reference when building your own custom conditions.

3. Provide a name for your condition.

4. Open the code editor (click Edit). The code must be written in JavaScript.

5.If needed, define input parameters (for example: a string, number, or list) – these will show up later when configuring the condition in an experience.

6.Write the logic to compute condition result. Use local variables, avoid global object modifications, namespace shared logic if reusing across conditions  to avoid conflicts.

7.Switch to the Configuration tab to define the condition output text – how this condition will be displayed in the UI, with placeholders for your defined input parameters using double square-brackets ([[parameterName]]). Missing parameters or incorrect syntax will show errors.

8.Once you’ve defined the code and output, test the condition using sample guest data. You can either retrieve a guest ID from the browser or use a known visitor ID.
To find the guest reference ID:

• Open the Sitecore AI-integrated webpage in your browser.
• Inspect the page and navigate to Application → Cookies.
• In your site’s cookies, look for a cookie named sc_<id>_personalize.
  This value is your guest reference ID and can be used to verify that the logic works as expected.

Added a Guest Reference

Add Conditional Parameters

Test Response

9.If test passes, Publish the condition so it’s available for use in Experiences.

Thats it – your custom condition is now part of the Conditions Library and ready to be used by content or marketing authors.

If your organization has enabled the Code Assistant via Sitecore Stream, you can even bypass manual JS –  just describe what you need in plain English, and the assistant generates code for you. But always review/test it.

Wrapping Up

Custom conditions are one of those features that quietly but significantly elevate the personalization strategy for any XM Cloud + Personalize implementation, they bridge the gap between what the platform provides and what your business actually needs. They let you capture the nuances of your business rules and make them reusable, testable, and accessible to content authors without additional development cycles.

Think of them as building blocks: once you define the logic correctly, authors can mix and match them to create highly targeted experiences – all without touching code. And thats exactly where the strength of the platform lies.

This wraps up the last part of my personalization series, but I hope it’s also the beginning of you exploring personalization in a more thoughtful and structured way. If you have been relying only on out-of-the-box rules, try creating your first custom condition – the clarity and control it brings is genuinely worth it.

In this episode of “What If? So What?”, Jim Hertzfeld sits down with Wally Burchfield, former senior executive at GM, Nissan, and Nissan United, to explore what’s driving transformation in the automotive industry and beyond. 

 Wally’s perspective is clear: in a world obsessed with automation and data, the companies that win will be the ones that stay human. 

 From “Build and Sell” to “Know and Serve” 

 The old model was simple: build a car, sell a car, repeat. But as Wally explains it, that formula no longer works in a world where customer expectations are shaped by digital platforms and instant personalization. “It’s not just about selling a product,” he said. “It’s about retaining the customer through a high-quality experience one that feels personal, respectful, and effortless.” Every interaction matters, and every brand is in the experience business. 

 Data Alone Doesn’t Build Loyalty – Trust Does 

 It’s true that organizations have more data than ever before. But as Wally points out, it’s not how much data you have, it’s what you do with it. The real differentiator is how responsibly, transparently, and effectively you use that data to improve the customer experience. 

 “You can have a truckload of data but if it doesn’t help you deliver value or build trust, it’s wasted,” Wally said. 

 When used carelessly, data can feel manipulative. When used well, it creates clarity, relevance, and long-term relationships. 

 AI Should Remove Friction, Not Feeling 

 Wally’s take on AI is refreshingly grounded. He sees it as a tool to reduce friction, not replace human connection. Whether it’s scheduling service appointments via SMS or filtering billions of digital signals, the best AI is invisible, working quietly in the background to make the customer feel understood. 

 Want to Win? Listen Better and Faster 

 At the end of the day, the brands that thrive won’t be the ones with the biggest data sets; they’re the ones that move fast, use data responsibly, and never lose sight of the customer at the center. 

 Listen to the full conversation with Wally Burchfield for more on how trust, data, and AI can work together to build lasting customer relationships—and why the best strategies are still the most human. 

Subscribe Where You Listen

Apple | Spotify | Amazon | Overcast | Watch the full video episode on YouTube

Meet our Guest – Wally Burchfield

Wally Burchfield is a veteran automotive executive with deep experience across retail, OEM operations, marketing, aftersales, dealer networks, and HR. 

He spent 20 years at General Motors before joining Nissan, where he held multiple VP roles across regional operations, aftersales, and HR. He later served as COO of Nissan United (TBWA), leading Tier 2/3 advertising and field marketing programs to support dealer and field team performance. Today, Wally runs a successful consulting practice helping OEMs, partners, and dealer groups solve complex challenges and drive results. A true “dealer guy”, he’s passionate about improving customer experience, strengthening OEM-dealer partnerships, and challenging the status quo to unlock growth. 

Follow Wally on LinkedIn  

Learn More about Wally Burchfield

Meet our Host

Jim Hertzfeld is Area Vice President, Strategy for Perficient.

For over two decades, he has worked with clients to convert market insights into real-world digital products and customer experiences that actually grow their business. More than just a strategist, Jim is a pragmatic rebel known for challenging the conventional and turning grand visions into actionable steps. His candid demeanor, sprinkled with a dose of cynical optimism, shapes a narrative that challenges and inspires listeners.

Connect with Jim:

LinkedIn | Perficient

In my previous blog https://blogs.perficient.com/2024/07/01/sitecore-personalize-close-event-logic/, I shared a method for using cookies to enable the user to dismiss an alert banner.  This process involved writing the cookie when the user clicks the close icon and checking for the cookie when the experience is displayed.  This approach worked well because the entirety of the javascript code could be stored in the web template.  This ensures the code to check for the cookie can’t be missed or forgotten when the template was used.  Unfortunately, this had an unintended side effect.  Personalize still executed the experience and counted it in the analytics and performance metrics even though the javascript never added the elements to the screen.  This lead to overinflated metrics and the inability to use the data for accurate forecasting.  This problem can be overcome with advanced page targeting.

Advanced Page Targeting

Advanced page targeting allows you to run client side javascript to decide if an experience should execute.  Since the javascript runs client side, you can read the url and query string parameters, you can access the console to log messages, you can access the document object to query selectors on the page, and of course read cookies.  Advanced page targeting javascript runs after the page loads, but before the experience loads which allows us to prevent the experience from executing and overinflating analytics.  Be sure to keep your script as lean and performant as possible to reduce the possible screen flicker of loading the experience after the page has loaded.

Checking Cookies with Advanced Page Targeting

In order to use advanced page targeting, you must select the “specific pages” setting under “Page Targeting”.

Enable page targeting on specific pages to enable advanced page targeting

In the flyout window for page targeting, add any filters for pages where you want the experience to display.  If you want the experience to display on all pages, simply use the contains “/” rule.  In the advanced targeting section, click the “add script” button.

Configure advanced page targeting

In the advanced targeting code editor, enter the following code.

(function() {
   // console.log(new Error().stack);

    var cookies = document.cookie.split(';');
    for (var i = 0; i < cookies.length; i++) {
        var cookie = cookies[i].trim();
        if (cookie.indexOf('pers-' + selectedVariant.ref + '=clicked') === 0) {
            return false;
        }
    }

    targetingPassed();
})();

In my previous blog, I created the cookie using the variant.ref as part of the cookie name.  This adds the guid of the current experience id to the name of the cookie making it unique even when the web template was reused.  Advanced targeting does not have access to the variant.ref property.  So it doesn’t work with the close event logic idea I came up with before.  However, there is a selectedVariant.ref property that you can use.  Using selectedVariant.ref works for both experiences and experiments as it can dynamically get the correct guid of the current variant at run time.

When personalize evaluates this block of javascript code, it only continues processing the flow of execution for the experience if the “targetingPassed()” function is called.  If you want to stop the flow of execution, return false.  In our case, we want to stop the flow of execution if the cookie is found.  Otherwise we can call the targetingPassed() function and allow the experience to display to the user.

Once you have added advanced targeting javascript, you can edit the script by clicking the pencil icon.

Edit advanced page targeting settings

Edit advanced page targeting script

Things to Know About Advanced Page Targeting

As mentioned, this solution solves the problem of overinflating analytics.  The downside is the advanced page targeting settings and code cannot be saved with the web template.  So the marketer or content author must remember to enable this setting and add the javascript code to the experience.  If the code is not added, the user will be able to close the experience, but it will display on the next page load since the code to check for the cookie is missing.  One other thing to note, if you change your page targeting settings back to “all pages”, the advanced targeting script is deleted from the experience.  In both cases, ensure that it is easy for content authors to find and reuse.

In my previous blog – Personalization in Sitecore XM Cloud: What’s New, What’s Different, and What It’s Built On!, I explored what makes personalization in Sitecore XM Cloud so powerful – from its cloud-native infrastructure and headless architecture to the built-in rule-based targeting engine. Now, I’m shifting from concepts to implementation. In this post, I’ll walk you through how to enable personalization using analytics identifiers that track and categorize visitor behavior in real time. Then, I’ll show how to use Page Builder to create audience-specific page variants, and personalize components – all with a few clicks, not code.

In Sitecore XM Cloud, personalization happens primarily at the page level. The process revolves around creating page variants and personalizing components. This functionality is fully integrated into Page Builder, allowing you to define variations of the page based on different personalization criteria.

Key Points:

• Personalization is configured directly within Page Builder on a per-page basis.
• You can create page variants – each tailored to specific audiences or conditions.
  • Individual components on the page can be personalized : swapped, hidden and can be edited to show different content
• All of this is managed via the Personalize tab available on the page within Page Builder.

How to Check if Personalization is Enabled:

To determine whether personalization is set up:

• Go to the Page Builder for the desired page.
• Click on the Personalize tab.

If personalization is not enabled, you will see :

• No variant options available.
• A prompt or empty state indicating no personalization rules are define.

If personalization is enabled, you’ll see:

• Variants listed based on configured rules.
• Options to add/edit rules and personalize individual components.

Adding Analytics Identifiers to Enable Personalization

Analytics identifiers are essential for enabling personalization in Sitecore XM Cloud. They help track visitors, manage sessions, and unify data across sites for a complete view of user behavior. Without them, personalization rules and targeted content delivery won’t function. Assigning the same identifier to multiple sites allows for consolidated analytics, providing a holistic view of user engagement across different sites.

Step 1: Access Site Settings

1. Navigate to the XM Cloud Portal: Log in to your XM Cloud environment.
2. Open the Sites Dashboard: In the top navigation bar, click on Sites to view all your sites.
3. Select the Desired Site: Locate the site you wish to configure. Click on the Actions menu (three dots) associated with that site and select Settings.
4. Select the Site hosts: Browse through the options on the left side and select Site hosts option and then select the desired host

Step 2: Add or Assign an Analytics Identifier

1. Navigate to the Analytics and Personalization Tab: Within the site settings, click on the Analytics and Personalization tab.
2. Add Identifier for a Language: In the list of languages associated with the site, click the plus (+) icon next to the language you want to configure

Step 3: Choose Identifier Type:

• • Create a New Identifier: Select the Create new tab.
    • Name the Identifier: Provide a unique name for the analytics identifier.
    • Set Session Timeout: Define the session timeout duration (default is 30 minutes).
  • Assign an Existing Identifier: Select the Assign existing tab.
    • Select Identifier: Choose from the list of existing identifiers available in your environment.

Let’s Personalize a Page in Sitecore XM Cloud

1. Navigate to the Page in the Page Builder

• From the XM Cloud portal, open your site and select the page you want to personalize.
• Once it loads in Page Builder, you’ll see a “Personalize” tab at the top navigation bar if personalization is enabled.

2. Create a Page Variant

• Click on the Personalize tab.
• Select Create Variant.
• Provide a name for the variant (e.g. “Every Monday Campaign”)

• Click Next to proceed to audience configuration.

3. Define the Audience for the Variant

Click Add first condition to define who should see this variant.

Choose from the available conditions such of different tags

• Configure the selected condition using the provided fields.

• You can add multiple conditions using AND/OR logic.

4. Customize the Variant

• Once you click on Save, your variant is created and the audience is defined, you can now edit the variant.
• On the side is a screenshot of the Page Builder that lists down all that we can do with personalization on the page.

• You’ll see a color-coded border or indicator showing that you’re editing a personalized version.
• Each change you make is isolated to that variant and won’t affect the default view.

5. Preview the Variant

• Use the Preview feature to see what the page will look like for the targeted audience.

6. Publish the Variant

• When satisfied, click Publish to activate your personalized variant.
• Sitecore XM Cloud will now automatically show the appropriate variant to users matching the defined audience.

Personalization in Sitecore XM Cloud isn’t just a feature – it’s a strategic advantage. By enabling analytics identifiers and using Page Builder to create tailored experiences, you can deliver the right content to the right audience at the right time. With this setup in place, you’re well on your way to building smarter, more engaging digital experiences.

In the next blog, I’ll take you behind the scenes of how personalized content is actually delivered in Sitecore XM Cloud. We’ll explore the request lifecycle, how the Cloud SDK plays a role in fetching and rendering personalized variants, and the technical flow that powers real-time targeting. This deeper dive will help you understand not just what personalization looks like, but how it works under the hood.

Today in our “We Are Perficient” series, we explore how businesses can take their digital experience to the next level through mobile optimization. In an exclusive conversation with Jonathan Crockett, Managing Director of Go-To-Market, Sales, and Solutions at Perficient, we dive into key strategies to ensure brands deliver seamless, high-impact experiences on mobile devices. 

In today’s digital world, user experience is everything. Companies looking to stand out must provide seamless, personalized, and optimized interactions at every touchpoint. In this video, we explore how the combination of Artificial Intelligence, advanced digital experience strategies, and collaboration with technology leaders like Adobe is redefining the way brands connect with their customers. 

Optimizing for a Mobile-First World 

 Today, most digital interactions happen on mobile devices. Without a well-optimized mobile strategy, brands risk losing conversions and engagement. From ultra-fast loading times to intuitive and accessible interfaces, mobile optimization is no longer optional—it’s essential to improving customer retention and conversion rates. 

 AI-Driven Personalization 

Artificial intelligence is transforming user experiences by enabling real-time personalization based on data. From content recommendations to adaptive interfaces that respond to user behavior, AI helps deliver unique and relevant experiences at every interaction. This not only enhances customer satisfaction but also boosts lifetime value and brand loyalty. 

Adobe and the Digital Strategies Evolution 

As an Adobe strategic partner, Perficient helps businesses unlock the full potential of Adobe’s cutting-edge solutions. From Adobe Experience Manager to Adobe Sensei, our strategies merge creativity and technology to design immersive, scalable, and highly effective digital experiences. 

Ready to Take Your Digital Strategies to the Next Level? 

The future of digital experience lies in personalization, optimization, and continuous innovation. If you’re looking to transform how your customers interact with your brand, Perficient can help. 

Contact us today and discover how we can elevate your digital strategy. 

Shoptalk Spring 2025 in Las Vegas is only a few weeks away, and our experts cannot wait to reconnect with brands and discuss where the industry is headed. They have been busy scheduling meetings, packing their mics, and making predictions about which technologies and strategies retailers and ecommerce brands will be placing their bets on this year.  What do they believe is a safe bet?

Will you be there? Let’s schedule some time to chat over a coffee, tea, or cocktail.

An Agenda that Centers On the Customer

Nothing tells the story of ecommerce and retail this year quite like the topics making up the conference’s agenda. Across the agenda, key themes rise to the top like innovation in retail media, customer centricity, the concept of hospitality within retail, and the transformation of customer journeys using new technologies. Justin Racine, Principal of Commerce Strategy, points out that he is most looking forward to hearing from Liza Lefkowski, Chief Merchant and VP of Stores for Wayfair. She will discuss Muse, their new AI-powered tool for personalized home shopping and how it will lead to better customer experience. Another keynote that our senior strategist, Timm Henderlight, is excited about is “Re-Imagining Gap for a New Golden Age,” presented by Richard Dickson, President and CEO of Gap Inc. While this session focuses on unified commerce, there will be additional sessions on ecommerce personalization and retail media strategies.

Our team is eager to listen in and be a part of the conversation about what it means to be customer-centric and how brands and consumers need to come together to humanize the shopping experience. More than ever, brands are embracing connection with their customers and creating a personal experience rather than a transactional one.

Will Brands Take Risks or Play It Safe?

Our experts are going all-in on several bets that retailers might be taking, including mobile apps, augmented reality, and increased AI usage. The house doesn’t always win, however, and Timm suggests that a few capabilities parallel each other. There’s going to be continued discussion about AI and how it’s going to change the industry, but ample opportunities for personalization at scale are often missed by retailers. We’ll continue to see disconnected experiences, whether customers are searching or browsing, usually due to retailers using different technologies. Customer identity resolution and customer data platforms will continue to play a role and should be part of everyone’s personalization strategy.

As more companies move towards personalization, our team recommends brands keep these key points in mind when deciding on a solution:

1. Primarily ensure you are not creating friction in the experience.
2. Be able to identify the customer both online and offline through previous order history and customer affinities.
3. Track intersession data when a customer is not logged in and augment the experience based on how the customer was attracted to the website.
4. Represent the customer journey from a mobile ad or paid advertisement throughout the entire experience, augmenting based on real-time signals from the customer.

Staying relevant in retail is an ongoing challenge, and it means understanding the customer across all channels. It requires having a clear omnichannel strategy and understanding how the journey inside the store touches the digital footprint. In the future, there’s the potential for beacon technology being implemented in physical retail environments, which will track your movements between departments to give in-store associates access to your previous behaviors. This will help guide the store associates and yourself to purchases you’re most likely to make based on where you’ve been. Of course, there’s so much more beyond this, and our experts can’t wait to meet with brands and discuss new opportunities during the event.

For now, watch your step: the future has a lot in store. Stay up-to-date with all the new innovations in commerce, retail + distribution, and consumer goods.

Will you be there? Let’s schedule some time to chat over a coffee, tea, or cocktail.

Our Adobe experts are heading to Vegas this month to attend Adobe Summit, connect with industry leaders, and learn about Adobe’s latest innovations. The conference will provide plenty of opportunities to learn how to grow your business and deliver exceptional digital experiences.

In the video below, Perficient principals Robert Sumner and Ross Monaghan have identified the top three topics they are excited to hear about: GenStudio, the rise in B2B features, and personalization.

Check out the video and learn more about why they’re excited and make sure to check out all the ways you can engage with us if you’re attending Summit as well.

Watch: Why Our Experts Are Excited About GenStudio, B2B, and Personalization

Meet Us at Adobe Summit

Going to Adobe Summit? Find out how to connect with us!

Learn more. 

Adobe Summit is the platform’s premier digital experience conference. This year it’s being held in Las Vegas at The Venetian Convention and Expo Center, March 18 – 20.

Attending the conference is a great way to learn about the latest digital trends, connect with peers and experts from around the world, and explore Adobe’s vision for the future of AI-powered digital experiences.

As a sponsor, our experts are excited to return to the Summit, connect with industry leaders, and share insights on how to grow their businesses and deliver exceptional digital experiences.

While we’re there, attendees will have several opportunities to engage with us. Read on to learn more about where to find us!

1. Women in Digital Breakfast

This highly popular breakfast event has been a Perficient tradition since 2017 and this year we’re excited to partner with Adobe to share it with Summit attendees again.

Attendees will join us before the opening keynote to grab a bite and have an opportunity to connect with peers and engage in meaningful discussions. Our panel of inspiring women in the digital space will share their journeys, insights, and strategies for success and making an impact in today’s digital landscape.

This year’s event has already sold out, but you can still join our waitlist.

Join the Waitlist

2. AI-Enabled, Consumer-Centric Find Care Experiences Lunch

When: Tuesday, March 18 | 11:30 A.M. – 1:30 P.M.

Where: Grand Lux Café in the Palazzo

What: Healthcare systems and providers are invited to join us for lunch and discover how AI-enabled, consumer-centric experiences can build brand loyalty, support better health outcomes, and improve satisfaction across the full care journey, starting with the steps to choose a provider–a critical decision that signals real-time intent.

Register: How AI-Driven Find Care Experiences Drive Growth and Loyalty

3. Welcome Reception in the Community Pavilion

When: Tuesday, March 18 | 5:30 – 7:00 P.M.

Where: Community Pavilion in The Venetian Convention and Expo Center

What: Stop by booth #1189 and see us! You can meet the team, learn more about Perficient’s capabilities, and enjoy refreshments.

4. Make Marketing Data and Your CDP Work for You Breakfast

When: Wednesday, March 19 | 8:00 A.M. – 9:30 A.M.

Where: Grand Lux Café in the Palazzo

What: Join us for breakfast before the day-two keynote and learn how to make sense of the data you need to meet customer experience objectives, boost your marketing team’s impact, and get the most out of your Adobe Experience Platform investment.

Register: Make Marketing Data and Your CDP Work for You

5. Beyond GenStudio: Crafting a Modern Content Supply Chain Vision Lunch

When: Wednesday, March 19 | 11:30 A.M. – 1:30 P.M.

Where: Grand Lux Café in the Palazzo

What: Join us for lunch before heading back to afternoon sessions and explore why having a clear, strategic vision is essential before deploying new technologies. We’ll discuss how GenStudio and other tools can fit into your existing content workflow to maximize efficiency and creativity.

Register: Beyond GenStudio: Crafting a Modern Content Supply Chain Vision

6. Summit Session: Marketo Engage Data Hygiene Strategies With Qualcomm

When: Thursday, March 20 | 1:00 – 2:00 P.M.

Where: The Venetian Convention and Expo Center

What: Delve into advanced Marketo Engage strategies for maintaining data hygiene using executable campaigns. During this session, you’ll learn how to implement a governance framework for managing required fields and validation rules while improving both the quality of data and the efficiency of your marketing operations.

Add to Schedule: Adobe Summit – Sessions

7. Join Us in The Grand Lux Café at The Palazzo

When: Tuesday, March 18, and Wednesday, March 19 from 8:00 A.M. until 5:00 P.M.

Where: The Grand Lux Café in the Palazzo (Note: The Grand Lux Café at The Palazzo is different from The Grand Lux Café at The Venetian)

What: Located on The Palazzo side of the resort, The Grand Lux Café provides a quiet and comfortable space for meetings with Perficient experts and executives.

To find us, stroll through the waterfall atrium and past the Love sculpture. Head north toward Sands Avenue, through the Palazzo Casino, and you’ll see The Grand Lux in the right corner.

See You at Adobe Summit!

From Sneaks to Bash, and all the innovation in between there is so much to look forward to at Adobe Summit.

No matter what your conference schedule looks like, we hope to see you there.

[BONUS] Join Us After Adobe Summit

Following Adobe Summit, we are co-hosting a virtual Adobe user group meetup to discuss the latest innovations that will be announced at the conference. It’ll be an opportunity to debrief on what attendees learned and what they’re excited about and gain insights from Adobe experts.

Adobe Summit 2025: Top Insights, Favorite Sessions, and What’s Next!

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“Data is everywhere—so how do we make it work for us?” 

Imagine walking into your favorite store, and before you even reach the counter, your phone buzzes with a personalized discount for an item you’ve been eyeing. This isn’t the future—it’s happening now. Adobe and Perficient are revolutionizing digital experiences, making personalization smarter, faster, and more intuitive.

Ross Monaghan, Principal of Perficient’s Adobe practice, breaks it down: “There’s a lot of different parts of a customer that are left in a multitude of places. Some individuals may have multiple devices, in-store experiences—there’s a lot of data to stitch together.” The challenge? Unify this scattered data into a single, actionable profile. The solution? Adobe’s AI-powered ecosystem, coupled with Perficient’s expertise, turns raw data into seamless, hyper-personalized experiences.

Why Data Readiness is the Key to Success 

Most businesses have enormous amounts of data but struggle to use it effectively. Often, IT controls the data, leaving marketers without the access they need. Perficient helps bridge this gap through its Adobe Data Factory Jumpstart, allowing marketing and IT teams to collaborate, unify attributes, and act on real-time customer insights.

“We bring all those different sources of data together and unify them within a profile that’s constantly enriched,” Ross explains. This means that every new interaction—whether online, in-store, or via mobile—enhances the customer’s profile, allowing brands to communicate with precision, relevance, and consistency.

The Future is AI-Driven & Dynamic 

Adobe Experience Cloud is a game-changer, enabling businesses to leverage AI-powered automation for content creation, audience segmentation, and journey optimization. Instead of relying on manual A/B testing, companies can now dynamically generate and deploy personalized ads, website experiences, and messaging in real time.

“Leveraging Adobe’s GenStudio and Firefly, we can dynamically create new imagery and messaging at scale,” says Ross. “This isn’t about replacing creativity—it’s about amplifying it.” The result? Highly relevant, on-brand experiences that resonate with customers and drive conversion.

Personalization That Delivers Results 

True personalization is about being in the right place, at the right time, with the right message. With Adobe Journey Optimizer, brands can send contextual notifications based on real-time triggers. Picture this: A loyal customer enters your store, and their phone alerts them to use their $20 loyalty reward—right at the perfect moment.

Ross highlights the power of this, “These are highly relevant contextual experiences that matter, and Adobe’s experience platform really allows you to satisfy that end-to-end.” By leveraging AI-driven insights and real-time customer profiles, businesses can enhance loyalty, increase engagement, and maximize revenue.

 The Perficient Advantage: Turning Data into Actionable Personalization 

Implementing personalization at scale isn’t easy. Data readiness, AI adoption, and seamless customer journeys require the right strategy and execution. As an Adobe Platinum Partner, Perficient has the expertise to help businesses unlock their full digital potential.

“These are complex topics, but Perficient is ready to help you take your digital marketing to the next level,” Ross assures. Whether you’re looking to optimize your content strategy, enhance your customer journey, or scale your personalization efforts, our team is ready to bring your vision to life. Let’s unlock the full potential of your digital marketing strategy together.

Get in touch with us today and take the next step toward digital excellence. 

Months before the ball even dropped, our experts were analyzing the trends they believed would shape the retail and commerce landscape in 2025. To confirm the hypotheses, we attended NRF: Retail’s Big Show in New York City. Namely, Justin Racine, Principal of Commerce Strategy, and Zach Zalowitz, Principal of Order Management, attended and shared their preliminary thoughts for the 2025 show. When the dust settled, two major themes emerged.

The first theme is brands humanizing experiences with their consumers. Justin Racine explained that he had heard a lot about this during 2024, with organizations beginning to emulate niche brands by creating and cultivating consumer communities. This involves bringing together like-minded people who share interests and products, fostering a herd culture where they can share buying experiences and personal lives. In 2025, it looks like these brands are all-in on this approach.

The second theme is agentic AI, especially focusing on AI acting without human intervention. This trend may sound more like science fiction, but we’re already so close to an age where AI understands your buying behaviors and automatically purchases products for you. For example, in the cosmetics space, AI could learn your preferences for products like lipstick or eyeliner based on past purchases, engaged content, and social media activity, and start ordering these products for you automatically.

Let’s dive into what they saw at the show that confirmed their suspicions.

The Big Show’s Big Takeaways

Before taking on a full day at the show, Perficient hosted a breakfast with our partner Coveo – leader in smart search — for a morning mix-and-mingle event. The topic? To discuss how AI is reshaping the future of e-commerce and consumer experience. Coveo’s smart search capabilities have greatly improved B2C commerce sites that have had poor search relevance, and we have partnered with them to generate conversions by leveraging multiple complex AI models for optimized merchandising, product placement, and page views. This in turn has driven billions of desktop and mobile views for various brick-and-mortar and online retailers – an incredible advancement that will continue to grow in 2025.

During the show, there was an emphasis on AI, specifically around customer experience and operational innovation AI use cases. This was exemplified during Nvidia’s session about Real-World AI. They’ve built some incredible AI-backed programs, particularly around digital twins for some of the world’s largest brands: L’Oréal, Walmart, and Lowe’s. From their work with L’Oréal’s creative team to speedily deliver new campaigns, to their project for crucial forecasting of inventory for accurate and efficient supply chains at Walmart, Nvidia’s AI initiatives were some of the most cutting-edge use cases we’ve seen to date.

As Justin and Zach walked the NRF show floor, they met with brands and vendors to get their thoughts on the year ahead. Rohit Goyal, CEO of inriver, expressed hope that in 2025 we’ll start to see real deployments of AI, along with value at scale. Dominick Miserandino, CEO of RetailWire, expressed that we’re getting used to AI, we’re familiar with it, and we’re not surprised when it gives us really bad or good answers. He believes because of this normalization of AI, we should start to see greater implementation in the year to come. Kristen Naragon, Chief Strategy Officer of Akeneo, highlighted that 2025 is the year of AI in product experiences. She noted that business innovation will have to occur, especially surrounding the use of customer data and employee .

NRF 2025 highlighted two pivotal trends, the humanization of consumer experiences and the rise of agentic AI, with both set to transform the retail and commerce landscape in the years to come. As brands continue to focus on creating community-driven interactions and AI leads the way for smarter, enhanced interconnected organizational capabilities, e-commerce is poised for significant innovation.

Learn more about our commerce expertise.

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Artificial Intelligence (AI) is revolutionizing B2B ecommerce, enabling capabilities such as personalized product recommendations, dynamic pricing, and predictive analytics. However, the effectiveness of these AI-driven solutions depends heavily on the quality of the underlying data. Despite AI’s potential, poor data governance remains a significant challenge in the industry. A recent Statista survey revealed that 25% of B2B ecommerce companies in the United States have fully implemented AI technologies, while 56% are experimenting with them.

As AI adoption grows, B2B companies must address data quality issues to leverage AI’s benefits fully. Anyone who has spent time in the B2B industry will acknowledge that quality data is often a struggle. This article explores the critical importance of clean data in AI applications and offers strategies for improving data governance in the B2B ecommerce sector.

Common Symptoms of Bad Data Governance

Bad data governance is a pervasive issue in the B2B ecommerce landscape, particularly in industries like manufacturing, where complex supply chains and product catalogs create unique challenges. Here are some of the most common symptoms:

1. Duplicate Records: Customer and product data often contain duplicate entries due to inconsistent data entry processes or a lack of validation protocols. For example, a single customer might appear in the database multiple times with slight variations in name or contact information, leading to inefficiencies in communication and order processing.
2. Inconsistent Formatting: Manufacturing and distribution often involve extensive product catalogs, and inconsistencies in SKU formats, product descriptions, or units of measurement can disrupt operations. For instance, some entries might use “kg” while others use “kilograms,” confusing systems and causing inventory management and procurement errors.
3. Outdated or Missing Data: Stale data, such as outdated pricing, obsolete product details, or inactive customer accounts, can lead to misinformed decisions. Missing data, like incomplete shipping addresses or contact details, can result in delayed deliveries or lost opportunities.
4. Siloed Data Systems: Many B2B companies, especially in manufacturing, rely on disparate systems that don’t communicate effectively. A lack of integration between ERP systems, CRMs, and ecommerce platforms leads to fragmented data and manual reconciliation efforts, increasing the risk of errors.
5. Unreliable Vendor and Supplier Information: Manufacturing businesses often deal with a large network of suppliers, each with varying formats for invoices, contracts, and delivery schedules. Poorly managed supplier data can result in delayed production, stockouts, or overordering.

Why is Bad Data Governance So Prevalent in B2B Manufacturing?

Unlike B2C industries, where streamlined data processes are often a core focus, manufacturing businesses face unique challenges due to their operations’ complexity, reliance on legacy systems, and decentralized structures. Understanding why these problems are so prevalent is key to addressing the underlying causes and fostering long-term improvements.

1. Complexity of Operations: Manufacturing involves numerous moving parts—raw materials, suppliers, distributors, and customers—making data governance inherently more challenging. The sheer volume of data generated across the supply chain increases the likelihood of inconsistencies.
2. Legacy Systems: Many B2B manufacturing companies rely on outdated legacy systems not designed for modern ecommerce integration. These systems often lack robust data validation and cleaning mechanisms, perpetuating bad data practices.
3. Decentralized Operations: Manufacturing companies frequently operate in multiple locations, each with its own systems, processes, and data entry standards. This decentralization contributes to a lack of standardization across the organization.
4. Focus on Production Over Data: In traditional manufacturing mindsets, operational efficiency and production output take precedence over data accuracy. Thus, data governance investments may be considered a lower priority than equipment upgrades or workforce training.
5. Limited Awareness of the Impact: Many B2B organizations underestimate the long-term impact of bad data on their operations, customer satisfaction, and AI-driven initiatives. The focus often shifts to immediate problem-solving rather than addressing root causes through improved governance.

By recognizing these symptoms and understanding the reasons behind poor data governance, B2B manufacturing companies can take the first steps toward addressing these issues. This foundation is critical for leveraging AI and other technologies to their fullest potential in ecommerce.

Why Clean Data Governance is Non-Negotiable in the AI Era

AI thrives on data—structured, accurate, and relevant data. For B2B ecommerce, where AI powers everything from dynamic pricing to predictive inventory, clean data isn’t just a nice-to-have; it’s the foundation for success. Without clean data governance, AI systems struggle to provide reliable insights, leading to poor decisions and diminished trust in the technology.

As the B2B commerce world embraces AI, those who recognize and prioritize addressing a systemic industry problem of bad data will quickly move to the front of the pack. Garbage in, garbage out. Implementing AI tools with bad data will be doomed to failure as the tools will be ineffective. Meanwhile, those who take the time to ensure they have a good foundation for AI support will overtake the competition. It’s a watershed moment for the B2B industry where those who recognize how to get the most value out of AI while those who refuse to alter their own internal workflows because “that’s the way it’s always been done” will see their market share diminish.

1. Accuracy and Relevance: AI models rely on historical and real-time data to make predictions and recommendations. If the data is inaccurate or inconsistent, the AI outputs become unreliable, directly impacting decision-making and customer experiences.
2. Scalability and Growth: In an era where B2B companies are scaling rapidly to meet global demands, clean data ensures that AI systems can grow alongside the business. Bad data governance introduces bottlenecks, stifling the scalability of AI-driven solutions.
3. Customer Experience: AI-powered personalized recommendations, accurate delivery timelines, and responsive customer service are critical to building customer trust and loyalty. These benefits rely on clean, well-governed data. A single misstep, like recommending the wrong product or misquoting delivery times, can damage a company’s reputation.
4. AI Amplifies Data Issues: Unlike traditional systems, AI doesn’t just process data—it learns from it. Bad data doesn’t just result in poor outputs; it trains AI systems to make flawed assumptions over time, compounding errors and reducing the ROI of AI investments.
5. Competitive Advantage: Clean data governance can be a differentiator in a competitive B2B market. Companies with well-maintained data are better positioned to leverage AI for faster decision-making, improved customer service, and operational efficiencies, giving them a significant edge.

Ignoring data governance in the AI era isn’t just a missed opportunity—it’s a liability. Poor data practices lead to inefficient AI models, frustrated customers, and, ultimately, lost revenue. Moreover, as competitors invest in clean data and AI, companies with bad data governance risk falling irreparably behind.

Clean data governance is no longer optional; it’s a strategic imperative in the AI-driven B2B ecommerce landscape. By prioritizing data accuracy and consistency, companies can unlock AI’s full potential and position themselves for long-term success.

How B2B Companies Can Address Bad Data Governance

Tackling bad data governance is no small feat, but it’s a journey worth undertaking for B2B companies striving to unlock AI’s full potential. The solution involves strategic planning, technological investment, and cultural change. Here are actionable steps businesses can take to clean up their data and ensure it stays that way:

1. Conduct a Comprehensive Data Audit
2. Standardize the Data Entry Process
3. Implement Master Data Management (MDM)
4. Leverage Technology for Data Cleaning and Enrichment
5. Break Down Silos with Integration
6. Foster a Culture of Data Ownership
7. Commit to Continuous Improvement

The first step is conducting a thorough data audit—think of it as a spring cleaning for your databases. By identifying gaps, redundancies, and inaccuracies, businesses can reveal the full extent of their data issues. This process isn’t just about finding errors; it’s about creating a baseline understanding of the company’s data health. Regular audits prevent these issues from snowballing into more significant, costly problems.

Once the audit is complete, it’s time to set some ground rules. Standardizing data entry processes is critical for ensuring consistency. Clear guidelines for formatting SKUs, recording customer details, and storing supplier information can prevent the chaos of mismatched or incomplete records. Employees should be trained on these standards, and tools like automated forms or validation rules can make compliance seamless.

Of course, even the best data entry standards won’t help if different systems across the organization aren’t communicating. That’s where Master Data Management (MDM) comes in. By centralizing data into a single source of truth, companies ensure that updates in one system are automatically reflected across all others. With MDM in place, teams can work confidently, knowing that their data is accurate and consistent.

But standardizing and centralizing aren’t enough if you’re already sitting on a mountain of messy data. Performing this step by hand is significantly time-intensive. Enter data cleaning and enrichment tools. AI-powered solutions can quickly identify and correct errors, deduplicate records and fill in missing fields. These tools don’t just clean up the past; they automate routine processes to keep data clean moving forward.

For many B2B companies, fragmentation is one of the biggest hurdles to clean data. Silos between ERP systems, CRM platforms, and ecommerce tools create inconsistencies that ripple across the business. Breaking down these silos through system integration ensures a unified flow of data, improving collaboration and decision-making across departments. This requires a thoughtful integration strategy, often with the help of IT experts, but the payoff is well worth the effort.

Clean data isn’t just a technical problem—it’s a cultural one. Companies must foster a culture of data ownership, where employees understand the importance of the data they handle and feel accountable for its accuracy. Assigning clear responsibilities, such as appointing a Chief Data Officer (CDO) or similar role, can ensure that data governance remains a priority.

Finally, data governance isn’t a one-and-done project. Continuous improvement is essential. Regular review of data policies and feedback from team members help refine processes over time. Establishing KPIs for data quality can also provide measurable insights into the success of these efforts.

By taking these steps, B2B companies can move from reactive problem-solving to proactive data management. Clean, well-governed data isn’t just the backbone of AI success—it’s a strategic asset that drives better decisions, smoother operations, and stronger customer relationships. In an increasingly data-driven world, those who master their data will lead the way.

Conclusion: Turn Your Data into a Competitive Advantage in the AI Era

In the rapidly evolving landscape of B2B ecommerce, integrating AI technologies offers unprecedented opportunities for growth and efficiency. However, as we’ve explored, the effectiveness of AI is intrinsically linked to the quality of the underlying data. Companies risk undermining their AI initiatives without robust data governance, leading to inaccurate insights and missed opportunities.

Perficient stands at the forefront of addressing these challenges. With extensive experience in implementing comprehensive data governance frameworks, we empower B2B organizations to harness the full potential of their data. Our expertise encompasses:

• Product Information Management (PIM): We assist in managing all aspects of your product data—from SKUs and descriptions to stock levels and pricing—ensuring consistency and accuracy across all platforms.
• Digital Asset Management (DAM): Our solutions help organize and distribute digital assets related to your products, such as photos and videos, enhancing the efficiency of your operations.
• Data Integration and Standardization: We streamline your data processes, breaking down silos and ensuring seamless communication between systems, which is crucial for effective AI implementation.

Investing in clean data governance is not just a technical necessity but a strategic imperative. With Perficient’s expertise, you can transform your data into a powerful asset, driving informed decision-making and sustainable growth in the AI era.