The rapid growth of predictive analytics is being fueled by advancements in AI and machine learning—giving marketers the ability to analyze vast datasets, anticipate customer behavior, personalize campaigns, and drive higher ROI.
But technology alone isn’t enough. To succeed, brands need the right strategy, skillsets, and systems in place.
That’s exactly what Ryderwear—an activewear brand operating globally across e-commerce and physical gyms—set out to build. Faced with fragmented data and limited internal resources, Ryderwear transformed its marketing approach with SAP Emarsys and predictive analytics. The result? A 4x increase in email revenue, a smarter automation engine, and a lean, scalable strategy.
This article breaks down the real-world steps Ryderwear took to unlock sustainable growth using predictive marketing—and what you can learn from their journey.
Ryderwear's Data Challenges: A Closer Look
Like many fast-growing brands, Ryderwear knew they were sitting on valuable customer data—but couldn’t unlock its full potential. The biggest issue? Disconnected systems and an overreliance on manual processes.
“When I first came on board, email revenue contribution was sitting at about maybe 4–5% of the business. Now we’re sitting at just under 20%.”
Data silos and fragmentation
Ryderwear’s customer data was scattered across platforms, leading to:
- Inconsistent profiles across tools and touchpoints
- Limited visibility into the full customer journey
- Inefficient campaigns due to incomplete insights
- Inability to build or trust predictive models
These data silos prevented Ryderwear from gaining a single customer view, meaning the team was working with assumptions—not real-time, data-driven insights.
Expertise gap in advanced analytics
Ryderwear also lacked internal expertise in building and interpreting machine learning models. Without dedicated analysts or data scientists, their lean CRM team struggled to:
- Translate data into actionable strategy
- Build predictive segments or lifecycle models
- Understand which customers were most likely to churn, convert, or spend more
And with a team of one running CRM across global markets, the margin for error was tight.
“I’m a team of one. We operate Ryderwear out of the US, UK and EU and I manage the loyalty platform as well. [...] The fewer internal barriers there are, the quicker you can get things to market.”
How Ryderwear Built a Smarter, Faster Marketing Engine
Ryderwear did more than just invest in technology—they built a foundation for smarter, more sustainable marketing. By unifying their data, upskilling their team, and partnering strategically with SAP Emarsys, they unlocked the full potential of predictive analytics.
Creating a unified data foundation
To solve for fragmented customer data, Ryderwear prioritized full data integration. Working with SAP Emarsys, they connected key systems and built a centralized view of their audience—eliminating duplication, outdated information, and blind spots across channels.
This gave them:
- A real-time, unified customer profile
- Clean, consistent data across platforms
- A reliable foundation for segmentation and personalization
- The ability to act on insights quickly
By taking full advantage of pre-built Emarsys integrations, Ryderwear reduced complexity and accelerated time to value—without needing heavy developer support.
Building internal expertise through training
Technology only works when your team knows how to use it. That’s why Ryderwear invested in upskilling—through hands-on experimentation, data-driven testing, and a willingness to break things in the name of learning.
Justin didn’t need a large team. He needed autonomy, curiosity, and a culture that supported testing and iteration.
“My boss empowers me because he's confident that every change that I make, good or bad, it's going to be a learning. If I break something, [my boss] doesn’t care. At the end of the day, we’re not saving lives—we’re sending emails.”
This mindset empowered him to:
- A/B test relentlessly (even “off-brand” ideas)
- Make fast decisions without heavy approvals
- Iterate automations continuously for better results
- Trust the data—even when it challenged assumptions
Strategic partnership with SAP Emarsys
Ryderwear’s success wasn’t built in isolation. Their partnership with SAP Emarsys gave them access to:
- Predictive analytics tools built for marketers
- Strategic support on implementation and optimization
- AI-driven capabilities like Max AI for engagement and churn prediction
- A flexible platform that adapts to a lean, agile team
By combining platform capabilities with a bold, data-driven culture, Ryderwear set itself up for lasting, scalable success.
How Ryderwear Turned Predictive Analytics into Performance
With a unified data foundation and growing internal expertise, Ryderwear began implementing predictive analytics across their marketing strategy. The result? Smarter decisions, stronger customer experiences, and significantly improved performance—especially through automation and AI.
Enhancing marketing with automation and AI
Best practice: Use AI and automation to predict customer needs, streamline execution, and deliver the right message at the right time—without relying on manual effort.
How Ryderwear did it: Ryderwear embedded automation across their lifecycle programs, particularly email. They shifted away from static campaign blasts to predictive, data-driven flows that adapt to customer behavior.
By focusing on automated journeys, they were able to:
- Forecast engagement patterns and send at optimal times
- Personalize offers and content based on real-time behavior
- Reduce manual workload and increase scalability
- Shift revenue from campaign-led to automation-led
“Campaign revenue was bringing in about 80%, automation was 20%. Now it’s flipped—automation revenue is 80%, and that’s really where you should be aiming for.”
Utilizing machine learning for customer insights
Best practice: Machine learning surfaces patterns in customer behavior to identify top-value segments, forecast next purchases, and drive upsell opportunities—all without guesswork.
How Ryderwear did it: By using tools like Max AI within Emarsys, Ryderwear removed the need for assumptions or manual list building. Instead, they relied on AI to:
- Identify high-value customers and loyalty triggers
- Predict who was likely to churn—and when
- Automatically adjust timing, content, and offers based on engagement signals
This allowed Ryderwear to confidently reduce send volumes to unengaged users—boosting deliverability and efficiency—while personalizing experiences for their most valuable segments.
“I can rely on the machine to tell me when a customer is going to engage or when they’re going to defect... It takes the guesswork out.”
Privacy-compliant data management
Best practice: As predictive marketing evolves, so must your approach to privacy. Ensure data practices are transparent, consent-driven, and aligned with global regulations.
How Ryderwear did it: Working closely with SAP Emarsys, Ryderwear ensured their predictive analytics strategy was fully compliant by:
- Centralizing consent management across all touchpoints
- Applying role-based access controls and encryption
- Maintaining audit-ready data trails for GDPR/CCPA compliance
This balance of personalization and privacy helped them build trust while still delivering tailored customer experiences at scale.
What Ryderwear Achieved – and How They Made it Happen
Predictive analytics has become a core part of Ryderwear’s marketing engine, driving clear and sustained improvements across revenue, engagement, and team efficiency.
Email marketing performance
Email has gone from a minor contributor to a major revenue channel. With automation and AI in place, Ryderwear achieved:
- An increase in email-driven revenue from 4–5% to nearly 20%
- Better engagement thanks to relevant, behavior-based messaging
- Higher conversion rates through personalized product recommendations
- More efficient use of time and resources with automation doing the heavy lifting
Learn more about SAP Emarsys AI-driven email marketing, where industry-leading deliverability meets real-time AI-powered personalization.
Stronger segmentation and personalization
With unified data and predictive tools in place, the team could finally act on what they knew about their customers—targeting people more precisely and building journeys that felt tailored, not generic.
This shift helped them:
- Spot high-value segments earlier in the lifecycle
- Anticipate what customers would want next—and promote accordingly
- Increase average order value by 15% with more targeted messaging
- Improve satisfaction by reaching people at the right time, with the right content
These improvements gave Ryderwear a much clearer picture of who their customers are and how to connect with them more meaningfully. With stronger segmentation and smarter personalization, their marketing now works harder, feels more relevant, and drives better results—without adding complexity.
Learn more about the power of AI segmentation with Ryderwear’s Story.
Greater operational efficiency
Behind the scenes, Ryderwear also streamlined their internal processes. With better data and automation in place, the team could move faster and plan smarter.
They saw:
- More accurate inventory planning based on demand patterns
- Smarter budget allocation across channels
- Fewer resources spent on low-performing campaigns
- Faster decision-making rooted in real-time insights
And all of this came from a single-person CRM team empowered by the right tools and a culture of experimentation.
The Future of Predictive Analytics
With a strong foundation in place, Ryderwear continues to explore new ways to evolve its predictive marketing strategy—focusing on more advanced AI models, deeper customer segmentation, and even more personalized customer experiences.
AI-driven analytics models
Ryderwear is now testing more sophisticated models that allow for:
- Deeper insights across larger and more complex datasets
- Improved accuracy in predicting customer behavior
- Detection of subtle patterns that are often missed with manual analysis
- More tailored personalisation across key channels
These models are helping the team move faster from insight to action—without needing to increase headcount or rely on external support.
Machine learning for high-value segmentation
As their customer base grows, Ryderwear is using machine learning to sharpen its understanding of value-based segments. That means:
- Prioritising the most engaged, profitable customers
- Identifying churn risks before they drop off
- Discovering new audience clusters based on real-time behavior
- Targeting retention and loyalty efforts with greater precision
By focusing their attention on the right people, Ryderwear is getting more from every campaign and creating better customer experiences in the process.
Enhanced personalised marketing
Predictive analytics also supports a more personalised approach to content, offers, and timing—especially as expectations around relevance continue to rise.
The team is using their insights to:
- Deliver more meaningful messages based on real-time intent
- Tailor promotions based on predicted customer value
- Show personalised product recommendations that actually convert
- Choose the right channels for each customer, not just the most convenient ones
These advances are helping Ryderwear build stronger relationships with their customers—and ensuring each touchpoint feels timely, thoughtful, and on-brand.
What Marketers can Learn from Ryderwear’s Success
Ryderwear’s approach to predictive analytics offers clear lessons for any marketing team looking to improve performance with greater precision and less manual effort.
Start with data unification: Fragmented data makes accurate predictions nearly impossible. Building a centralized, real-time customer view is the first step to meaningful automation and personalisation.
Invest in people, not just platforms: Technology only delivers value when your team knows how to use it. Give marketers the time, training, and freedom to test, learn, and iterate.
Partner strategically: Working with a platform like SAP Emarsys gave Ryderwear the tools and guidance to move fast without a large team or in-house data science resources.
Focus on actionable insights: Insights are only valuable when they lead to action. Ryderwear turned predictions into personalised campaigns, smarter segmentation, and better timing across the customer journey.
Empower marketers to test and adapt: Removing internal barriers unlocked faster execution and stronger results. Let your marketers experiment, A/B test, and make decisions based on what the data says—not just what feels safe.
Final Thoughts
Predictive analytics is no longer a “nice to have.” It’s a competitive advantage—and Ryderwear proves that you don’t need a huge team or a complex tech stack to make it work.
By unifying their data, empowering their CRM lead, and leaning into automation, Ryderwear transformed the way they connect with customers. Email revenue quadrupled. Campaigns became smarter and more relevant. And the entire strategy became faster, more agile, and easier to scale.
With SAP Emarsys, Ryderwear found a platform that gave them both the flexibility to experiment and the intelligence to make every message count. And they’re just getting started.
Ready to turn your marketing data into real results?
Discover what SAP Emarsys can do for your brand. Book a demo today.
About the author
Kirk Donlan is a Product Marketing Manager at SAP Emarsys, specializing in D2C marketing, product messaging, and go-to-market strategy. He crafts compelling content that helps brands connect with consumers, increase engagement, and drive measurable growth. With expertise in sales enablement and marketing strategy, Kirk translates complex solutions into clear, actionable insights for D2C brands.
