B2B marketers are eager to deliver personalized experiences at scale, but the journey often feels overwhelming. Before trying to leap straight into advanced tactics like AI-driven targeting, you need to build the foundation that makes personalization possible.
To cut through the complexity, I spoke with Sam Hofman, Manager of Analytics at JPL, about the practical steps marketers can take to progress along the path to personalization. From establishing clean data practices and integrating systems to testing assumptions and eventually layering in AI, Sam outlines a maturity journey that helps organizations grow at the right pace without skipping the essentials.
Q: If you could give B2B marketers one “quick win” to get more value from their data tomorrow, what would it be?
Sam Hofman: The quickest win is to step back and make sure the basics are in place. Too often marketers rush toward highly personalized campaigns without even being able to measure their funnel stages accurately. Can you clearly identify when someone moves from an initial click or demo request to a marketing qualified lead, a sales qualified lead, and eventually to a closed deal—or a lost opportunity? If you can’t, then that’s the first place to start.
Once that foundation is strong, the next step is to think about who is in each stage. Are they in a particular industry? A specific geography? That’s where segmentation begins. And once you can reliably segment, then you can layer on true personalization.
Think of the path to personalization like a staircase: You don’t jump to the top; you climb step by step. Starting small, proving value and building confidence in the data make the bigger leaps possible later.
Q: What are some practical ways marketers can maintain data hygiene and governance over time, rather than treating it as a one-time project?
Sam Hofman: Think of data hygiene like preventive healthcare—you can’t just clean things once and assume they’ll stay that way. Someone must own it. Governance can’t be everyone’s part-time job; there has to be accountability for keeping data clean and usable.
That responsibility includes enforcing consistent naming conventions, monitoring UTMs and regularly reviewing your tag management setup to clear out legacy tracking that no longer serves a purpose. Beyond the ongoing upkeep, it’s critical to step back every year or two and ask: Does our data structure still make sense for how our business works today?
Organizations change. Campaigns evolve. Without this regular pruning, you’ll end up with cluttered systems that slow everything down.
So, the three keys are:
- Put a system in place
- Assign ownership to maintain it
- Schedule periodic reviews to adapt it as you grow.
Q: How should marketers approach integrating tools like CRM, MAP and analytics platforms to get closer to a single customer view?
Sam Hofman: A single customer view is a worthy goal, but it’s often more aspirational than practical. The reality is that customer journeys are messy. People engage across multiple platforms—your website, product pages, CRM, email—and privacy regulations mean you can’t always stitch everything together into one perfect profile.
That said, the closer you can get, the more powerful your insights become. The first step is to ask: How centralized is our user flow? If most actions happen in one system, integration is much easier. If they’re spread across three or four, then you need a reliable way to tie actions back to a unique identifier.
Even then, don’t let perfect be the enemy of good. If you can’t trace a deal all the way back to a blog post someone read three years ago, that’s okay. Focus on what you can connect, optimize those journeys and keep perspective. Incremental progress still brings you closer to the outcomes you want.
Q: Where do you see AI and machine learning making the biggest impact on personalization in the near term?
Sam Hofman: AI’s biggest strength is pattern recognition—but it needs a lot of data to work well. For organizations with large datasets, AI can power things like predictive lead scoring, instantly flagging which prospects are more likely to convert based on historical trends. That can transform how sales teams prioritize their time.
For companies with smaller datasets, the impact will be different but still valuable. Tools like chatbots can use natural language processing to deliver smarter recommendations or assist users in real time. AI tools can also optimize content delivery—testing subject lines, tailoring email copy or even reordering content in newsletters based on what similar audiences have engaged with before.
The key is to not overestimate what AI can do with limited data. If you have only a handful of leads each month, advanced modeling won’t work. But automation, personalization at the content level and conversational tools can still create meaningful improvements.
Q: Beyond lead generation, what KPIs should marketers use to measure success with personalization at scale?
Sam Hofman: Personalization isn’t just about more leads—it’s about better engagement and faster progression. That means KPIs need to reflect behavior across the funnel, not just at the top.
- Look at email engagement: Are open and click-through rates increasing when you personalize?
- Track funnel velocity: Are prospects moving from awareness to consideration to close faster when they receive tailored content?
- Measure conversion quality: Do personalized experiences lead to higher-value or longer-term customers?
Every business is different, but the key is to align your KPIs with the journey your customers actually take.
Q: What mindset shifts or cultural changes are necessary for organizations to become truly data-first?
Sam Hofman: Being data-first is less about technology and more about culture. First, there’s no shortcut around governance. Clean, accurate data must be the foundation.
Second, organizations need to embrace a hypothesis-driven mindset. Don’t just launch campaigns—form a hypothesis, test it and use the results to guide decisions.
Equally important is how data is shared. Teams don’t need 58 dashboards with hundreds of metrics. They need the right data in the right context so they can act on it.
The role of analytics isn’t just reporting numbers; it’s storytelling with data by framing insights in a way that empowers people to make better decisions.
Ultimately, being data-first means creating a culture where data is trusted, understood and used to continually improve—not where it’s overwhelming, inconsistent or ignored.
Q: If you were advising a CMO, how would you describe the maturity journey from basic segmentation to advanced, AI-driven personalization?
Sam Hofman: The maturity journey is all about building in the right order.
- Step 1: Clean and organize your data
- Step 2: Understand your funnel and how leads move through it
- Step 3: Segment your audience in meaningful ways—by industry, geography or behavior
- Step 4: Layer on testing and personalization before bringing AI into the picture
AI tools can only be as smart as the data they’re given. If your email campaigns are still named “Email1 Copy(1),” no AI system will know how to optimize them. But if your data is structured, clean and well-labeled, AI can enhance your testing and optimization in powerful ways.
Think of AI as an accelerator of good practices, not a replacement for them.
Q: What’s your advice to marketing leaders who want to future-proof their data strategy and stay ahead of the curve?
Sam Hofman: From a technical perspective, avoid vendor lock-in. Choose platforms that give you access to your data and flexibility to adapt. If you rely on a walled garden solution, you’ll face major headaches down the line when you want to evolve your strategy.
From a cultural perspective, take the long view. Don’t try to leap from step two to step 10. Plant your seeds now—invest in data hygiene, governance and thoughtful testing. It might feel slow, but in a few years, you’ll have a healthy, scalable data ecosystem that supports personalization and AI without constant rework.
As the saying goes, the best time to plant a tree was five years ago. The second-best time is now. The same is true for data: start today, and you’ll reap the rewards tomorrow.
Q: Let’s close this interview with one big takeaway on personalization.
Sam Hofman: Personalization is not a single project, it’s a journey. Build strong data hygiene, test continuously, scale responsibly and let AI enhance what you’ve already structured. The path may be gradual, but it’s the only way to reach personalization that truly delivers value for your brand.
Personalization should shorten the distance between first touch and final decision, and your metrics should show whether that’s happening.
About Sam Hofman, Manager of Analytics: Sam leads JPL’s analytics practice, bringing data-driven insights to inform marketing strategies. With expertise in attribution, creative optimization and cross-platform measurement, he empowers clients to achieve targeted business outcomes.
