Key Takeaways:
- Iterable’s Priya Gill says B2B customer engagement now depends on consistent, connected experiences that build trust over time, not just more campaigns or surface-level personalization.
- Gill argues AI should reduce operational complexity by handling repeatable tasks and helping teams act on signals in context, while humans stay focused on judgment, nuance, and experience design.
Customer engagement is getting harder to earn and easier to lose. B2B buyers are more deliberate about where they give their time, attention, and budget, and they expect every brand interaction to feel relevant, connected, and worth it. For marketers, that raises the bar well beyond campaign execution: success now depends on delivering experiences that build trust consistently across channels and moments.
The Iterable 2026 Customer Engagement Marketing Report captures the tension many teams are navigating right now. Personalization may be more common, but too often it still feels performative rather than helpful. At the same time, marketers are struggling to make sense of fragmented engagement signals and looking for ways to use AI and automation to cut through operational complexity instead of adding to it.
In this Q&A, Iterable CMO Priya Gill shares her perspective on what it takes to meet those rising expectations. Gill discusses how brands can strengthen loyalty and trust in a more selective market, what makes personalization feel meaningful instead of superficial, and how artificial intelligence (AI) can reduce complexity while still leaving room for human judgment where it matters most.
Demand Gen Report (DGR): Priya, thanks for taking time to talk to us today. How can B2B brands build and maintain loyalty when customers are more selective and quick to disengage?
Priya Gill: Thanks for having me. We’re seeing a big shift in how loyalty is earned. Consumers are making much more intentional decisions about where they spend their time, attention, and money, and they’re quicker to disengage when an experience doesn’t feel worth it.
What stood out in our research is that loyalty itself hasn’t disappeared. More than half of respondents said they’ve stayed loyal to brands they trust for over 10 years.
What this tells me is that people are still willing to build long-term relationships with brands, but the expectations are higher now. They don’t expect perfection, but they do expect consistency. Every interaction either builds trust or chips away at it.
DGR: What helps close the gap between marketing activity and the actual customer experience?
Gill: People don’t experience marketing the way marketing teams describe it internally. No one feels a “campaign” or a “workflow.” They just experience whether something feels connected and useful, or whether it feels fragmented and disconnected.
A lot of the issues come from what’s happening behind the scenes. There are still too many systems involved, too many handoffs, and too many moments where context gets lost between teams.
What I’ve seen work better is when teams stay much closer to the experience they’re trying to create for people, rather than the mechanics of how it gets delivered. When that alignment is there, things tend to feel simpler on the outside, even if the work behind it is still complex.
From Connected Experiences to Operational Efficiency
DGR: How should B2B teams think about AI so it reduces operational complexity instead of adding to it?
Gill: A lot of teams are still defaulting to AI as a content tool first, because that’s the most visible output. But generating more content doesn’t really fix the underlying issue most marketing teams are dealing with.
Our research found that 64% of marketers say their personalization efforts are more about optics than impact. That points to a bigger operational challenge underneath the surface, not a creativity problem.
Marketing teams need to look at where AI can remove steps, reduce handoffs, or help people make decisions faster with better context. When that’s done well, AI doesn’t feel like another layer in the stack. It takes work off people’s plates so they can focus more on the parts of marketing that actually require judgment, creativity, and understanding people.
DGR: How can AI be used in a way that actually reduces complexity?
Gill: A big factor here is trust. If teams don’t understand or trust how AI is making decisions, they don’t use it fully, which often leads to duplicate processes and workarounds.
The most effective setups are the ones where AI is clearly scoped: what it owns, what it supports, and where humans stay in control. Without that clarity, AI adds another layer instead of removing one.
DGR: How should teams balance automation with human-led decision-making?
Gill: AI isn’t about replacing people. It’s more about being clear on what each side is actually good at.
There are a lot of operational decisions that systems can handle really well now. Things like timing, routing, optimization. But people are still important for shaping the experience, making judgment calls, and understanding nuance.
Around 70% of teams in our research said they still rely heavily on manual decision-making for day-to-day campaign adjustments, which is where a lot of inefficiency sits. The best balance is when automation quietly handles the repeatable work in the background, and people stay focused on what the experience should actually feel like.
Getting Personalization Right
DGR: What makes personalization actually meaningful, rather than just surface-level customization?
Gill: One big takeaway I found from our research is that a lot of marketers feel their personalization is still more about optics than impact. And people can feel that immediately. If it’s just surface-level, it still feels generic.
We also saw that only about a third of marketers feel confident their personalization is actually influencing behavior in a meaningful way.
The personalization that actually works tends to be much simpler— it’s about timing, context, and understanding what someone is trying to do at that moment. It doesn’t need to feel complicated. In fact, the simpler and more natural it feels, the better it usually performs.
DGR: How do you ensure personalization actually aligns with customer expectations?
Gill: There’s always a balance here between being relevant and going too far. Consumers want experiences that feel useful and tailored, but they’re also much more sensitive to how their data is being used.
We saw in our research that nearly half of consumers say they’re more selective about engaging with brands because of how personalization is handled. That tells you something important. It’s not that people don’t want personalization. It’s that they’re very aware when it feels overdone or intrusive.
The personalization that actually works is the kind that feels almost invisible. It just shows up at the right moment, helps someone move forward, and doesn’t overexplain itself or feel like it’s constantly referencing what a brand knows about them.
DGR: What’s the best way for B2B marketers to act on engagement signals in real time?
Gill: Engagement is situational. Timing, channel fatigue, and incentives all change how engagement signals should be interpreted.
Our research shows how strategic customers have become—for example, 67% of consumers now delay purchases waiting for larger discounts. They’re playing the game here. That kind of behavior means a click or view on its own doesn’t tell you much.
Engagement signals only become useful when you connect them over time and across channels.
Adapting Campaigns for More Strategic Buyers
DGR: How should campaigns evolve to match more selective, strategic customer behavior?
Gill: Consumers are much more aware of how brands show up now. They recognize patterns. They know when something is likely automated or when they’re being guided through a set sequence of messages.
This changes the customer experience completely. Fixed paths don’t hold up anymore because people don’t move in straight lines. What works better is when the experience can adjust based on what someone is actually doing in the moment, instead of assuming what they’ll do next.
It’s less about designing everything upfront and more about staying responsive as behavior changes.
DGR: How can teams make engagement signals more reliable for understanding intent?
Gill: A click or a visit doesn’t tell you intent anymore. People interact across channels in ways that are inconsistent by design. They’ll browse, drop off, come back later, compare elsewhere, and return when the timing is right for them.
The issue I see is that teams still tend to treat each interaction as if it carries meaning on its own. In our research, only about a third of marketers said they feel confident they can accurately interpret intent from engagement data today. That reflects a real gap between the volume of signals available and how usable they actually are.
What works better is stepping away from isolated actions and looking at repeat behavior over time. Whether someone returns, how their channel usage shifts, and what they do across multiple touchpoints.
