retention in 2025: EML, SMS, AI, and a whole lot of learning

We’re halfway(ish) through 2025, so I’m taking a minute to look back—and think ahead.

Here’s the short version:

• Retention is harder this year.

• Email metrics are shifting (again).

• The real impact happens after the inbox.

• AI is speeding things up and changing the game.

• And, I’m still learning.

If you’re in the world of retention marketing, this one’s for you. ⤵

Where I’m At Now

Like most of you, I can’t believe we’re already halfway through 2025. And what a wild start it’s been. In the DTC world, things feel chaotic—but if I’m being honest, everything feels chaotic right now.

Here’s what’s stood out so far:

Retention is harder this year.
There’s a lot of uncertainty in the market—and customers are feeling it. They’re spending differently than they did even a year ago. For marketers, that means the old playbook might not cut it anymore. Heck, even last year’s playbook might be out of date.

We have to understand customers in a new way—tracking shifts in buying behavior, noticing how (and when) people engage, and figuring out how to earn loyalty that lasts. It’s not just about getting the sale—it’s about becoming the product they choose when they do decide to spend.

Email metrics keep evolving.
Remember when Open Rates were the thing? Now, they’re mostly just a directional signal—great for deliverability, less helpful for measuring engagement.

Just as we’ve settled into this, another shift is happening, this time with click rates. 

AI tools and non-human activity are muddying the waters. Clicks still have value—but they need more context than they used to. These days, I care less about whether someone clicks—and more about what they do after. That’s where the real story starts.

Where I’m Leaning In

So, where am I leaning in for the rest of the year?

I’m reframing email and SMS as more than just communication channels. Anyone deep in these channels already knows they’re powerful growth levers. The real challenge? Helping the rest of the company see them that way, too.

It’s not about sending another blast—it’s about identifying the broader gaps, and figuring out where email or SMS can actually move the needle.

For example, when we saw a dip in Month 1 retention, we dug into the data and realized new customers weren’t reaching their ‘aha’ moment fast enough. That insight led to a revamped post-purchase flow with clearer value props—designed to educate and guide customers to value faster.

Here’s a shift I’ve been making:
When I’m speaking with the broader company, I don’t lead with program-level metrics. I start with the business problem—and then show how email or SMS can help solve it.

Within my team, I’m tracking program health closely. But outside of it, I rarely bring up specific metrics unless they’re unusually strong or clearly signaling an issue. A 2% click rate doesn’t mean much to someone who isn’t thinking about click rates all day.

It’s easy to get caught up in opens, clicks, and unsubscribes—but those numbers don’t tell the full story. Instead, focus on business KPIs like revenue and retention.

If revenue is up, great—what messaging helped drive that?
If retention is down, where are we losing people, and how can lifecycle messaging help close that gap?

It’s relatively easy to manipulate channel metrics. It’s harder—but far more impactful—to show how email and SMS are driving the outcomes that actually matter to the business.

AI and the Workflow Shift

I’d be remiss not to talk a little bit about AI. 

At the start of the year, I was curious—but honestly didn’t know where to start or what would actually be useful. Over the past few months, though, I’ve gotten into a groove—using ChatGPT for brainstorming and leaning into Iterable’s AI-powered features. 

One mindset that’s really stuck with me: never start with a blank page.

Now, if I’m feeling stuck, I’ll drop a quick brain dump into ChatGPT to get things moving. Whether it’s outlining ideas or organizing my thoughts, it helps me get going faster—and spend more time refining, less time staring at the cursor.

None of this is groundbreaking. But it’s helped me shift how I work. And it’s made me more comfortable exploring what else AI can do.

Wrapping it Up

If there’s one thread running through all of this, it’s that I’m still learning. Always.

Retention is harder. Metrics are shifting. AI is changing the way we work. There’s no one playbook anymore—not for lifecycle, not for growth, not for customer engagement. That’s what makes this work challenging. And also what makes it exciting.

Thanks for reading. More to come.