What Personalization Looks Like When It’s Profitable

Everyone talks about personalization in email and SMS marketing. But the truth is, most brands are doing it for optics, not outcomes.

Eric Rausch, whose retention agency, New Standard, works with 8- and 9-figure DTC brands, puts it plainly:

“Personalization is currently an industry buzzword. The way most brands approach it, it doesn’t move the needle. Some of it actually wastes time.”

So what does profitable personalization look like?

It’s not first-name tags or weather-based triggers. Real personalization makes an impact only after the foundations are in place. When done right, it improves merchandising, drives better product discovery, and directly increases revenue per email (RPE).

Why personalization should come last, not first

According to Rausch, most retention programs get personalization wrong from the start by skipping the order of operations.

Here’s what the hierarchy should look like:

1. Lead capture: Are you capturing enough emails and phone numbers through optimized popups?
2. Flow optimization: Are your welcome, post-purchase, and abandonment flows tested and dialed in?
3. Merchandising: Are you showing the right products to the right cohort at the right time?
4. Personalization: Is there a meaningful way to personalize that truly improves conversions?

“You’d be surprised how many brands want to personalize based on cold weather or gender but haven’t even tested the first two emails in their flows.”

Skipping the first 3 means that personalization efforts are layered on top of a broken foundation, causing diminishing returns.

Product affinity beats identity-based segmentation

Basic triggers like names or locations don’t make much impact. 

Instead, the most reliable form of personalization comes from product behavior, specifically, product affinity and buying patterns.

“If someone bought Product A, when are they likely to buy Product B? How many days between? What’s the next SKU that performs best in that journey?”

Rausch’s team relies on basket analysis and cohort behavior to determine when and how to show specific products in flows and campaigns. That’s what true behavior-led personalization looks like.

It also avoids the common pitfall of invasive, performative segmentation, like including a customer’s name without any context or targeting based on irrelevant signals like weather or season.

Category-level personalization outperforms SKU-level complexity

Many brands fall into the trap of over-engineering personalization at the SKU level, sending 10–20 hyper-targeted emails based on individual products or attributes.

Rausch has a better benchmark:

“We’ve seen brands translate an email into 22 languages while 90% of the revenue still comes from 1 or 2 versions.”

Instead of micro-segmenting by SKU, he recommends this focused strategy:

• Identify top-converting product categories for each cohort.
• Test broader messages tied to those categories.
• Use those insights to drive performance in key flows like post-purchase and winback.

Category-level personalization is easier to execute, more scalable, and often more effective. It also gives marketers room to test offers, layout, and sequencing—without overfitting based on small data samples.

When to test batch vs. niche personalization strategies

Before diving into dynamic segments, test at the batch level.

When auditing flows, Rausch’s team tests:

1. The offer: What’s the actual hook or incentive?
2. Above-the-fold content: What do you show first? Is there a clear CTA?
3. Merchandising logic: What product is being featured, and where does it lead?
4. Audience-match sanity check: Are you even sending the right message to the right group?

“You’d be shocked how often poor merchandising (not poor segmentation) is the real reason an email fails.”

After these variables have been tested, his team sets up segment-specific logic (e.g., a special offer for protein buyers vs. hydration buyers). This approach ensures that every test is grounded in performance, not assumptions.

TL;DR: What does profitable personalization look like?

• Fix the foundation first: Capture more leads (popups). Optimize your flows (welcome, post-purchase). Test your merchandising.
• Avoid shallow signals: Names, locations, or weather-based triggers don’t drive real impact.
• Start with behavior, not demographics: Use product affinity and buying patterns (not names or weather) to guide what and when you show items.
• Personalize at the category level first: Target segments by product type or journey stage before going SKU-specific.
• Test messaging before segmenting: Validate offers, CTAs, and merchandising logic before layering in segment-specific tactics.
• Ground it in performance: Every personalization layer should be backed by data, not assumptions.

Profit-driven personalization starts with the right data

Even the best personalization strategy falls flat if your audience data is incomplete, outdated, or fragmented across sessions.

That’s where Tie comes in.

Tie helps DTC brands identify anonymous visitors, enrich subscriber profiles, and sync behavior and identity data to your marketing stack, so your emails reach the right person with the right message, every time.

Whether you’re building high-performing flows or refining segments for scale, Tie gives your team the clean, enriched data needed to make personalization truly profitable.

Book a demo to see how Tie helps you drive real revenue from personalization.