How Made In Cookware Drove 108x All-Time SMS ROI With Attentive’s AI-Powered Targeting

The challenge

Converting during high-intent moments in a high-consideration category

Cookware is an investment purchase, and Made In sees the strongest buying intent during seasonal peaks and major promotions. The team plans for these moments throughout the year, from recurring promo periods like Presidents’ Day, Memorial Day, and Labor Day, to product launches and the holiday season. 

To convert when intent peaks, Made In spends the rest of the year building confidence through education, so customers already understand the product quality and how to use it when promotions hit.

Scaling fast-moving messaging across multiple markets

Made In runs four international programs, treating the US, Canada, the UK, and Australia as separate markets, with continued expansion plans. During peak periods, messaging changes quickly across “sale chapters,” and operational efficiency becomes a requirement when updates need to roll out across multiple regions at once.

Primary goals

Across high-traffic periods, two priorities guided the plan:

• Capture as many new subscribers as possible across SMS and email during the highest traffic period of the year
• Personalize the customer journey while keeping execution efficient across markets

The solution

Made In uses Attentive to grow its subscriber base ahead of peak traffic periods, personalize messaging across campaigns and automations, and reduce the operational load of rapid changes during high-intent moments. The program is supported by a foundation of educational content, AI-driven acquisition and optimization, and AI-powered journeys that adapt to each shopper’s context.

Strategy

1) Treat list growth as a peak-season lever, then validate changes before traffic spikes

Made In prioritizes subscriber capture ahead of peak traffic periods, because adding a subscriber during a high-intent moment can still pay off months later through owned-channel nurturing. That means optimizing popups early, pressure testing the experience, and making sure acquisition is performing before traffic ramps.

AI Grow helped replace constant manual testing with a higher-performing, scalable approach. The team A/B tested AI Grow popups against standard popups, validated the lift, then rolled it out broadly ahead of peak traffic so surges in site visits translated into stronger net-new subscriber capture. 

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“Before AI Grow, we were constantly tweaking popup frequency, timing, and placement, trying different delays and page contexts to squeeze out incremental gains. Once we A/B tested AI Grow against our standard popups, the difference was clear, so we made sure it was fully in place going into Black Friday.”
- Kait DeNolf, Lifecycle Marketing Manager, Made In Cookware

2) Run peak periods as “sale chapters,” and shift journeys to match the moment

During peak periods, Made In rotates messaging through distinct sale phases, adjusting promotions and content quickly based on the moment. To keep the experience relevant, the team turns off evergreen flows during key sale windows and runs seasonal automations and journeys that reflect what shoppers need most, including gifting support.

“We turn off evergreen flows during the sale and run holiday-specific automations and journeys instead, with a big focus on gifting. During Q4, we move fast through sale chapters, from early bird to Black Friday, Cyber Monday, Cyber Week, gifting, last-chance holiday shipping, and New Year’s.”
- Kait DeNolf, Lifecycle Marketing Manager, Made In Cookware

Holiday messaging also includes guidance prompts, like asking customers who they’re shopping for, to make decisions easier at checkout.

3) Use AI Journeys to scale personalization and eliminate manual message churn

Peak sale periods require constant updates. AI Journeys reduced the operational burden by allowing the team to schedule sale messaging changes, instead of manually editing 50 to 100 individual flow messages across markets.

Performance exceeded expectations. In a 50/50 split test across the full peak-season window, AI Journeys drove roughly 180% more conversions than standard flows, and the lift was incremental beyond what the team was already doing with a well-mapped, category and product-type journey strategy.

“We already had journeys mapped by category and product type, so personalization was built in. AI Journeys still outperformed what we could do manually, and it felt truly incremental.”
- Kait DeNolf, Lifecycle Marketing Manager, Made In Cookware

4) Apply AI Pro based on message intent, then keep refining

During peak season, Made In uses AI Pro to improve timing, targeting, and recovery journeys, while keeping message strategy aligned to the moment.

Send Time AI
Send Time AI is used when a message can be valid across the day, and timing flexibility can improve engagement. For last-call or launch messaging that needs a specific moment, the team sends at a set time.

Audiences AI
Audiences AI is used to improve both reach and efficiency.

• Inclusions: expand beyond manually built segments by adding subscribers with similar behavior to the selected intent group
• Exclusions: remove subscribers less likely to purchase, reducing unnecessary sends and improving cost efficiency
• Audiences AI inclusions impact: 21% send lift overall

Identity AI
Identity AI helps recover more value from abandonment triggers by recognizing more visitors and increasing the volume of relevant messages.

• Monthly lift: low teens to 20% range
• Weekly aggregate lift: 14%, with a peak week up to 82%
• Lift by journey type: Product View 20%, Page View 13%, Add to Cart 10%

“It’s all about testing and making sure it works for your program. We’re intentional about where we use it, then we keep iterating, because it’s not one-size-fits-all.”
- Kait DeNolf, Lifecycle Marketing Manager, Made In Cookware

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5) Build confidence year-round through “confident and educational” messaging

Made In’s messaging mix combines education, inspiration, and product guidance to reduce friction in a category where customers need to feel confident using what they buy. That includes how-to content (cleaning and usage), guidance for first-time stainless buyers, recipes, and chef storytelling, alongside launches and promotions.

“Our voice is confident and educational. We want customers to trust the quality and feel confident using the product, so we share practical guidance like cleaning and how-to content, plus recipes, inspiration, and how chefs are using our cookware.”
- Kait DeNolf, Lifecycle Marketing Manager, Made In Cookware

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6) Turn platform advantages into measurable list growth, then channel contribution

After migrating ahead of the holiday season, Made In saw meaningful net-new SMS list growth compared to the prior year, and tied the lift to Attentive’s two-tap opt-in experience that reduces signup friction.

As the list scaled over the first 7 to 8 months on the platform, SMS contribution also strengthened. During peak season, SMS and email were neck-and-neck overall, with key days where SMS led.

“When we moved to Attentive, we saw much healthier net-new SMS list growth during the Black Friday season. Two-tap opt-in made a big difference because people can opt in immediately, without needing to reply to confirm.”
- Kait DeNolf, Lifecycle Marketing Manager, Made In Cookware

7) Partner closely to adjust and improve over time

The team actively shares feedback on how experiences show up on-site, including popup frequency concerns, and works with Attentive to adjust configurations and improve performance.

“The support is unreal. The team is responsive, open to our ideas, and quick to help us problem-solve. It feels like a true collaboration, and we can give feedback on how things are working in the real world, then make adjustments from there.”
- Kait DeNolf, Lifecycle Marketing Manager, Made In Cookware

Made In built a year-round education strategy and an execution model designed for fast changes across markets. By validating list growth updates before traffic spiked and using AI-powered journeys to schedule sale messaging shifts, the team reduced manual effort while keeping experiences personalized. With AI Pro, Made In continued to tune timing, targeting, and abandonment recovery based on message intent, then iterated through ongoing testing.

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