5 Ways Da Vinci Streamlines Campaign Creation and Personalization
Erica Dingman
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May 30, 2025
Marketers’ Potential Is Limited...
But it’s not due to a lack of creativity or strategic thinking. When it comes down to it, it’s the one resource marketers can’t manufacture: time.
Whether it’s creating countless campaign briefs, juggling marketing calendars, or mapping creatives to segments, marketers are left with little extra time. To produce industry-leading campaigns and drive true business growth, marketers need to embrace a newer, more efficient approach with AI.
There are five tangible ways Da Vinci AI can supercharge your productivity as soon as you add it to your tech stack. Let’s dive right in.
Trade Static Campaigns for Flexible Emails at Scale—Without the Manual Lift
Typically, marketers create a few different versions of their emails to send to pre-determined segments in order to reach millions of customers in their batch campaign program. This leads to a time-consuming process that still doesn’t result in a tailored send for every recipient.
But with Da Vinci, marketers no longer need to build one-off campaigns for a few segments. They can take a new approach by keeping all of their creative assets in Da Vinci’s content library, allowing AI to choose the most suitable asset for each subscriber. This automated decisioning approach to personalization not only speeds up marketers’ typical production processes, but it also ensures that the chosen assets are always relevant to each customers’ individual preferences.
Turn One-and-Done Creatives Into Impactful, Multi-Use Investments
Every marketer knows how costly creatives are, and spending thousands of dollars can be a challenging pill to swallow when you only use the asset once.
Remember that creative library we talked about? When Da Vinci chooses the most relevant content for each subscriber, that sometimes means forgoing the newest asset in favour of an older creative that will drive higher-value actions from the customer—but not to worry, because marketers can set the shelf life of each asset to ensure that outdated content is never deployed.
On top of that, marketers can also glean greater insights from their creative asset—when it lives in the library, marketers can analyze what types of assets are in high demand and which ones they have in surplus.
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Transform Static Segments into Individualized Stories That Drive Retention
Moving away from manual segmentation doesn’t only accelerate campaign builds and maximize creative investments. Using AI also enhances the output, as every campaign becomes a stepping stone in the subscriber’s brand journey.
Segments don’t reflect the nuances of each customer. For instance, if you’ve purchased golf clubs once, you might automatically be bucketed into a “golf” segment. But what if that customer is more likely to resonate with running-themed creative? Or loungewear?
When every customer receives their own unique mix of content—both tailored to today’s preferences and guiding them towards greater loyalty down the road—they ultimately receive a personalized cadence made just for them, rather than what a brand thinks they want to see. It maximizes today’s revenue, all while strengthening lasting retention.
Balance Quick Wins with Long-Term Customer Value
The more conversions the better…right?
Not quite. Instead, swap short-sighted conversion pushes for ongoing sales to drive steady revenue gains. Marketers need to take into account a plethora of other factors, such as average order value or setting up customers for continual purchasing in the future. That means throwing in a trigger should only be step one.
Da Vinci can optimize conversion-driving messages with personalization, but that only helps drive sales today. What about tomorrow? From tailored creatives using the library, to individualized timing and frequency, to always-on testing, marketers can optimize for both short-term conversions as well as strategies that value longer term customer relationships and loyalty.
Optimize Every Send Through Continuous Learning
A/B testing is a tried-and-true method for uncovering what works and what needs adjusting within your campaigns. The issue is, marketers often don’t have time to create meaningful A/B tests with each of their campaigns. By the time one campaign ends, marketers are already heads-down on deploying a new promotion and brainstorming the email after that.
That’s where a continuous testing approach comes in handy. After every email, Da Vinci learns from recipients’ signals—such as which creative asset was effective for each customer, when they’re most likely to engage, and how often they want to hear from a brand—and adapts its future responses. This acts as a continuous feedback loop that allows Da Vinci to improve its content, send time, frequency, and subject line personalization over time.
This new approach to testing completely revitalized Ballard Designs’approach to their email campaigns:
Using Da Vinci, they were able to run continuous experiments to learn from every send and automatically improve future ones. This meant they weren’t beholden to only testing one element of an email at a time—instead, they were able to constantly improve multiple aspects of their content personalization automatically and even gain takeaways for emails focusing on other categories. By letting Da Vinci determine who should see the message and when, Ballard Designs ensured that their most compelling creatives didn’t go to waste on the wrong audience.
The results were undeniable, with a 25X lift in revenue per send, an 11X increase in conversions, and a 2X increase in average order value—all through less time and effort than the traditional A/B test.
You’re 5 Steps Away From Efficient Campaigns That Work
By using Da Vinci, marketers not only save on time and resources—they produce campaigns that are more personalized, engaging, and revenue-driving. It’s the win-win that marketers need to keep up with fast-paced customers and never-ending competition.
Book a call with us to discover the AI-personalization engine behind Ballard Designs’ incredible results or explore the related AI resources below.
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