AddEvent scales GTM operations by building AI into workflows, not just adding tools
AddEvent, a calendar marketing and event management platform, is using generative AI to expand content production, personalize customer experiences, and automate routine marketing tasks. The approach differs from simply plugging AI into existing processes - the company rebuilt workflows around what the technology can do.
Joep Leussink, Chief Growth Officer at AddEvent, oversees sales and marketing operations. He said the team started with content generation because it's where most marketing departments turn first when exploring AI. But early on, they hit a familiar problem: AI-generated content that looks like everyone else's content.
Building a knowledge base before generating at scale
Instead of using AI to mass-produce articles, AddEvent created custom GPTs trained on the company's own content, messaging, and tone of voice. One GPT ingests blog drafts and recommends structural improvements. Another analyzes content gaps. The system improves as it processes more examples.
"We're really trying to feed it a lot of information and data on our value prop, ICP, blog articles we've written, and our tone of voice, so it stays very close to AddEvent's culture and positioning," Leussink said.
This approach let the team tackle long-tail keywords they couldn't reach before. Marketing teams historically focused on core messaging and major customer segments because content creation required significant time and resources. Now the work scales without multiplying headcount.
One piece of content becomes many
AddEvent uses AI and automation to repurpose single pieces of content across multiple channels. A blog post becomes an email, a social media ad, or a YouTube script. Previously, this kind of distribution required different skill sets and was considered too labor-intensive to prioritize.
The shift matters for small or under-resourced teams. A blog writer can now produce email copy. A copywriter can create video scripts. Quality doesn't need to be perfect for every format - a YouTube Short has different standards than a homepage article.
Personalization at scale without manual work
AddEvent's onboarding process used to treat all customers the same. Now the team scrapes customer websites and analyzes product usage patterns to personalize communications. They combine data on which features customers use, which blog articles they read, and what information they gather on their sites.
"Previously, you could personalize based on industry or company size, and that's what a lot of folks did. But now, there are so many more signals to include," Leussink said. This level of analysis required engineers or marketing operations staff before AI made it accessible to non-technical team members.
Early testing shows strong signals in personalized email performance - higher opens and engagement rates. The team tracks results through search and answer engine optimization tools, though Leussink notes the reporting landscape is still maturing.
AI beyond marketing copy
The team uses AI for tasks outside traditional content creation. They built a spam-filter GPT that scores outgoing campaigns before they launch and recommends improvements. They access customer data previously isolated in product teams to answer questions like "How many users engage with this feature and how often?" That data feeds back into their GPTs to improve performance.
Every customer-facing output has a human reviewer. Leussink said full automation may happen eventually, but the company maintains that checkpoint as long as quality improvements are possible.
The organizational challenge: mindset over tools
AddEvent's success with AI came partly from leadership buy-in and partly from how the company introduced the technology internally. Management allocated budget and made tools available. Leussink presented how marketing uses AI. Engineers showed how they use it in their work.
Early fear that AI would eliminate jobs shifted when people saw colleagues using it to do their work better. "Everybody quietly started sharing, 'I wrote this with ChatGPT,'" Leussink recalled. "Initially, people felt afraid of saying that because, well, that's my job."
For operations professionals, the lesson is straightforward: AI adoption fails when companies treat it as a tool problem. It succeeds when teams rethink the process first, then apply AI to the redesigned workflow. AddEvent improved how it works without getting stuck debating which tool to buy.
Start by identifying work you want to do but can't because of headcount or skill gaps. Test AI on a specific project. Measure results. Share what works across the organization. That's how internal AI competency builds.
Learn more about Generative AI and LLM implementation strategies, or explore the AI Learning Path for Operations Managers to develop skills in process optimization and workflow automation.
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