We’re joined today by Evaldas Mockus, a leading voice in the digital marketing space, to discuss the seismic shifts reshaping ecommerce. With daily email volume projected to hit 392.5 billion by 2026 and AI fundamentally altering how customers discover brands, the pressure on marketers has never been greater. In our conversation, we’ll explore how brands can cut through this noise by harnessing AI for authentic personalization, unlocking the immense potential of email automation, and adapting their strategies for a world where visibility in Large Language Models is paramount. Evaldas will share his insights on how marketers can not only survive but thrive by embracing experimentation and integrating AI into their daily workflows.
Many small brands struggle to balance personalization with a unique brand voice. How can AI-powered tools help them craft emails that feel both personally relevant and authentic to the company? Please share a step-by-step example of this process in action.
This is the central challenge that AI is finally solving. For years, smaller brands felt stuck because creating truly personalized, aesthetically pleasing emails required significant resources and deep expertise. Now, that barrier is gone. The key is to see AI not as a replacement for your brand voice, but as an engine to apply that voice at scale. A great example is a small online boutique. First, they can use their marketing platform’s AI to create intuitive customer segments—think “first-time visitors who viewed handbags” or “loyal customers who haven’t purchased in 90 days.” Second, the AI can instantly populate an email template with dynamic product recommendations tailored to that specific segment. Third, the AI can generate compelling marketing copy that leverages proven behavioral cues, like creating a sense of urgency for those handbag viewers. But here’s the most important step: the human marketer then takes that AI-generated draft and infuses it with the boutique’s unique charm and wit. AI does the heavy lifting of segmentation and data analysis, freeing the marketer to focus on the creative element that makes the brand special.
Automated emails triggered by user behavior, like abandoning a cart, can achieve conversion rates as high as 33%. What are the key elements of a high-performing automated workflow, and how does this user experience differ so dramatically from a standard promotional campaign?
The difference is night and day, and it all comes down to context and intent. A standard promotional campaign is like shouting into a crowded room, hoping someone is listening. It’s disruptive because it’s based on the brand’s schedule, not the customer’s. In contrast, a behavior-based automated email is a direct, one-on-one conversation initiated by the customer’s own actions. The key elements are timeliness and relevance. When someone abandons a cart, they have shown clear purchase intent. An automated email arriving shortly after feels less like an ad and more like a helpful reminder. This user experience is a world away from the crowded, ad-filled social media feeds. That’s why we see such a staggering difference in performance—one in three customers who click an automated email will make a purchase, compared to just one in eighteen from a scheduled campaign. Modern platforms make this incredibly easy to set up with templates and AI, meaning any brand can deploy these powerful workflows and start generating a significant portion—up to 37%—of their email marketing orders almost instantly.
The pace of AI development can feel overwhelming for experienced marketers. What daily or weekly habits should a marketing professional adopt to stay current with new AI tools, and how can they practically integrate experimentation into their workflows without disrupting key business operations?
The feeling of being overwhelmed is real, but the solution is to make learning a consistent, manageable habit rather than a massive, infrequent project. I believe marketers should dedicate a small block of time each day—even just 15-20 minutes—to professional development and experimentation. This isn’t about chasing every new shiny object. It’s about focusing on how AI can improve your immediate day-to-day tasks. A practical way to integrate this is to start small. Don’t try to overhaul your entire strategy overnight. Instead, pick one specific task. For example, if you’re a junior marketer tasked with creating a new welcome series, use your platform’s AI to help you draft the copy or suggest the workflow logic. This task, which once might have taken days and required significant experience, can now be accomplished in minutes. This approach allows for experimentation in a controlled environment. You’re not disrupting major campaigns; you’re optimizing the smaller, foundational pieces of your marketing engine. This habit applies to everyone, regardless of seniority. The marketers who embrace this continuous learning mindset are the ones who will lead, while those who rely only on what they already know will inevitably be left behind.
As AI overviews change how people discover information, traditional SEO strategies are becoming less effective. What is the first step for a marketing team to ‘reverse engineer’ LLM results, and how must their content strategy shift to gain visibility across multiple, distinct AI platforms?
The first step is to become a power user of the very platforms you want to influence. Your marketing team needs to be in an all-out race to understand what makes these LLMs tick. This means actively querying different AI platforms with prompts related to your industry, your products, and your competitors. You have to study the results, not just for what is said, but for where the information comes from. That’s the core of reverse engineering: identifying the patterns in the sources the LLM relies on. This completely changes your content strategy. It’s no longer just about keywords on your blog. If you discover an LLM heavily prioritizes recent articles from major business publications, your strategy must now include a robust PR and outreach component to get your company featured in those exact publications. The critical thing to remember is that this isn’t a one-size-fits-all approach. Different LLMs pull from different sources, so you have to test, learn, and optimize your strategy to gain visibility across multiple, distinct AI platforms. Being visible in these AI-driven search results is no longer a nice-to-have; it’s essential for survival.
What is your forecast for the role of the human marketer as AI becomes more integrated into every aspect of campaign creation and search visibility?
My forecast is that the human marketer becomes more of a strategist, a creative director, and an experimenter than ever before. AI will not replace people, but it will absolutely replace outdated workflows and skill sets. The future role of the marketer isn’t about the tedious, manual tasks of the past, like pulling lists or A/B testing subject lines for hours. AI will handle that with incredible efficiency. Instead, the marketer’s value will be in their ability to guide the AI, to ask the right questions, to interpret the data, and to infuse the brand’s soul into the AI-generated output. They will be the ones reverse-engineering LLM results to build new content strategies and deciding which customer behaviors warrant a new automated journey. In essence, AI becomes the powerful engine, but the human marketer is the one with the map, the hands on the steering wheel, and the vision for the destination. Those who fail to learn how to drive this new vehicle won’t just see their sales slow; they’ll find it nearly impossible to catch up.
