Mass marketing campaigns have long prioritized scale over relevance, often reaching many, but resonating with few. For most marketing teams, this means low engagement, weak conversions, and poor ROI. SolarPlexus, a Swedish SaaS marketing platform, saw this as an opportunity: what if marketers could achieve personalization at scale, without compromising brand consistency or speed?

To bring this vision to life, SolarPlexus partnered with GoML to build a Gen AI-powered solution that enables hyper-personalized marketing across thousands of customer segments automatically and in real time.

The problem: mass marketing with minimal impact

Even with sophisticated automation tools, most marketers struggle to achieve meaningful engagement. Traditional mass marketing techniques prioritize reach over relevance, sending the same message to thousands of users with little consideration for individual context or preferences. As a result, campaigns often feel generic, disconnected, and ineffective, leading to poor conversion rates and low return on investment.  

The root cause lies in the lack of real-time personalization and the inability to dynamically tailor messages to evolving user personas. Marketers are forced to choose between scale and impact, relying on static templates and manual segmentation processes that simply can’t keep up with the speed and complexity of modern audiences. SolarPlexus identified this gap and set out to change the equation, by enabling brands to deliver hyper-personalized marketing experiences at scale, without compromising brand consistency or operational efficiency.

The solution: a Gen AI platform for hyper-personalized marketing at scale

GoML worked closely with SolarPlexus to co-develop a generative AI solution that automatically creates real-time, segment-specific marketing assets, images and copy, based on the user's persona, behavioral patterns, and branding guidelines. The system was built to be fast, scalable, and fully aligned with the customer’s brand identity.

1. Automated branding extraction using Claude-v2

Claude-v2 was used to extract brand rules (logos, fonts, tone, color schemes) from unstructured brand documents and standardize all generated content across campaigns.

2. Real-time user segmentation using ML models

Marketers upload audience data (like demographics, past behavior, and campaign history), which is segmented using clustering algorithms to build dynamic user profiles and personas in real time.

3. Personalized asset generation using Stable Diffusion and DALL·E

Using segment-level insights and brand styles, Stable Diffusion and DALL·E generate tailored email banners, ads, and visuals, ensuring that each user segment receives a unique, on-brand, high-converting message.

The impact: hyper-personalized marketing that’s scalable and effective

• 10X conversion boost from hyper-personalized campaigns led to dramatically higher engagement and conversion rates, especially for email marketing.

• 32% reduction in creative ops effort automated asset generation meant less time designing collateral and more time focusing on strategy.

• 60% higher ROI on campaigns by tailoring messaging to personas, every dollar spent on marketing delivered greater returns.

Lessons for marketers and SaaS platforms

Common pitfalls to avoid

• Relying on static templates that ignore evolving user behavior

• Assuming one-size-fits-all messaging works across segments

• Manually designing creatives for every segment, slows you down

Tips for marketing and product teams

• Build live user personas using clustering and segmentation

• Use generative AI models to automate asset creation at scale

• Ensure branding consistency with automated brand extraction engines

Want to unlock 10X conversions with hyper-personalized marketing?

Let GoML help you build a Gen AI-powered marketing platform that personalizes campaigns in real-time, at scale, without sacrificing speed or brand consistency.

Reach out to build your next-gen SaaS marketing engine.