Effektify
Effektify
Designing an AI-powered marketing platform around how marketers actually work
Designing an AI-powered marketing platform around how marketers actually work
Designing an AI-powered marketing platform around how marketers actually work
Effektify is a B2B SaaS platform that brings marketing data from channels like Google, Meta and LinkedIn into one place. I joined as the Lead Product Designer and later stepped into an Interim Product Owner role, working across research, product strategy, UX/UI and always in close collaboration with engineering.
Effektify had grown fast, but the product had become fragmented. Different customers were using different platforms, self-service onboarding was struggling and not working for important target users. Earlier design work had on top of that mostly stopped at concepts rather than complete product flows.
Working directly with company leadership, my challenge was to bring everything into one scalable platform that could work for both Enterprise customers and smaller marketing teams with no extra time on their hands.
Effektify is a B2B SaaS platform that brings marketing data from channels like Google, Meta and LinkedIn into one place. I joined as the Lead Product Designer and later stepped into an Interim Product Owner role, working across research, product strategy, UX/UI and always in close collaboration with engineering.
Effektify had grown fast, but the product had become fragmented. Different customers were using different platforms, self-service onboarding was struggling and not working for important target users. Earlier design work had on top of that mostly stopped at concepts rather than complete product flows.
Working directly with company leadership, my challenge was to bring everything into one scalable platform that could work for both Enterprise customers and smaller marketing teams with no extra time on their hands.
CLIENT
Effektify
YEAR
2025–2026
CLIENT
Effektify
YEAR
2025–2026
ROLE
Product design / Product strategy / UX & UI / PO
ROLE
Product design / Product strategy / UX & UI / PO
Who we were designing for
Who we were designing for
Research helped us choose Effektify’s ICP and focus the product and development around two core user groups:
SME marketing teams
Small teams that need a simple way to connect channels, understand performance and act without specialist expertise.
Enterprise marketing divisions
Larger teams that needed deeper reporting, central control and support for multiple markets or local teams.
Across both groups the shared need was clear: make complex marketing data easier to understand and turn into action.
Research helped us choose Effektify’s ICP and focus the product and development around two core user groups:
SME marketing teams
Small teams that need a simple way to connect channels, understand performance and act without specialist expertise.
Enterprise marketing divisions
Larger teams that needed deeper reporting, central control and support for multiple markets or local teams.
Across both groups the shared need was clear: make complex marketing data easier to understand and turn into action.
Research before roadmap
Research before roadmap
Before redesigning the product, I wanted us to understand who we were really building for. I led in-depth interviews and usability testing with 15+ SME and Enterprise customers. The research helped us sharpen our ICP, challenge assumptions and move the roadmap away from individual feature ideas and one-offs towards higher-impact opportunities grounded in real user needs.
I also facilitated workshops with leadership, marketing specialists and engineering to turn those insights into clear product priorities, and then into design and implementation.
Before redesigning the product, I wanted us to understand who we were really building for. I led in-depth interviews and usability testing with 15+ SME and Enterprise customers. The research helped us sharpen our ICP, challenge assumptions and move the roadmap away from individual feature ideas and one-offs towards higher-impact opportunities grounded in real user needs.
I also facilitated workshops with leadership, marketing specialists and engineering to turn those insights into clear product priorities, and then into design and implementation.
Making marketing data easier to understand
Making marketing data easier to understand
One recurring pain point was information overload. Users already had access to plenty of marketing data. What they lacked was help understanding what happened, why it mattered and what to take action on.
A clearer analytics experience
I redesigned the dashboard experience around clearer information hierarchy and structure. We added a knowledge hub and inline guidance with either tooltips or one-click-away modals for hard-to-understand data points. Together with AI-generated contextual insights we connected the data with insights and then the insights with possible related actions.
User quotes
“The insights view where you get insights in plain text. ‘You should do X, Y and Z’ is spot on.”
“What is good? What is bad? 100,000 views, is that great or terrible? It must be put in context to our target group and investment.”
Easier to get connections working
Research also showed that setup itself was a barrier. I redesigned Connections as a guided flow with clearer states, explanations and easy recovery paths.
Designing a consistent
analytics experience
Designing a consistent analytics experience
Designing a consistent
analytics experience
As the platform grew, consistency and speed became increasingly important. I built a design system from the ground up together with our full-stack developer, creating reusable components, guidelines and UX patterns.
All charts and table modules used to build our dashboards were made into responsive, standardised and reusable components. They could then be individually configured with different sizes, visual styles or details depending on the incoming data points and dashboard layout.
This helped us make the platform more consistent while also speeding up future design and development.
Rapid prototyping with AI
Rapid prototyping with AI
All larger features were prototyped either in Figma or built rapidly with AI and then validated with our specialists and users. I used tools like Codex, Lovable and Replit to turn ideas into realistic prototypes quickly, exploring complex interactions and logic as well as iterating before moving the design to development. Reducing the speed between the idea and getting feedback has been extremely valuable for the product team.
Key feature deep-dive
Key feature deep-dive
Simplifying cross-platform advertising
Simplifying cross-platform advertising
Social media's complex ad platforms
One clear opportunity that our research revealed was that SME users described native advertising platforms as very complex and time-consuming. One user said “I don’t really have the time or the knowledge to use Meta for Business.”
Brand consistency in Enterprises
Enterprise customers had a different problem. Central marketing teams needed to maintain control and brand consistency while still making it easy for local business units or franchisees to run relevant campaigns.
Effektify's Ad Studio
This became Ad Studio, a simpler way to create and publish ad campaigns across channels without recreating the complexity of tools like Meta Ads Manager.
One iteration after another, to get it right
Ad Studio changed direction several times as we learned more from users, stakeholders and technical constraints. Instead of treating those changes as failed concepts, each iteration helped simplify and focus the model.
Multiple ads, multiple creatives, cross-publishing
The latest release combines campaigns with analytics and reusable ad variants for different platforms. Multiple creative assets and a dynamic and flexible publishing flow that can adapt to the most popular platforms: Meta, Tiktok, LinkedIn.
Sharing campaigns with local business units
For enterprise users we added ability to share campaigns and assets with configurable permissions to local business units.
One iteration after another, to get it right
Ad Studio changed direction several times as we learned more from users, stakeholders and technical constraints. Instead of treating those changes as failed concepts, each iteration helped simplify and focus the model.
Multiple ads and cross-publishing
The latest release combines campaigns with analytics and reusable ad variants for different platforms. Multiple creative assets and a dynamic and flexible publishing flow that can adapt to the most popular platforms: Meta, Tiktok, LinkedIn.
Sharing campaigns with business units
For enterprise users we added ability to share campaigns and assets with configurable permissions to local business units.
Results: 160+ B2B customers
onboarded into the new platform
Results: 160+ B2B customers onboarded into the new platform
Results: 160+ B2B customers onboarded into the new platform
We increased activation rate going from ~40% to ~85% across the platform serving 160+ B2B clients. Activation: customers successfully connecting one marketing data platform and starting to use the platform.
Customer feedback highlighted clearer dashboards, useful AI Insights, the Knowledge hub and in general a more engaging and well crafted experience.
The new design system and reusable product patterns also made it easier to design, build and iterate as the platform grew.
But one of the most important and time-saving changes was how we worked with rapid AI prototyping and gathering feedback as quickly as possible to understand better what to build and why.
We increased activation rate going from ~40% to ~85% across the platform serving 160+ B2B clients. Activation: customers successfully connecting one marketing data platform and starting to use the platform.
Customer feedback highlighted clearer dashboards, useful AI Insights, the Knowledge hub and in general a more engaging and well crafted experience.
The new design system and reusable product patterns also made it easier to design, build and iterate as the platform grew.
But one of the most important and time-saving changes was how we worked with rapid AI prototyping and gathering feedback as quickly as possible to understand better what to build and why.
