Insights/Action/Outcome: Wanted Lab wanted to democratize access to data that prevented teams from adopting a culture of continuous experimentation. Using Amplitude as the common data language, Wanted Lab increased the landing page sign-up conversion rate by 150% and built a self-sufficient experimentation culture that produces over 1,300 charts annually.

As the Senior Performance Marketer at Wanted Lab, I had a seemingly impossible mission: improve marketing efficiency while increasing sign-ups and applications—despite a shrinking marketing budget in a tightening labor market.

With a reduced budget, we couldn’t afford to buy growth. Instead, we had to engineer it by optimizing our existing funnel. We knew there was a lot of room for improvement, but first, we would have to be more intentional with our data.

Wanted is Korea’s largest AI-powered recruitment platform, connecting millions of professionals with top employers through an incentivized referral model, rewarding users with cash when their referrals result in successful hires.

Our biggest internal stumbling block to fueling career growth for more users was data literacy and access. We had several concerns:

• Our marketing and product teams spoke different data languages, leading to overreliance on an overburdened analytics team for data
• When problems surfaced in the product, we couldn’t drill down into feature-level performance
• Addressing issues required handoffs between multiple teams, slowing everything down
• Working in isolation, we couldn’t connect the dots between an ad click and resume completion, a high-intent signal for applying.

The answer seemed obvious. If we could democratize data, non-technical marketers could form their own hypotheses and design experiments. It would relieve pressure from the analytics team while improving issue resolution and product velocity.

The only problem was that we didn’t have an analytics tool that provided deep visibility into user actions while ensuring we were self-sufficient—until we found Amplitude.

Building a common data language with Amplitude

Amplitude became our common data language across product, development, and marketing.

To close the loop between insight and action, I designed a formal “Experiment-Analyze-Improve” cycle using Amplitude's full suite of data analytics tools. With Amplitude Analytics, our teams could track how users moved through the product, where they hesitated, and where we were losing them, without needing to submit a request to the analytics team.

Next, I built feature-specific dashboards using Amplitude’s metrics charts to monitor each feature’s performance in real time and quickly detect problems. These dashboards broke down silos and enabled marketing, product, and analytics team to speak the same language.

Whenever we detected an issue, we turned it into an experiment agenda using Amplitude Feature Experimentation, which has strengthened data utilization and experimentation culture across the organization. So far, I’ve designed experiments across web, app, and feature levels to drive product improvement.

Behavioral Cohorts allowed us to go further by grouping users by shared behaviors rather than broad demographics, enabling us to execute hyper-personalized campaigns for specific segments. We use these insights to improve the AI’s matching accuracy and Execute hyper-personalized campaigns that improve the experience for user segments. Users with low match rates, for example, formed a distinct cohort, leading to an experiment that increased click rates for resume creation.

Introducing Amplitude has strengthened data utilization and experimentation culture across the organization.

A factory for product improvements that gets the job done

Amplitude has helped us improve marketing efficiency while growing sign-ups and applications. Today, we create more than 1,300 charts each year, and we’ve become a factory for product improvements.

• Optimizing the core funnel: We increased the landing page sign-up conversion rate from 4% to 10%—a 2.5x growth rate—by identifying where visitors hesitated and removing the friction in the registration flow.
• Recovering lost opportunities: By resolving friction points for motivated job seekers, we improved the conversion rate for popular search terms by 38%. Additionally, a single UX experiment on the bulk apply button restored over 7,000 monthly applications that had previously been lost to friction.

From data dependency to self-sufficiency

Beyond improving our KPIs, using Amplitude has elevated data literacy across the entire organization.

Dashboards have democratized access to data and empower all teams to work on product improvements simultaneously. We have fostered a strong culture of continuous experimentation, replacing reactive singular fixes. I do my part by continuing to share what I’ve learned about data interpretation and experimentation through internal and external events, such as Amplitude coffee chats, Wanted Pre-onboarding, and MGS2025.

Wanted Lab has moved beyond short-term performance optimization to build a sustainable growth structure and experiment-driven decision-making system.

Rather than being overly dependent on the analytics team, the product experience and marketing performance teams at Wanted Lab are tightly linked and much more self-sufficient. Together, we turned a mission impossible into a mission accomplished.