By building a personalized marketing system,
we established a data-driven decision-making framework.

For many years, this B2B company had been operating its business with transaction data focused on corporate clients and an offline-based CRM.
However, when they launched a new online store (D2C),
they were confronted with new challenges that could not be solved with their existing approach.

They were collecting data on traffic and on-site behavior,
but lacked a multidimensional understanding of who their customers were, why they were visiting, and which messages actually drove conversion.

“We’ve launched the site… but we have no idea what customers actually want.
We don’t know what to do to trigger conversion.”
— CRM Manager, Offline-based Business

What this company wanted was a structure for
personalized scenario orchestration on a marketing cloud, behavior-based targeting, and conversion rate optimization.

Their existing CRM was limited to transaction-focused data such as company name, contact person, and contract history,
while consumer behavior like site visits, product views, and cart events was stored as isolated datasets
and could not be turned into unified, customer-level insight.

We summarized the core of the problem as follows:

CRM and behavioral data were separated, so customers could not be defined properly.

There was no scenario, rule, or goal framework in place to support personalization.

The organization lacked shared KPIs, collaboration, and execution structures for D2C operations.

We gradually built a personalized marketing system that connected data integration, customer redefinition, personalized scenario design,
and a continuous loop of performance measurement and optimization.

Through the three steps below, we co-created a structure that allowed the brand to understand
“who is doing what, and which experiences are actually driving conversion”—and to operate based on that insight.

Based on continuously accumulating data,
we formed, tested, and refined hypotheses and updated marketing scenarios accordingly.

It may look like something any company can do, but
to truly trust such a system and build a data-driven decision-making framework
requires a fundamental shift in how the organization thinks and works.