How to Systematically Prioritize Design Work in Fast‑Paced Product Iterations

1. Analyzing Business with a Systematic View

The Ku Dashi platform, an online modeling tool for designers, has built its core modules—home, model square, workspace, help center, activity center, and course center—from 0 to 1. Although each module is independent, they influence each other, so the product is treated as a system.

By mapping the system to three metric types— core metrics (overall project goals), strategy metrics (variables that affect core metrics), and behavior metrics (specific user actions)—the team can pinpoint which parts of the product most impact the core goals.

The identified strategy metrics are registration UV, site traffic UV, and client traffic UV, corresponding to the visitor page, detail page, and workspace modules, which become the design focus areas.

2. Analyzing Users Systematically

User research yields a set of keywords that describe Ku Dashi’s audience. These keywords are sliced and reorganized to form a systematic user profile.

Users are segmented by lifecycle stage: new visitors, new users, and senior users. Their needs differ—new visitors and users focus on value‑need matching, while senior users seek maximum product value.

For each segment, a detailed persona is created through deep interviews, ensuring design decisions are tightly aligned with actual user pain points.

3. Planning Design Strategy Systematically

Design for Senior Users (Client Revamp Example)

Senior users are characterized by a concise statement that captures their profile. Combining this with the service model, the team derives a step‑by‑step design strategy, illustrated in the following diagram.

After defining the strategy, the design implementation follows the identified user needs.

Design for New Users (Visitor Page Redesign Example)

The team uses a "need → concern → driver" framework to organize advantage information, aiming to convert visitors into consumers quickly.

The resulting design emphasizes both common and differentiated value, with strong incentive points to drive conversion.

4. Validating Design Outcomes with a Model

Design impact is measured through behavior metrics such as button clicks, dwell time, scroll depth, and bounce rate. These metrics are linked back to strategy metrics, and AB testing or pre‑post release monitoring quantifies the effect.

In Ku Dashi, the design‑only variable led to noticeable increases in registration conversion and returning‑user login conversion, as shown below.

Conclusion

By applying a systematic mindset—analyzing the business as a whole, segmenting users, crafting targeted design strategies, and validating results with data—designers can focus limited effort on the most impactful areas, ensuring business goals are met and key user journeys are enhanced.