Aktana — Transforming Cloud-Based AI Sales Tools for Life Sciences

Aktana, a leader in AI-driven decision support for the pharmaceutical and Life Sciences industry, engaged Ryan to design and enhance a cloud-based AI sales platform. Over the course of a year, he led UX research and design across the US and Japan — work that played a key role in Aktana meeting its fundraising goals and securing a new round of funding.

Role: UX Research & Design Lead · Timeframe: 1 year

Markets researched on-site: US + Japan
Customer panel established: Day one
Business outcome: New funding round

Highlights

Comprehensive UX research across Japan: led in-depth research in Tokyo and Yokohama, engaging directly with pharma sales representatives, managers, and key stakeholders.
Cloud-based AI platform: designed an AI-driven sales platform to optimize decision-making for the pharma and Life Sciences industry.
Customer panel: established a customer panel on day one, enabling a consistent cadence of generative and evaluative UX research.
Cross-disciplinary collaboration: worked closely with product management, engineering, and the CEO to align goals and execute on a shared vision.
Impactful outcomes: played a key role in enabling Aktana to meet its fundraising goals and secure a new round of funding.

Context

Aktana sought to revolutionize how pharmaceutical sales teams operate by providing an intelligent, AI-driven platform to support decision-making. The project required deep user insights to ensure the product aligned with user needs while navigating cultural and market-specific challenges. Localization for both the US and Japanese markets demanded detailed customization to address distinct workflows and cultural expectations.

The Challenge

Design objectives

Create a user-friendly, cloud-based platform capable of supporting pharma sales teams in real-time.
Localize the product for diverse global markets, with a focus on the US and Japan.
Balance AI-driven insights with intuitive user experiences.

Research objectives

Understand the workflows, pain points, and expectations of pharma sales teams in Japan and the US.
Validate design hypotheses through generative and evaluative research.
Build long-term user trust in an AI-driven tool by addressing transparency and reliability concerns.

Process

Ryan followed a user-centered UX process:

Define: conducted stakeholder interviews to align on business goals and established the scope of research and design deliverables.
Research: conducted contextual inquiries and semi-structured interviews with users across Japan, studying pharma sales representatives in their daily workflows to uncover latent needs, and analyzed qualitative and quantitative data to identify key pain points and opportunities.
Ideate: synthesized findings into personas, wireframes, journey maps, and workflow diagrams, and facilitated workshops with cross-functional teams to brainstorm design solutions.
Prototype: developed wireframes, interactive prototypes, and high-fidelity mockups, iteratively tested with the customer panel to refine usability and functionality.
Implement: worked closely with engineers to translate designs into a scalable, cloud-based solution, with usability testing pre- and post-implementation to ensure seamless adoption.
Evaluate: used the customer panel for regular feedback loops, gathering insights for future iterations.

Research Highlights

Japan

Methods included contextual inquiries, in-depth interviews, and usability testing with pharma sales representatives, sales managers, and regional directors — in Tokyo and Yokohama offices and on field visits with sales representatives.

Respect for established relationships: Japanese users placed a high value on tools that respected existing business relationships and enhanced trust within structured hierarchies.
Structured work environment: efficiency was paramount in a highly organized workflow with clearly delineated roles, requiring tools that seamlessly fit into pre-existing structures.
Localized needs: unique reporting structures in Japan necessitated specific adaptations to the platform's analytics and reporting features.

United States

Methods included user interviews, surveys, and usability testing with sales reps, sales managers, and senior executives.

Workflow flexibility: US sales reps had greater autonomy in determining their workflows, requiring tools that supported diverse approaches to meeting sales goals.
Customization demands: a strong emphasis on customizable dashboards and reporting tools to align with individual and organizational needs.

Design Outcomes

Localized features: tailored reporting workflows for Japan's hierarchical organizational structure, and enhanced customization options for US users with flexible dashboard configurations.
Smart calendar and planning tools: a smart calendar feature to help sales reps efficiently plan their schedules and prioritize tasks.
AI assistant for custom presentations: an AI agent that assists sales reps in customizing presentations for their specific audience, ensuring relevance and engagement.
Streamlined interface: an intuitive, visually clean interface optimized for tablet and desktop use.
Iterative testing: usability testing with the customer panel, leading to significant improvements in task efficiency and user satisfaction.

Impact

Using Google HEART metrics, the following improvements were achieved:

Happiness: post-launch user satisfaction significantly improved due to localized and user-centered features.
Engagement: users reported enhanced productivity and deeper interaction with the platform, driven by smart tools and transparency features.
Adoption: strong adoption rates in both the US and Japan, supported by extensive localization and usability testing.
Retention: sustained user retention through continuous iteration and user feedback loops.
Task success: notable improvements in task completion rates and user confidence in leveraging AI-driven insights.
Business impact: the project's success played a pivotal role in Aktana achieving their fundraising goals, securing a new round of funding.

Key Takeaways

Early user engagement: setting up a customer panel on day one fostered a feedback culture.
Cultural sensitivity: adapting designs to local markets is essential for global product success.
Cross-disciplinary collaboration: close interaction with product management, engineering, and executive leadership was critical to achieving project goals.
Iterative design: frequent testing and iteration are key to building trust in AI-driven platforms.