Advertiser Self-Serve DSP
2025 Nexad
AI-powered platform simplifying programmatic advertising for seamless, efficient campaigns.
Designed the advertiser onboarding flow and campaign creation experience for Nexad’s first self-serve ad platform, supporting ad campaigns reaching 30M+ active users. Collaborated closely with the PM and development team to ensure technical feasibility under tight timelines.
Team
2 UX Designers
2 Software Engineers
1 PM
Role
Product Designer
Tool
Figma
Duration
3 Months
Nexad operates as an intermediary between chatbox publishers and advertisers.
Nexad is an ad-tech startup building an AI-native advertising platform that delivers personalized, real-time, context-aware ads within AI applications like chatbots and AI search engines.
Help small and medium-sized (SMB) businesses reach the right audiences with relevant ads.
Reaching the right audience is challenging for SMB advertisers and often results in underperforming campaigns.
Friction in setting up
Ineffective campaign targeting and management
Stuck in business growth
Limited resources and expertise leave advertisers unclear about their audience and market.
After we did further analysis, we found that starting with limited resources, these factors formed a vicious cycle that stalled SMB growth. and rapid shifts in marketing as external reason cause the situation even harder.
Design Goal
How might we design a self-serve DSP to support SMB in achieving their goals?
Based on previous problem, our team decided to tackle the problem from following 3 aspects:
Budget-friendly
Maximize ROI while working within limited resources.
Easy setup & Efficient management
Streamlines campaign setup, monitoring, and decision-making to keep advertisers on track without requiring deep expertise.
Learning for long-term growth
Help advertisers build marketing knowledge and make better decisions over time.
Understand Audience Effortlessly Before Campaign Setup
Understand audience by simple product URL.
Delivers real usage scenarios and Nexad's value intuitively.
Starts at peak interest for higher user engagement.
Reliable Insights and Explanations for Growth
Combined charts of pre-selected key metrics make performance insights clear.
Uncovers audience behaviors and patterns, guiding smarter targeting decisions.
Help less experienced users interpret results and build expertise.
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We conducted 5 advertiser interviews to identify users' pain points with existing common used platforms, which can guide potential features for our platform. From the interview, we found out they are sharing 3 main problems while they are using these main stream ads platform.
Difficulty targeting the right audience due to limited resources and expertise.
Inefficient and time-consuming operational decision-making.
Difficulty translating complex data into actionable insights.
To understand the problem more specifically, we mapped out their user journey to uncover the key steps that caused the most frustration.
Elevating Campaigns Through Step-by-Step Interventions to maximum ROI.
Based on previous frustrations, we decided to tackle problems step by step and eventually lift an end to end experience to make campaign operations easier and faster to SMB and help them build professional skills in a long run.
Make onboarding fast and intuitive while ensuring insights are delivered clearly.
Heavy text buried the message:
Splitting content into 3 parts to ease cognitive load.
User need time to process:
A button lets users control the flow, reducing overwhelm.
Data visualization makes information easier to grasp.
A more familiar chat interface makes the demo more understandable.
Improving AI usability with greater user control and clearer guidance during setup.
Added optional upload and editing for AI-generated creatives, giving users more control.
Shifted to a step-by-step flow to reduce overwhelm and prevent missed inputs.
Provided in-context explanations to improve clarity and help users choose confidently.
How to implement AI be trustful to inform user making right decision without overreaching.
Broke down information progressively
Instead of showing it all at once, reducing cognitive overload and tailoring explanations to different expertise levels.
AI as advisor, not decision-maker
Positioned AI to inform rather than decide, shifting from rigid recommendations to key indicators with context, so users stay in control.