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TAGby

Influencer Marketing app

Boosting Influencers: Simplify exploring flow and help the users to stand out

I led the app product design for an influencer marketing SaaS platform,

where my UX/UI innovations that boosted the monthly

campaign applications by 56.7% and campaign selection rates by 34%.

I led the app product design for an influencer marketing SaaS platform, where my UX/UI innovations that boosted the monthly campaign applications by 34% and campaign selection rates by 66%.

Go to vist

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My Role

App Design Lead

Project

2022.07 - 2022.10

Product

Flutter App

Skills

User Research & Competitor Analysis,

Usability Testing, Iteration Design, Design System

TLDR

Boosting Engagement Through

Data-Driven Insight and

Psychological Motivation Design

TAGby, an influencer-marketing SaaS, faced low campaign participation from new influencers, which weakened overall platform activation. Through UX analysis and user-behavior data,I identified that competition perception and anticipated chance of being selected were the key psychological factors driving participation.


Based on these insights, I redesigned the campaign flow to prioritize high-fit opportunities, visualize competition levels, and create early success experiences for new users. I also refined the Design System and UI architecture to improve team alignment, implementation efficiency, and product consistency.

Avg. Campaign applicants
per month

56.7% uP

Campaign application rate

among new sign-ups

144% uP

Monthly Selected campaign

accounts

34% uP

01

ProbleM statement

Case #01

Low campaign application rate among new users

Through data analysis, we discovered that new influencer users in the app have a low campaign participation
rate compared to their sign-up rate. To address this issue, we examined the following data:

Through data analysis, we discovered that new influencer users in the app have a low

campaign participation rate compared to their sign-up rate. To address this issue,

we examined the following data:

The monthly campaign application rate is over twice as low compared to the number of registered users

The TagBy solution is a SaaS platform for influencer marketing tailored to both marketers and influencers. It includes both app and web-based services. TagBy boasts a design that maintains consistent performance between its web and app services, leading to more effective usage of social media marketing initiatives. The objective is to cultivate a mutually beneficial scenario for both marketers and influencers, offering reciprocal advantages to both entities.

The application rate for new users is approximately three times lower than that of regular users

The TagBy solution is a SaaS platform for influencer marketing tailored to both marketers and influencers. It includes both app and web-based services. TagBy boasts a design that maintains consistent performance between its web and app services, leading to more effective usage of social media marketing initiatives. The objective is to cultivate a mutually beneficial scenario for both marketers and influencers, offering reciprocal advantages to both entities.

85% of new users are nano & micro-users

The TagBy solution is a SaaS platform for influencer marketing tailored to both marketers and influencers. It includes both app and web-based services. TagBy boasts a design that maintains consistent performance between its web and app services, leading to more effective usage of social media marketing initiatives. The objective is to cultivate a mutually beneficial scenario for both marketers and influencers, offering reciprocal advantages to both entities.

02

ProbleM statement

Case #01

Where Users Drop Off: Issues Across the Current Platform Cycle

The AS-IS analysis reveals several breakdowns in the platform’s campaign cycle. Users experience low visibility of filters, inconsistent navigation patterns, and unclear application steps, resulting in the lowest click-through rates within the Apply stage. Additionally, advertisers face difficulty selecting suitable influencers due to inconsistent data presentation. These gaps highlight the need for a more intuitive, guided flow that connects exploration, filtering, and application with fewer disruptions.

Through data analysis, we discovered that new influencer users in the app have a low

campaign participation rate compared to their sign-up rate. To address this issue,

we examined the following data:

AS-IS

Applying the psychological effects of slot machines to increase the selection opportunities, providing motivation

Challenge

Case #01

Limits in Improving Campaign Engagement

Applying the psychological effects of slot machines to increase the selection opportunities, providing motivation

Thus, improving mission engagement requires a solution that boosts influencer motivation without interfering with client-side

selection behavior, making stakeholder cooperation and strategic alignment essential.

We designed the campaign application participation rate for influencers by applying the theory of psychological effects derived from gambling and slot machines, aiming to provide appropriate rewards(success experiences). Simultaneously, we designed for success

participation of new influencer users to enhance the successful campaign execution experience for client(advertiser) users as well.

01

The fundamental way to increase campaign engagement is to raise the influencer selection rate.

02

we cannot directly push clients to select more influencers.

03

Because this touches the core business model, stakeholder alignment becomes critical.

USer research

Case #01

51% of new influencers skip applying to campaigns:
primarily because they fear not being selected, despite craving opportunities that match their interests.

🔍

Insights

01

Users seek beneficial & suitable campaigns by their interest

Users seek beneficial &

suitable campaigns by

their interest

Users seek beneficial & suitable campaigns by their interest

02

Users seek beneficial & suitable campaigns by their interest

More users will apply the

campaigns if there is

less competitive &

more chances

More users will apply the campaigns if there is less competitive

03

Users seek beneficial & suitable campaigns by their interest

Clients prefer to select

more nano & micro

influencer for the high

engagement

Users need to get more chances to be picked by clients

hypothesis

Case #01

Applying the psychological effects of slot machines to increase the
selection opportunities, providing motivation

Applying the psychological effects of slot machines to increase the selection opportunities, providing motivation

We designed the campaign application participation rate for influencers by applying the theory of psychological effects derived from

gambling and slot machines, aiming to provide appropriate rewards (success experiences). Simultaneously, we designed for successful

participation of new influencer users to enhance the successful campaign execution experience for client (advertiser) users as well.

We designed the campaign application participation rate for influencers by applying the theory of psychological effects derived from gambling and slot machines, aiming to provide appropriate rewards(success experiences). Simultaneously, we designed for success

participation of new influencer users to enhance the successful campaign execution experience for client(advertiser) users as well.

Solution

Case #01

How can we encourage influencers to be more
eager to participate in campaigns?

Iteration

Case #01

Evolving the Explore Page into an Intuitive &
Personalized Matching Experience

Pros

A layout that provides easy access to the

campaign thumbnails and details, offering a

clear view of multiple aspects and an intuitive

reward system.

Cons

The campaign setup is confusing. The filters are hard to see, resulting in fewer clicks, and the layout complicates viewing multiple campaigns.

Pros

The layout allows quick viewing of different campaigns, clearly highlighting key information. The prominent filter improves usability and likely boosts click-through rates, helping users easily identify available campaign types and enhancing engagement through the rewards system.

Cons

Checking campaigns by user preferences isn't intuitive; often-used filters are hidden, requiring extra clicks, which can confuse new users.

Pros

Key campaign details are clearly presented with a visual interface that features a personalized matching system. The layout allows easy access to various campaign types and filters based on user preferences, emphasizing the rewards system to enhance engagement.

Cons

The filtering layout is visually complex, adding to the overall confusion.

a/B TEST

Case #01

Test & Improvement

We ran a two-week A/B test with internal influencers for 2 weeks in August,

and the data showed Concept B drove greater user engagement. The detailed results are below:

-Increasing anxiety competition rate

-Lack of motivational information

-Lack of preferences & Unnoticeable filter

-Detailed match with personal interest & Easy to access

-Encouraging application feature

-Well-organized & intuitive beneficial information

Personal interest

Interface by personalized

1

Based on the user’s social account analysis, we provide personalized filters in the most convenient way.

Quick-Search

⚡️ High Chance

🚩New

💰$20+

💄Beauty

aPP

Influencer

Campaign exploration -> Displaying the

Default filtering for personal interest

1

High chance & motiation

filtering by highest selection rate

2

Calculate the selection frequency of new influencers and prioritize the display with the 'double reward time' & 'selection agv rate' for the high chance and motivation.

aPP

Influencer

Campaign exploration -> applying

Default filtering for High Chance & Motivation

2

Win-Win circle

new users first default Setting

3

By filtering, users can easily explore of the new influencers and information with diverse options.

New Users

Pc

Client

Campaign management -> Influencer selection page

Win-Win circle

Promotion for new users

4

The New User(influencer) Badge UI & tooltip guide clients to discover the benefits that increase their chances of being selected.

clients can earn monthly free chances to select new influencers. Through the banner, They Can Check The Benefits For New User Selection.

Pc

Client

Campaign management -> Influencer selection page

Communication

Designing a design system and guide for seamless
communication with team members

UX flows & actions Definition

Ensured efficient communication
across all team members

keeping everyone aligned and informed.

UI elements description

Seamless communication

with developers

Systematically organized functions, definitions, and guidelines

for components, modals, and pop-ups, and provided

environment-specific documentation to streamline communication

with developers.

design system guide

Consistent communication

with designers

Defined style guidelines to ensure system consistency and

collaborated seamlessly with designers and developers—

earning consistently positive design reviews.

result

Case #01

Selection and application rates doubled, making a significant impact

We designed our approach by applying the theory of the psychological effects of slot machines to our hypothesis, aiming to increase

influencer’s campaign application rates by providing successful experiences through appropriate rewards. This resulted in increased numbers of
selected accounts and campaign application rates, demonstrating successful outcomes.

The average monthly campaign

applicants

56.7% uP

7,167

11,229

22.07. 01 ~ 22.10. 01

The average monthly campaign

applicants

56.7% uP

7,167

11,229

22.07. 01 ~ 22.10. 01

The average monthly campaign

applicants

56.7% uP

7,167

11,229

22.07. 01 ~ 22.10. 01

Campaign application rate

among new sign-ups

144% uP

9%

22%

22.07. 01 ~ 22.10. 01

Campaign application rate

among new sign-ups

144% uP

9%

22%

22.07. 01 ~ 22.10. 01

Campaign application rate

among new sign-ups

144% uP

9%

22%

22.07. 01 ~ 22.10. 01

Monthly new users selected

for campaigns

34% uP

292

391

22.07. 01 ~ 22.10. 01

Monthly new users selected

for campaigns

34% uP

292

391

22.07. 01 ~ 22.10. 01

Monthly new users selected

for campaigns

34% uP

292

391

22.07. 01 ~ 22.10. 01

Next Project

© 2024 Yuri Yang

© 2024 Yuri Yang

© 2024 Yuri Yang