Newsletter Recommendation System

Driving 40% subscriber growth by designing recommendations setup for AWeber’s sign-up form editor

Driving 40% subscriber growth by designing recommendations setup for AWeber’s sign-up form editor

Driving 40% subscriber growth by designing recommendations setup for AWeber’s sign-up form editor

B2C · end-to-end design · UX research · iterative design · user testing

B2C · end-to-end design · UX research · iterative design · user testing

Project Overview

The Newsletter Recommendation system is designed to present personalized newsletters that align with preferences and interests of individuals signing up for a specific newsletter.

The Newsletter Recommendation system is designed to present personalized newsletters that align with preferences and interests of individuals signing up for a specific newsletter.

What I did

What I did

I led the end-to-end design of Newsletter Recommendation System, enabling customers to earn by promoting newsletters within their sign-up flows. I iterated on design solutions to ensure seamless integration with AWeber’s sign-up form editor and conducted usability testing to validate the experience.

I led the end-to-end design of Newsletter Recommendation System, enabling customers to earn by promoting newsletters within their sign-up flows. I iterated on design solutions to ensure seamless integration with AWeber’s sign-up form editor and conducted usability testing to validate the experience.

Contribution

  • UX research

  • UI/UX design

  • end-to-end design

  • usability testing

Contribution

  • UX research

  • UI/UX design

  • end-to-end design

  • usability testing

Impact

Impact

⚡️80%

⚡️80%

⚡️80%

faster set up time vs competitors

faster set up time vs competitors

⬆️ 20%

⬆️ 20%

⬆️ 20%

increase in AWeber engagement

increase in AWeber engagement

⬆️ 40%

⬆️ 40%

⬆️ 40%

subscriber growth through recommendations

subscriber growth through recommendations

Jump To Solution ↓

Jump To Solution ↓

Jump To Solution ↓

BACKGROUND

BACKGROUND

BACKGROUND

What is the Newsletter Recommendation System?

What is the Newsletter Recommendation System?

What is the Newsletter Recommendation System?

The Newsletter Recommendation system is designed to present personalized newsletters that align with preferences and interests of individuals signing up for a specific newsletter.

The Newsletter Recommendation system is designed to present personalized newsletters that align with preferences and interests of individuals signing up for a specific newsletter.

💰

Publishers get paid for recommending other similar newsletters.

💰

Publishers get paid for recommending other similar newsletters.

📈

Advertisers grow their subscriber base by advertising their lists.

📈

Advertisers grow their subscriber base by advertising their lists.

✨

Increased subscriber base means potential increase in AWeber engagement.

✨

Increased subscriber base means potential increase in AWeber engagement.

✨

Increased subscriber base means potential increase in AWeber engagement.

The feature request came from customers who wanted to earn and grow their audience "primarily through recommendations", a feature they had used on other platforms.

While the set was small, the stakes were high as we risked losing them to competitors.

The feature request came from customers who wanted to earn and grow their audience "primarily through recommendations", a feature they had used on other platforms.

While the set was small, the stakes were high as we risked losing them to competitors.

Seeing its broader value, we recognized an opportunity to build this new feature and integrate it within AWeber, aligning with how many users already promoted their newsletters through platforms like social media lead ads.

In this case study, we're only going to be focusing on "designing a solution for setting up newsletter recommendations."

Seeing its broader value, we recognized an opportunity to build this new feature and integrate it within AWeber, aligning with how many users already promoted their newsletters through platforms like social media lead ads.

In this case study, we're only going to be focusing on "designing a solution for setting up newsletter recommendations."

How can we design a seamless solution that enables AWeber users to earn through recommendations, fully integrating it into the platform experience?

How can we design a seamless solution that enables AWeber users to earn through recommendations, fully integrating it into the platform experience?

On a high level, my tasks were to

On a high level, my tasks were to

On a high level, my tasks were to

01.

Perform discovery research and lead end-to-end design, ensuring seamless integration with AWeber platform.

01.

Strategically add entry points to bring more beta customers to the feature page

02.

Perform usability testing on the solutions to validate the feature's experience and value.

02.

Redesign the feature page experience focusing on user confidence and prompt engagement

RESEARCH

RESEARCH

RESEARCH

I aligned with the PMs and other stakeholders to understand the feature requirements and constraints

I aligned with the PMs and other stakeholders to understand the feature requirements and constraints

Business Goals

Seamless integration


The feature must be seamlessly integrated within the existing sign up form editor flow.

Seamless integration

The feature must be seamlessly integrated within the existing sign up form editor flow.

Drive customer adoption


The flow must be so intuitive that users prefer our system over others.

Drive customer adoption

The flow must be so intuitive that users prefer our system over others.

Communicate Legitimacy


Ensure customers are aware that they will be promoting only legitimate newsletters.

Communicate Legitimacy

Ensure customers are aware that they will be promoting only legitimate newsletters.

I conducted a competitor analysis to evaluate flows and patterns, identifying opportunities for improvement.

I conducted a competitor analysis to evaluate flows and patterns, identifying opportunities for improvement.

I noticed that independent platforms required additional steps beyond connecting to an email marketing platform, with an average setup time of ~12 min. This was an opportunity to streamline the process and minimize setup time.

IDEATION

Before designing solutions, I invested time in groundwork such as gathering goals and mapping priorities to ensure a focused approach.

This helped me outline the necessary screens and establish the basic flow for the first Figma iteration. I maintained ongoing communication with Product Managers to align on goals and priorities, focusing on rapid iteration, early feedback, and continuous refinement.

DESIGN

Iteration 01 - The Wizard approach

I designed a step-by-step approach that allows advertisers to selectively include or exclude newsletters, modify selections, or deactivate recommendations anytime. It also gives control over the number of newsletters displayed.

  1. Customers can select up to three categories relevant to their newsletter content

  1. Newsletters are categorized for easy selection, allowing customers to customize the quantity with a dynamic preview.

  1. Customers select one or more existing sign up forms to apply the recommendations.

Iteration 01: Pinpointing Areas for Optimization

Enabling newsletter recommendations on multiple sign-up forms led to audience overlap, inconsistent experiences, and tracking challenges. It also complicated resource management, diluted impact, and risked subscriber fatigue.

Iteration 02- Form-based approach

To enhance control, I shifted to a per-sign-up form approach, allowing customers to manage categories and offers individually. This also extends the existing editor, ensuring seamless integration and user familiarity.

The option to select the number of recommendations was removed, standardizing it to five for consistency and optimal user experience.

The sign-up form editor page features a toggle to enable recommendations on a specific form and an interactive calculator to estimate potential earnings.

When the toggle is enabled, customers can select categories, and newsletters before finalizing the form for publishing.

Iteration 02: Addressing challenges for better impact

Enabling newsletter recommendations on multiple sign-up forms led to audience overlap, inconsistent experiences, and tracking challenges. It also complicated resource management, diluted impact, and risked subscriber fatigue.

Iteration 03- Sidebar modal approach

In the third iteration, I introduced a slide-out modal for quick recommendation setup, minimizing distractions and maintaining focus. Its familiar design ensures smooth integration with the rest of the app.

Clicking the Activate CTA triggers a slide-out modal that first displays categories, then shows offers based on the selected categories.

Customers have the option to review available offers and exclude any if necessary.

Customers can preview how the widget will appear to their subscribers, before activating recommendations.

Upon activation, customers see a success message and can edit or deactivate recommendations as needed.

I conducted usability testing on the third design iteration with 10 users focused on growing and earning through recommendations.

High-level findings

  • Users found the feature description unclear, leading to some questions as they struggled to understand it.

  • Users expressed a need for more information and confidence before recommending newsletters to subscribers.

  • There is a demand for better education on the feature and how to effectively promote their own newsletters.

  • Most users found the available categories to be too broad for their business.

SOLUTION

Final Design

I tackled the challenges from usability testing in the final design:

  • Simplified the UX copy to clearly convey the feature’s value.

  • Added social proof to each newsletter, displaying the number of promotions to boost user confidence.

  • Collaborated on creating knowledge base docs and promotional materials to better educate users on the recommendations feature.

I noticed that independent platforms required additional steps beyond connecting to an email marketing platform, with an average setup time of ~12 min. This was an opportunity to streamline the process and minimize setup time.

IDEATION

Before designing solutions, I invested time in groundwork such as gathering goals and mapping priorities to ensure a focused approach.

Before designing solutions, I invested time in groundwork such as gathering goals and mapping priorities to ensure a focused approach.

This helped me outline the necessary screens and establish the basic flow for the first Figma iteration. I maintained ongoing communication with Product Managers to align on goals and priorities, focusing on rapid iteration, early feedback, and continuous refinement.

DESIGN

Iteration 01 - The Wizard approach

I designed a step-by-step approach that allows advertisers to selectively include or exclude newsletters, modify selections, or deactivate recommendations anytime. It also gives control over the number of newsletters displayed.

  1. Customers can select up to three categories relevant to their newsletter content

  1. Newsletters are categorized for easy selection, allowing customers to customize the quantity with a dynamic preview.

  1. Customers select one or more existing sign up forms to apply the recommendations.

Iteration 01: Pinpointing Areas for Optimization

Iteration 01: Pinpointing Areas for Optimization

Enabling newsletter recommendations on multiple sign-up forms led to audience overlap, inconsistent experiences, and tracking challenges. It also complicated resource management, diluted impact, and risked subscriber fatigue.

Iteration 02- Form-based approach

To enhance control, I shifted to a per-sign-up form approach, allowing customers to manage categories and offers individually. This also extends the existing editor, ensuring seamless integration and user familiarity.

The option to select the number of recommendations was removed, standardizing it to five for consistency and optimal user experience.

The sign-up form editor page features a toggle to enable recommendations on a specific form and an interactive calculator to estimate potential earnings.

When the toggle is enabled, customers can select categories, and newsletters before finalizing the form for publishing.

Iteration 02: Addressing challenges for better impact

Iteration 02: Addressing challenges for better impact

A cluttered form with excessive settings risked confusion, lower completion rates, and insufficient focus on the recommendations feature.

Iteration 03- Sidebar modal approach

In the third iteration, I introduced a slide-out modal for quick recommendation setup, minimizing distractions and maintaining focus. Its familiar design ensures smooth integration with the rest of the app.

Clicking the Activate CTA triggers a slide-out modal that first displays categories, then shows offers based on the selected categories.

Customers have the option to review available offers and exclude any if necessary.

Customers can preview how the widget will appear to their subscribers, before activating recommendations.

Upon activation, customers see a success message and can edit or deactivate recommendations as needed.

I conducted usability testing on the third design iteration with 10 users focused on growing and earning through recommendations.

I conducted usability testing on the third design iteration with 10 users focused on growing and earning through recommendations.

High-level findings

High-level findings

  • Users found the feature description unclear, leading to some questions as they struggled to understand it.

  • Users expressed a need for more information and confidence before recommending newsletters to subscribers.

  • There is a demand for better education on the feature and how to effectively promote their own newsletters.

  • Most users found the available categories to be too broad for their business.

SOLUTION

SOLUTION

Final Design

Final Design

I tackled the challenges from usability testing in the final design:

  • Simplified the UX copy to clearly convey the feature’s value.

  • Added social proof to each newsletter, displaying the number of promotions to boost user confidence.

  • Collaborated on creating knowledge base docs and promotional materials to better educate users on the recommendations feature.

IMPACT

IMPACT

IMPACT

After releasing Newsletter Recommendations feature, we saw

After releasing Newsletter Recommendations feature, we saw

After releasing Newsletter Recommendations feature, we saw

⚡️80% faster

⚡️80% faster

set up time compared to competitors

set up time compared to competitors

⬆️ 40%

⬆️ 40%

subscriber growth via recommendations

subscriber growth via recommendations

⬆️ 20%

⬆️ 20%

increase in user engagement with AWeber

increase in user engagement with AWeber

“

As a new newsletter owner, I struggled to grow my audience through word of mouth. After using recommendations, I've gained 200+ engaged subscribers in just over 3 weeks.


~ Customer of >2 years

As a new newsletter owner, I struggled to grow my audience through word of mouth. After using recommendations, I've gained 200+ engaged subscribers in just over 3 weeks.


~ Customer of >2 years

Next project

Next project

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Background

Research

Goals

Design Audit

Ideation

Solution

Impact