Knowledge Base

UX Design for a Scaling Product

UX Lead
Research
Web App
Growth
WHEN
2022
ROLE
Senior UX Designer
WHERE
Elementor

Knowledge Base

UX Design for a Scaling Product

Info

About

Elementor is a leading WordPress website builder platform, enabling web creators to build and design professional websites with ease. Elementor serves a wide range of users, from professional designers to small business owners.

What

This project involved a comprehensive redesign of Elementor’s knowledge base and learning platform. The goal was to improve access to information, streamline support across multiple product versions, and create an intuitive experience that supports users in finding specific answers and facilitates continuous learning.

Why

As Elementor’s product offerings expanded and became more complex, users encountered difficulties in finding accurate and relevant information within the help center and academy resources, leading to frustration and inefficiencies.

The existing help center and academy were causing frustration for users due to inconsistent search results, layout issues, and irrelevant content. This redesign aimed to streamline the user experience, improve search accuracy, and ensure that users could easily find relevant information, thereby reducing the burden on customer support.

Team – UX Lead and UX Research – Aviya, Design Team Managers – Erez, Ronit

Main challenge

Redesigning a Knowledge Base for a Multi-Version Product

Transforming User Support with Data-Driven Design

A knowledge base isn’t just a support tool, it shapes user trust and experience.

When information is hard to find, frustration rises, and reliance on support increases.
Elementor’s growing product complexity made it difficult for users to access the right answers, causing inefficiencies and friction in their workflow.

This case study explores the UX challenges of structuring knowledge for a multi-version product, focusing on how users search for information, how to deliver content tailored to their state of mind, and how to combine didactic methods that support both quick troubleshooting and deeper learning.

Research

Exploring User Pain Points in a Growing Product Ecosystem
Research process and methods
User Interaction Analysis
Search Query Analysis
User Behavior Tracking
Content Audit
Competitors Analysis
Data Analysis
Customer Success Insights Analysis
Cross-Functional Collaboration

The research aimed to identify and understand the specific pain points users faced while navigating the help center and academy within this increasingly complex ecosystem.

Here are the key areas of focus that were addressed during the research process:

Identifying Key User Types

To fully understand the challenges users faced, I collaborated with the education and content teams to analyze user interactions with the help center and academy. This analysis focused on identifying how different types of users navigated the system and where they encountered difficulties.

Two primary user types were identified:

  1. Users Seeking Specific Answers: These users needed quick and accurate solutions to specific problems. Often, they were in the middle of building a website and needed immediate answers to keep working without delays. They required precise information without having to sort through unrelated content.
  2. Continuous Learners (Including New Users): These users, including those new to the product, wanted to build their skills over time, moving from basic to advanced levels. They needed a structured learning experience that allowed them to explore the product at their own pace.

Analyzing User Behavior

After identifying the user types, we closely examined how these users interacted with the help center and academy. This analysis was supported by data analysts, the SEO team, and a user behavior tracking tool:

  • Navigation Paths: Using data from the user behavior tracking tool and similar resources, we tracked how users navigated through the help center and academy. We identified common paths and places where users got lost or diverted. This analysis showed where the content structure was confusing or led to dead ends.
  • Search Term Analysis: With input from the SEO team and data analysts, we reviewed the search terms users frequently used. This analysis helped us understand what information users were looking for and whether they found it, revealing gaps in the search functionality and areas where users didn’t get relevant results.
  • Content Engagement: By analyzing data, we saw which content users interacted with most and how long they spent on specific pages. This information highlighted which resources were most useful and which were underused, indicating potential issues with how content was organized and discovered.

This detailed analysis, combined with insights from data experts and advanced tools, gave us a clear understanding of user behavior. It became evident that the existing system wasn’t fully meeting the needs of these user types, especially as the product offerings became more complex. These findings were crucial in guiding the redesign process, focusing on improving navigation, search functionality, and content structure.

As the product offerings grew, users increasingly struggled to navigate the knowledge base, often ending up in irrelevant sections due to inconsistent content structure across product versions.

Integrating User Feedback

We gathered feedback directly from the customer support team to understand the most common issues users were facing. This feedback was crucial in identifying the specific pain points that users experienced while navigating the help center and academy.

  • Common User Complaints: Users frequently reported difficulty finding relevant information, especially when dealing with multiple versions of the product. The feedback highlighted confusion over which articles applied to which version, as well as frustration with the navigation and search functions.
  • Prioritizing Issues: Based on this feedback, we prioritized the most critical areas that needed improvement in the knowledge base. This included enhancing search functionality, refining the content structure, and ensuring that users could easily find version-specific information.

Competitive Analysis

To build a comprehensive understanding of how the knowledge base could be improved, I conducted an in-depth analysis that extended beyond similar products, incorporating insights from various learning platforms and other relevant systems.

Drawing Insights from Related Platforms: I explored a variety of platforms, including knowledge bases from different industries, search engines, customer support platforms and more to uncover best practices.

Incorporating Insights from Learning Platforms: In addition to analyzing related platforms, I studied various learning platforms to understand alternative approaches to information retrieval, course structures and learning methods. This analysis focused on how these platforms organized content into units or chapters, integrated exercises within the course flow, and utilized features like class environments and interactive elements. The insights gained from these platforms revealed effective strategies for structuring and presenting educational content.

Users often found more accurate information using external search engines than in our help center, revealing significant gaps in our content and search systems.

Key Findings from the Current System

01

Inconsistent Content Structure Across Versions & Misused and Misleading Side Menu

Users encountered difficulties navigating the knowledge base due to inconsistent content organization, especially when searching for version-specific answers.
In some screens, a list of unrelated topics was incorrectly presented as a side menu, confusing users since it appeared functional but was irrelevant to both the content and the overall knowledge base.

02

Inefficient Internal Search Leading to Reliance on External Search Engines

The search functionality often returned outdated or irrelevant results, particularly for newer product versions.
As a result , users often turned to external search engines (e.g. Google) to find relevant answers, suggesting that the internal search system did not effectively meet their needs.

03

Static and Outdated Tagging System

The tagging system was static and did not update according to user needs or new product developments, making it harder for users to find relevant content, particularly across multiple product versions.

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Main Insights

01

Inconsistent and Irrelevant Search Results Cause User Frustration

Search data and SEO review revealed that users often received irrelevant and non-version-specific search results. Competitive research highlighted that incorporating context relevancy could not only improve search accuracy but also build user trust by helping users confidently locate relevant information.

Why it’s important

When users can’t quickly find the right answers, they lose trust in the knowledge base and turn to external sources. This frustration lowers engagement. Context-aware, version-specific search results build trust by helping users find accurate information faster. This improves problem-solving, enhances the user experience, and reduces reliance on external platforms.
02

User-Specific Content May Lead to Better Navigation and Engagement

Due to the complexity of managing multiple product versions, I identified that incorporating adaptive personalization features based on the user’s profile, profession, product version, interaction history, and proficiency could simplify navigation and improve user engagement.

Why it’s important

Without personalization, users often encounter irrelevant content, which makes it difficult to find what they need. By incorporating adaptive personalization features that take into account the user’s profile, profession, product version, interaction history, and proficiency, the knowledge base could prioritize relevant content upfront. This could reduce cognitive load, making it easier for users to navigate and interact with the system. Offering content tailored to their specific needs ensures that both beginners and advanced users have a more seamless experience, resulting in greater engagement, quicker task completion, and overall satisfaction.
03

Guiding Users Through the Learning Curve Could Improve Retention

Analysis of user behavior, along with research on learning systems and knowledge bases, suggests that using a structured learning methodology, supported by the education team, could improve retention and engagement, particularly for new users.

Why it’s important

Users face a steep learning curve without adequate guidance often become frustrated, leading to lower retention or underutilization of key product features. By incorporating a sequential learning approach, which emphasizes step-by-step progression, and a scaffolded learning methodology, where complexity builds over time, the system could support users as they advance from basic to more advanced tasks. With insights from the education team and research on learning systems, the knowledge base could implement a progressive learning system that allows users to move through learning stages gradually. This structured approach could help users of all proficiency levels feel more confident with the product, leading to higher engagement, satisfaction, and long-term retention.
04

Continuous Feedback Could Ensure Content Stays Relevant

Customer support data, user feedback, and the existing company’s community highlighted that integrating a continuous feedback loop into the content update process could be essential for keeping the knowledge base relevant and aligned with user needs.

Why it’s important

Outdated or irrelevant content can undermine user trust in a knowledge base. The company’s active community, which already raises and answers questions, presents a valuable resource that could be leveraged to help keep the knowledge base up to date. By incorporating a continuous feedback loop, this community can directly contribute to maintaining content accuracy and relevance. This approach not only builds user trust but also reduces the load on customer success teams, as the community plays an active role in providing accurate answers, lowering the volume of support requests.
05

The Need for Scalability in a Growing Product Ecosystem

Scalability emerged as a crucial requirement, ensuring that the knowledge base could handle the company’s continuous product growth and an expanding user base without compromising performance or accessibility

Why it’s important

As the product offerings evolve and new versions are introduced, the knowledge base must be capable of expanding effortlessly to accommodate these changes. Ensuring scalability means both new and experienced users will continue to find relevant and accurate information as the system grows. A scalable structure allows the knowledge base to stay reliable, efficient, and adaptable over time, ready to meet future demands without overwhelming users or support teams.
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Suggested Solutions

Product Design strategy & Concept

Designing a Scalable, Trustworthy Knowledge Base for an Evolving, Multi-Version Product Support

The core challenge was building a system that could provide quick access to information, support continuous learning, and scale as the product ecosystem grew. Additionally, the system needed to rebuild user trust by offering reliable and contextual information based on user needs.

As part of the overall UX strategy, flexibility was essential to allow the knowledge base to grow and evolve, effortlessly adapting to new content, versions, and products while maintaining a cohesive structure.
Main Design challenge

Delivering Fast and Reliable Access to Information Across the Knowledge Base

Reminder & Approach

The key challenge was to design a system that provided quick, reliable answers to users’ queries.
Users needed to easily find accurate, relevant information tailored to their product version, without being overwhelmed by irrelevant results.

My approach focused on creating a user-centered, scalable knowledge base, ensuring that information was organized dynamically to support both current and future product versions.

By streamlining navigation and search functionality, the system empowered users to quickly locate the right answers while fostering trust in the knowledge base as a reliable resource.

The knowledge base empowers users to navigate confidently, building trust with quick answers while encouraging deeper exploration for ongoing learning.

Home Page Structure

Desktop Hierarchy

The home page is designed to provide immediate access to the most relevant information for users, reducing time spent searching.

  • Scalable Side Menu: A dynamic side menu organizes content by categories, ensuring that users can quickly find topics while easily accommodating future product versions or updates – This menu is designed to scale seamlessly as the company releases new products or versions.

Popular Tags and Current Bugs

  • Popular Searches & Tags: Directly below the search bar, popular tags guide users toward frequently accessed content, ensuring users can find answers without frustration.
  • Known Bugs Banner: To further reduce customer support burden, the banner below the search field highlights current bugs and performance issues, offering transparency and proactive assistance – This ensures users have immediate visibility into any known issues, building trust and confidence in the system.
Personalized results guide users to quick, accurate answers, turning frustration into efficiency.

In-Article Navigation

Quick Navigation for Immediate Solutions

  • Version-Specific Content: Delivers personalized answers based on product version.
  • Featured Snippets: Essential information summarized clearly at the top, enabling quick answers without reading the full article and enhancing SEO visibility.
  • Anchor Menu: Jump directly to key sections, avoiding long scrolls.
  • Highlighted Sections: Emphasizes the most relevant parts of the article based on the user’s query and product version.

Encouraging Continuous Learning

  • Persistent Side Menu for Exploration: While users focus on their immediate query, the side menu remains visible, offering a clear path for further exploration. This encourages users to dive deeper into related topics.
  • Related Learning Suggestions: After resolving their primary query, the system presents personalized learning recommendations, guiding users toward related content based on their product version and proficiency level.

User-Driven Content Improvement

Keeping Articles Relevant & Up-to-Date

Each article includes sticky feedback options to keep content relevant:
“This article was helpful” – Tracks usefulness.
“Suggest Edits” – Allows users to request missing information or improvements.

This feature relies on our active community to keep content up to date, reducing customer support load and ensuring the content team stays connected to user needs.

Search Results & Suggestions Page

  • Featured snippets displayed at the top of each suggested result – The search system offered instant suggestions as users typed, summarizing key information so users could often receive a solution without needing to click through.
  • Enhanced autocomplete – provides relevant queries based on the user’s product version, with hover-over video previews for quick evaluation.

These features speed up the search process, helping users find answers faster.

  • Feedback buttons – Recognizing that users might find their solution directly in the search results, feedback buttons were added below to capture user input at this stage.

FAQs

Structured for Accessibility and Relevance

The FAQ page and section were redesigned to help users find answers more easily while improving overall information organization, incorporating SEO query research and user data.

  • Categorized by Topic: FAQs are organized into popular subjects, accessible through dedicated tabs for quick navigation.
  • Product & Version Filtering: Users can refine FAQs by product and version to find more relevant answers.
Design challenge nr.2

Optimizing Complex Navigation for Mobile Devices

Navigating the knowledge base on mobile devices presented significant challenges due to the complexity of the system and the limited screen space. The key focus was ensuring users could quickly locate the information they needed, while minimizing excessive scrolling and managing complex hierarchies on smaller screens.

Mobile Hierarchy

Floating Table of Contents Button for Easy In-Article Navigation

  • The anchor menu was adapted into a floating button on mobile, allowing users to tap and view the table of contents for quick navigation between sections. This minimized scrolling while keeping the screen clear.
  • Tapping the floating button expanded the full content structure, allowing users to jump to specific sections of the article. The menu collapsed after use, maintaining a clean interface.

Mobile-Optimized Hierarchical Structure

  • Main menu – The desktop content hierarchy was adapted for mobile, enabling users to reach deeper content layers directly from the main menu while keeping navigation clear and efficient..
Design challenge nr.3

Next Step Toward the Vision: Expanding the Knowledge Base to Include Both Help Center & Courses

The future of the knowledge base goes beyond answering questions—it’s about empowering users to learn, explore, and grow within a single, trusted environment. The vision for the next step is to merge the Help Center and Academy (Courses) into one seamless platform, allowing users to transition effortlessly between troubleshooting and structured learning.
By bridging the gap between two user types—those seeking specific answers and continuous learners—this unified approach would build trust in the system while fostering deeper engagement and confidence. A fully integrated knowledge base would ensure that every user—whether solving a problem or developing new skills—finds the right guidance without friction.
The proposed design explores how this vision could take shape, maintaining intuitive navigation, smarter search, and a structured learning experience within a single platform.

Building a Cohesive Learning Flow

Navigation

Centralized Navigation: The header menu includes Home, Courses, Knowledge Base, and Support, making all resources easily accessible.
Consistent Structure & Learning Flow: The side menu follows the same structured approach as the knowledge base articles, ensuring familiarity and ease of use.
Progress Tracking: Unlike the knowledge base, users see a checkmark icon on completed content, helping them track progress and discover suggested next steps.

Supporting Learning Tools

Bringing Class Structure Into the Interface.
Below each video, familiar class-based tools support deeper learning:

  • About: Video overview and context
  • Notebook: Space for personal notes
  • Community Chat: Ask and answer peer questions
  • Exercises & Uploads: Practice tasks and example files
  • Highlights: Easily access all saved moments

Supporting Learning Tools

Search & Highlight for Video Accessibility: Videos include searchable transcripts for quick topic access. Users can highlight key moments to revisit later.

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Conclusion

Main challenge
Building a Future-Ready Knowledge Base

The redesign of the knowledge base was driven by the need to address key user challenges, such as finding quick, reliable answers and navigating through complex content hierarchies. By focusing on both personalization and scalability, the new system provides users with a streamlined, intuitive experience across desktop and mobile platforms.

This future-ready system not only meets current demands but is built to handle the challenges of tomorrow.

Key Success Factors: Flexibility and User-Centric Design

The key to the success of this project was its forward-thinking, flexible structure, designed to grow with the company. By allowing the knowledge base to seamlessly integrate new product versions and updates without overwhelming users, we ensured that the system remained relevant and useful over time.
The emphasis on quick answers through features like featured snippets and personalized content helped build user confidence, while clear navigation paths supported both beginners and advanced users in their learning journeys.
The result is a knowledge base that not only solves current challenges but is also adaptable to future demands, establishing it as a central, trusted resource for users seeking information and learning opportunities.

In the long term, the redesign aims to lead to improved user satisfaction, reduced customer support dependency, and the ongoing success of the company’s product ecosystem.

© 2024, Aviya Serfaty  |  Built by David Gershon

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01

B2C Customer Service APP

UX Design

WHEN
2019/2020
ROLE
Senior UX Product Designer
WHERE
Global leader in CS solusions

Info

About

The company focuses on providing customer service solutions for businesses (B2B). This project was developed within the company's innovation department.

What

The app is the company's first B2C product, designed to facilitate connection and act as a realtor between users and customer service providers.

Why

The app MVP goal is to overcome the “time-consuming” feeling users has expressed when calling a call center.

What else

Extra Challenge: Engaging a Team of Developers New to Collaboration with Designers.

Before

Before I joined the team, the team’s initial goal centered around creating a technical prototype to demonstrate feasibility, with an emphasis on showcasing technical capabilities.

Upon joining, my first task was to redesign the app to address key issues before a large Alpha testing phase.

This is what I inherited to begin with.

Original screens before redesign

Research

Sub-challenge

Bridging the Gap through Research

Empowering Team Engagement to Prioritize UX Issues
Research process and methods
Competitors Analysis
Data - Initial Testing group
User testing
Interviews
Questionnaires
LDJ Workshop
Analysis & Classification
Follow-up User Testing
Alpha test

As my main mission was to improve user experience and address important product issues before the Alpha phase, I recognized the challenges of prioritization within our product. Understanding that our team was new to working with a designer, especially in UX design, I saw the importance of involving them in this process.

My goal was to actively engage the team and deepen their understanding of the significance of necessary UX enhancements.

To accomplish this, supported by the product team, I pursued a multifaceted approach with a strong emphasis on the research phase to gain their full collaboration.

The secondary objective of this research session was to actively engage the team and deepen their understanding of the importance of required user experience improvements.

User Testing & Interviews

In addition to prior research that has been done, due to a prioritization challenges of key issues in the product, I initiated an extensive user testing session with 17 participants.

The goal of this expanded user testing was to enhance the team’s understanding of the importance of the required user experience improvements.

Seamless Live Streaming for Team Engagement

With user comfort in mind, we maintained a minimal presence in the interview room. Nonetheless, we encouraged team involvement by allowing them to participate via live stream – an unusual but valuable step.

LDJ Workshop

After completing the user testing and interviews, I led a one-hour “Lightning Decision Jam” with the team. This rapid session aimed to promptly address pressing issues identified during interviews and testing, even before a full analysis. The goal was to rapidly align on urgent UX issues while insights were still fresh.

Research Analysis & Classification

We had many interesting conclusions from the user testing and interviews.

I analyzed and classified the information we received in the interviews and questionnaires to examine trends and extracting unique and relevant information on special usage, thoughts or behaviors that we did not anticipate

USer testing example
Before user testing, data indicated that our initial test group of 10 users did not use the search field effectively.

Why it’s important

The app is designed to ensure a seamless user experience by promptly guiding users to the appropriate department for quick assistance. To optimize performance, users are encouraged to specify both the provider they wish to contact and the reason for their call. Failure to do so may prolong their process.

*Note – At at this stage, I was limited to work with the existing screens

Original Screens

Identified issue

I’ve noticed that the copy is not communicating this ideal way to search the system:
who + why (and not or)

in addition the “issue” scroll was very long making it difficult to find the required issue.

Repeating Problem

During the USER TESTING

We’ve tested a few different solutions based on the current screen to better understand the issue some were done spontaneously on the spot after the first day of testing, and some in advance.

*Note - At at this stage, I was limited to work with the existing screens.

Repeating Problem

During the USER TESTING

The animated test did work on getting the users’ attention and they even read it outloud, BUT the outcome was the same.

User Testing Key Findings

While privacy emerged as a primary concern, it’s crucial to note that “Recording and transcribing” calls was the most appealing feature among all users, even those with lower adoption rates.

01
90%

Rare natural detailed requests

Only 1/17 users used a full sentence (provider+issue) naturally BUT made a very long sentence.

02
90%

Knowing, Not Doing

Despite users reading the instructions within the app out loud and comprehending the need for a complete request, they instinctively asked only for the provider’s name.

03
90%

Guided Users: Complex Queries

Other users, that were specifically guided by us to compose a full issue + provider sentence, created excessively complex sentences.

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Main Insights

01

Calling a Provider & Search Experience

User testing showed that users often produced sentences that were either incomplete or too complicated, which made it difficult for the app to call a provider and reach the appropriate department. In addition, the long “issue” scroll complicated finding the required issue.

Why it’s important

The app aims for a smooth user experience, quickly directing users to the right department for a prompt assistance.

This is crucial for two main reasons:

  • Product limitations and development requirements: Swiftly acquiring this information allows backend calling and navigation processes to begin, keeping users engaged with the app.
  • Streamlined Interactions: Pre-collecting this data can simplify user interactions, supporting the primary goal of a fast and effortless experience.
02

Call recording & Transcript

Users failed to notice the recording message. During user testing, users were tasked with locating their call history. It was only upon completing this mission, unaware of its existence, that they discovered the app had been recording their calls.

Why it’s important

While privacy emerged as a primary concern, it’s crucial to note that “Recording and transcribing” calls was the most appealing feature among all users, even those with lower adoption rates.

03

Repeating Calls

Through user interviews and questionnaires, it became evident that users frequently encounter recurring issues and frustration due to unresolved problems or disconnections, leading to multiple calls for the same issue.

Users also consistently contact the same providers and departments over time, regardless of previous issues.

Why it’s important

While this issue highlights larger concerns that require broader solutions, the MVP’s primary focus was on refining the calling experience, making this insight essential for resolution and improvement of this feature.

04

Call Timing Preferences

From both interviews and questionnaires, all working individuals with typical “9-5” schedules mentioned that they perform their tasks during the daytime while at work, with many specifying the lunch break as the most common time.

Why it’s important

The wait for a customer service provider usually involves a significant amount of time. Understanding that users are calling during working hours is essential because they might initiate the call when they are free, but the customer service may take time to answer, potentially leading to users being in a meeting or unavailable at work when the call is finally answered. This factor should be taken into consideration.

05

Trust Issues & Anxiety

Primary Discovery: During user testing, we observed that despite the presence of a progress bar displaying estimated call duration, users remained fixated on the screen, even when engaged in conversation. Upon inquiry, several concerns emerged:
  • Trust: Users expressed uncertainty about the app’s reliability in initiating the call.
  • Inadequate Communication: The progress bar lacked clarity, providing only basic steps without conveying sufficient information.
  • Anxiety and Curiosity: Users felt anxious or curious about monitoring the call progress.
  • Uncertainty About Wait Status: Users, accustomed to hearing music while waiting, were unsure if they were still on hold.

Why it’s important

The app aims to seamlessly connect users with call centers, serving as the intermediary. However, when users remain fixated on the screen, this objective is not fully achieved. Additionally, it’s crucial to build trust in the app for users to feel calm and reassured about their call’s progress.

Suggested Solutions

Design challenge nr.1

Enhancing Call and Search Experience

Reminder & Approach

User testing revealed the urgent need for an improved and swifter search experience.

Acknowledging that users may not always interact with the ‘CS assistant’ system as intended, my approach focused on effectively guiding them while offering essential assistance. Recognizing that In spontaneous interactions, users may not articulate themselves optimally, I aimed to enhance navigation by anticipating needs and streamlining processes.

*Note – Presented here are low-fidelity designs based on the wireframes, integrating one of the proposed branding concepts for testing purposes.

I addressed this challenge through several strategies:

Home Screen - Recent Calls / Your Providers

  • The search field is positioned at the center while ensuring compatibility with both voice and text inputs.
  • While first-time users are presented with preferred providers.
  • Returning users benefit from access to their recent calls,
  • Additionally, search results are tailored based on provider relevance.

 

*Note – Low-fidelity designs based on the wireframes, integrating one of the proposed branding concepts for testing purposes.

User profile & Add Providers

Users can set up and update their profiles at any time, allowing them to customize their list of preferred providers for a more personalized and seamless experience.

This also helps the system anticipate their requests more effectively.

Smart Autocomplete

We implemented a smart autocomplete system capable of adapting to different sentence structures.

This included:

  • Utilizing the navigation tree (IVR)
  • Integrating popular inquiries
  • Implementing a history-based approach.

 

As for the Alpha phase, our focus was on leveraging the existing navigation tree as the foundation of our efforts.

Design challenge nr.2

Emphasize Call Recording & Transcription

Reminder

In testing, users missed the recording message.

Privacy is a primary concern, yet “Recording and transcribing” calls was highly favored by all users, even those with lower adoption rates. I approached this issue both in the initial chat and the providers screens.

Call recording & transcript - Chat

This feature encompasses several aspects:

  • Introduction: Displaying it prominently within the chat.
  • Privacy: Highlighting crucial privacy and legal aspects using simple language.
  • Flexible Options: Providing multiple choices to enhance usability:
    • Record all calls
    • Record all calls from a specific “provider”
    • Record only the current call

Call recording & transcript - Settings

Additionally, users can define their preference in their profile at any time.

Design challenge nr.3

Call Now or Later

Reminder

We found that users often make calls during work breaks, where they may not be available when the call is answered. To address this, we aimed to provide users with a greater sense of control and flexibility over their calls.

Call timing

Once the system is predicting the call timing, we communicate it to the user.

In this same message, taking in consideration that the timing of the returned call might not be comfortable, we offer the user the possibility to “call later”, scheduling the call for a more convenient time.

Additionally, when a call arrives, users can decline and reschedule it for later, with an indication appearing on the home page.

Design challenge nr.4

Trust and Anxiety

Reminder

Following the user testing, my goal is to create a more engaging wait experience and build trust step by step.

I offered a few solutions:

Trust Issues & Anxiety

  • Keeping it “familiar”: Users can connect their personal Spotify for enhanced hold music, which stops when the call arrives.

 

  • Call progress is visually represented and changes with each step, providing entertaining content for screen-fixed users. GIFs were chosen for the MVP due to their ease of development.

 

  • Additionally, we explored advanced entertainment options, including partnerships and implementations.

Results

Sub-challenge
Enhancing Team Engagement Through Research

The team’s commitment to the research was remarkable. Even the off-site development team took the initiative to observe live user testing and recorded sessions.

This not only enhanced their comprehension of the significance of implementing UX changes but also generated enthusiasm within the team for the project.
Features implementation

Assessing Improved Capabilities

Alpha Test Results

The Alpha test was conducted gradually with 50 employees.

It involved evaluating the new search abilities, though with some limitations:

  • Autocomplete was based IVR (phone tree)
  • Autocomplete based on users’ history
  • Tags based on phone tree (IVR)
  • Partial autocomplete based on popular issues, without AI integration

 

Initial data indicated an immediate enhancement.
However, given that these were internal users, we cannot guarantee they solely utilized the app for its intended purpose, despite our guidance.

Results from Follow-Up User Testing (5 Users)

After the initial user testing and throughout the alpha phase, the additional features were evaluated and proven effective.

More screens from this project

© 2024, Aviya Serfaty  |  Built by David Gershon