Exploring the Effectiveness of Help Center Content Layouts.
Exploring the Effectiveness of Help Center Content Layouts.
The goal of this project was to understand what makes an effective help center article and why. The Ads content strategy team had noticed a decrease in article traffic and customer satisfaction ratings, and sought to gain insights into user behavior and preferences in order to improve the overall user experience of the help center.
To begin the research process, I met with stakeholders to define the scope, participant criteria, and timelines for the project. To help the stakeholders identify their main questions, I set up a live meeting where I used a brainstorming canvas on Figma with empty post-it notes. During the meeting, I asked the stakeholders to write down their questions about article content models on the post-it notes.
After the meeting, I conducted a thematic analysis of the post-it notes to identify the main research questions. The key goal of the research was to gain a foundational understanding of user needs when visiting a help center and their sentiments about help center content. Additionally, my teams wanted to gather insights on how users are reading Google's help center pages.
With these goals in mind, I designed the research plan, including timelines for each step of the process and specific deliverables to be produced at the end of each phase. The research aimed to answer the following questions:
When are users typically using self-help sources in their product use journey?
What are their expectations from help center articles?
What are examples of effective help center article layouts?
How are users reading through Google’s Help Center articles? What is their feedback on content?
For this study, I sourced participants from our Enterprise recruiting database and screened them to get representation from a variety of advertiser segments, such as small to medium-sized businesses (SMBs) and agency users, with differing proficiencies and tenure with our product. To ensure a diverse and representative sample, I aimed to recruit 18 participants, allowing for 2 potential no-shows. The participants were located across the United States.
I started by doing some background research on content model creation and found a few outside sources with some general guidance. But I really wanted to get a better understanding specifically for our target users - advertisers. So, I decided to validate what I found through my research with them directly.
I scheduled 90-minute remote interview sessions with a sample of our advertisers. The goal of these interviews was to understand the user's needs when seeking self-help and to gather feedback on the visual treatments and layouts of Google Help Center articles.
The interviews were split into two parts:
In the first part, I conducted a semi-structured interview with each participant, using a set of prepared questions to guide the discussion. However, the goal was to keep the dialog open and conversational, allowing the participant to share their thoughts and experiences freely.
In the second part, I presented a set of three articles* to each participant, each with different formatting treatments. I asked the participants to scroll through the pages, glancing through the content, and thinking out loud as they read through the page. I was seeking feedback on information presentation, color formats, section breaks, etc. Additionally, I asked probing questions about specific portions of the article that my stakeholders wanted feedback on.
*Articles shown were counterbalanced to ensure each article was seen the same number of times by participants.
The study was conducted through moderated remote sessions over Google Meet, with a live stream setup for observers to watch the sessions in real-time. I also created a chat channel for observers to ask questions as they followed along. At the end of each session, I summarized interesting observations and debriefed with my stakeholders through this chat. This mini-debrief helped to keep stakeholders engaged and informed throughout the research process.
After all the sessions were completed, I conducted a final debrief session, where I went through my notes and distilled the findings based on user needs and feedback on the Help Center articles. I created a high-level summary of the findings, which I shared as a "teaser" with my stakeholders. My final report was organized by highlighting key themes that emerged from the sessions, such as the users' mental model when consuming Help Center articles, and included a section for recommendations for content model creation. Finally, I proposed next steps for the team and suggested areas for follow-up research.
The study aimed to understand user behavior when seeking self-help and what makes an effective help center article. The findings had a significant impact on the content strategy team's efforts to improve the help center.
Firstly, the study revealed that users have a variety of resources they turn to for self-help, depending on the stage of product use and the urgency of their support needs. This insight helped the team understand the user's mental model when seeking self-help and inform future efforts to improve the help center.
Based on the findings, I created guidelines and recommendations for content creation, such as providing accurate and meaningful titles for easy scannability, using bulleted lists to show step-by-step instructions, and incorporating visual cues to represent the product interface along with text-based instructions. These guidelines were crucial in refreshing over 100 help center articles, ensuring consistent visual formatting, information hierarchy, and presentation.
Another key finding from the study was the importance of in-product help as a core part of self-help. This led to a productive dialog with the product team, resulting in plans for further research to dive deeper into user needs for in-product self-help, such as tool tips and pop-up help panels.
I gained valuable skills and insights through this study. I discovered how important it was to thoroughly engage with stakeholders and effectively brainstorm their questions in order to refine and focus my study goals.
I was pleasantly surprised by how much our team valued being included in each step of the research process. It made me a more trusted and credible voice when presenting my recommendations.
I now appreciate the impact of having a solid socialization plan and sharing my findings with multiple stakeholders. I learned that the effects of my research can spread far beyond my immediate team.
I picked up some valuable skills in analyzing article traffic and log data, which will be useful in future projects.