People Design Business
Developing a deep understanding of small advertisers to build the right solutions, in the right way, and create a 3-year team strategy
Generative and observation research: I partnered with Product, Design, Data Science, Engineering, Product experience analyst supporting my team.
Literature review: While I conducted the review independently, I partnered with different business units working with a similar audience to build a shared vision.
Immersion: 4 teams within the same business unit, including the PM lead for that unit.
A top social media company.
The team lacked a foundational understanding of the audience they were building for: their processes, constraints, challenges and needs from social media platforms. As we planned to build our roadmap for the next half, year, and a 3-year strategy, a deep understanding of users was critical to determine the most impactful focus areas.
A mix of generative research, observation research, literature review, and in person immersions helped build this detailed understanding. Instead of conducting all the research in one go, it was split into multiple phases, studies and goals to enable short term roadmaps, learning and iteration and going deeper into strategic themes.
summary of the approach
Foundational research to understand SMB Advertisers, their process, challenges, perceptions to chalk the problem landscape and generate key themes to focus on.
Observation plus interview to dive deep into one of the top identified themes: making an Ad creative.
Literature review / synthesis of Jobs-to-be-done for detailing another theme: post launch Ad management and improvements.
Immersion to enable cross functional and cross team partners to learn about and directly from the people they build for, but rarely interact with.
The following sections will detail the context, rationale behind the chosen methodologies, key information areas, stakeholder engagement and impact of each study.
foundational research to understand process and generate themes
The team was looking to evolve their flagship automation product for small advertisers. Data (UXR, data science, product marketing and engineering experiments) suggested that the direction the team had been considering (a subscription product) would not be ideal. So, we needed to identify a new direction.
HYPOTHESIS FOR A NEW DIRECTION
The team hypothesized that some form of a robot ad agency would be valuable - providing agency like help to advertisers using machine learning.
NEED FOR RESEARCH
We lacked foundational knowledge on advertiser's journey, their pain points, their perceptions towards ad automation, the role they want us to play, and what a robot agency even means - all of which would be critical in designing a successful solution.
key information areas and techniques
Ad strategy: What are the top advertising moments and goals? how do they make decisions on different ad components? Where do they feel confident and where would support be helpful?
What are the key jobs-to-be-done while advertising? Which jobs are the hardest? Which are the most time consuming? Which jobs would the advertiser rather outsource and their expectations from an agency.
Measurement: What is an example of an Ad they'd consider a success? a failure? How is this measured? How do they leverage the insights we provide? How do we make them actionable?
Process: What is the high-level workflow of key JTBD, on or off platform?
What role could automation play in their ad journey? What should and shouldn't be automated? Why? How might we overcome these barriers? What are the gaps in the current solution?
Desired role: Write a letter to the team -What role does we play for their business today? What role would they like us to play in the future?
Roadmap and strategy: Research highlighted the biggest challenges our users face throughout their journey. This influenced both, the short-term roadmap (to be executed within a half, for example improving discoverability of Ad insights), and focus areas for the 3-year strategy (confidential). Prioritization was based on value to the user, team's metric impact and engineering lift.
Product evolution: Generated themes for brainstorm for next evolution of the automation product, highlighted which parts of the journey would be most valuable to automate, performance expectations, and design principles to increase trust and adoption of an automated solution.
New focus areas: Findings indicated the importance of parts of the user journey to advertisers that our product team hadn't considered thus far.
The next 2 sections delve into 2 of the identified themes: Content / Creatives for the Ad and post launch Ad management.
observation research on Ad creatives
The content / creative used in Ads was not only one of the most challenging and time-consuming aspects for advertisers but was also strongly associated with the team's success metric, thereby making it an important focus area.
NEED FOR RESEARCH
We didn't have an understanding of the end-to-end workflow or experience of the tools used by the advertiser for content creation. This information was essential to narrow down what problem we should solve for and expectations from potential solutions. Additionally, there was an increasing interest in understanding video creation.
This was a critical topic for multiple teams. To ensure research efficiency, higher impact, and a shared perspective, we created a group with UXR representatives from each team to cross share plans, learnings and partner where needed.
A TYPICAL SESSION
Participants shared examples of different styles of content they had created. They were then asked to create a sample content in real time which gave an opportunity to observe the process, tools and features used, the time each step too, and challenges faced.
Observation was followed by discussion to understand perceived value and expectations from potential solutions we could offer, experience with our existing solutions, perceptions around automating content creation, and video content creation.
Hypotheses created with Product and Data Science
Problems that users will want us to solve.
Types of solutions they will find compelling.
Feature expectations from those solutions.
Device preferences for content creation.
Reasons for low usage of video creatives
Observation + interview: Given the need to understand the workflow and usability of existing content creation tools, as well as the visual nature of the topic, I decided on observation research to ensure ease and accuracy of conveying information.
Discovery of additional sub JTBD: Apart from the workflow for creation itself, research elicited additional tasks related to content (for example, integrity issues and A/B testing) - impacting our understanding of the problems to solve for.
Steering on potential solutions: Research found that the value of a solution the team was interested in exploring would be limited unless it was made as powerful as Canva, which was not aligned with organization goals. Instead, we could solve a bigger challenge, like improving visual quality, through our automation solutions.
Improving existing solutions: We found that despite needing and wanting our guidance to improve creative quality, small advertisers found our recommendations difficult to understand and/or action on.
Considerations for automation solutions: We understood the level of control advertisers desired, the biggest barriers to automation and the type of AI guidance they wanted for content creation.
literature review on Ad management
For businesses, the journey didn't end at Ad creation. Post launch, they needed to understand the outcomes of their Ad, reasons for the performance, how to improve the current and future Ads and audience insights.
While the team was aligned that these problems impacted the user's experience, they were skeptical about investing resources in it since Ad management projects hadn't moved the team's success metrics so far.
WHY THIS WAS IMPORTANT
Qualitative research suggested that perceived performance of a previous Ad significantly impacted a business's desire to advertise again and their willingness to spend. Providing insights in the right way was an opportunity to communicate performance and provide guidance. Additionally, on reviewing the projects the team had executed until then, I realized they were not solving for the biggest user challenges, which could've impacted success.
CHOICE OF METHODOLOGY
Given the lukewarm interest in this area, I decided on doing a synthesis of existing research, which would be sufficient to understand advertiser needs, and be a lot quicker and cost effective than running a new study.
SCALING CAPABILITIES THROUGH CROSS TEAM PARTNERSHIPS
Given resource constraints, I found teams in other business units that were also interested in the topic area. I partnered with their Design team to create a collaboration model that allowed us to share knowledge, resources, and build a common vision.
Synthesis on jobs to be done and challenges around Ad management shared with partner team.
Design sprint, ending in concepts
Learnings cross shared with our team.
Projects identified for either co-execution or splitting between the teams.
Concepts evaluated in research by sister team.
Experiments launched on promising solutions by sister team
WHAT WE DID
An immersion trip with 18 cross functional partners from 4 teams to understand the audience they build for, but rarely interact with.
WHY WAS IT NEEDED
Deeply understand who these businesses are, outside of 'users' of our product: how they operate their business day to day, their realities and constraints that impact their behavior on our platforms, their vision and future plans for their business.
Not all of these teams had embedded product researchers, 2 of them relying on secondary data. These deliverables were often striped of 'additional context' on the audience.
Several new members had joined the team, and connecting with users directly was a much faster way to onboard them than several large presentations.
To learn about a new segment of businesses the team wanted to build for.
RESEARCH BY EVERYONE
The team was divided into groups and each person was assigned active research responsibilities, keeping in mind personal preference and strengths: Primary moderator, secondary moderator, note taker, synthesizer, and asset collector. I provided short moderation trainings and critical do's and don'ts while interacting with participants.
A debrief workshop at the end provided the space for each group to share their learnings. To make the debrief productive, I pre-created prompts to guide the discussion. As a team, we then created affinity maps for synthesis and co-authored the final deliverable.
Cost constraints prevented hiring a vendor. I also wanted to ensure active participation by each team member, and providing each person with a role gave them purpose.
Considerations for 3-year strategy: The immersion provided confidence to some areas of our strategy, and key considerations for execution that would impact success.
Empathy: Even though some team members were aware of advertiser challenges through previous research presentations, hearing directly from the business about why it mattered to them led to a different level of empathy. This resulted in individual engineers creating lightweight experiments to solve the challenges they'd personally heard.
Answers to team specific questions: The teams without embedded researchers got an opportunity to get some of their specific questions answered as a part of the immersion.