How can Valassis reduce its need for legacy software, help Business Analysts optimize digital ad campaigns more efficiently, and drive consumer savings?
By understanding our users, their day-to-day operations, pain points, and desires, we could provide Business Analysts with a more efficient method of campaign optimization and balanced workloads by building an entirely new product.
Team
- Dane Wesolko – Sr. Interaction Designer
- Clay Porter – Sr. Visual Designer
- Landon LaPorte – Sr. User Researcher
- Patrick Lawson – User Researcher, Intern
The Challenge
Expertise and delivery are the reasons clients continue to choose Valassis. However, significant complexities go into managing a digital advertising campaign. Monitoring and optimization are essential elements to their success. Minor adjustments to how an advertisement gets served can make a difference in its impact.
The internal team at Valassis relied heavily on highly technical Data Scientists and Business Analysts to perform these functions. Working in Python, R, and custom Jupyter notebooks executing terminal commands, these technicians could analyze performance data and make adjustments when necessary.
However, this posed a serious problem as there was a vast knowledge gap and reliance on a small subset of individuals. A cross-collaborative team and I set out to close that knowledge gap and create a solution that would make it easier for other less technical Analysts to join in on the optimization.
Finding Opportunity
Valassis saw an opportunity to create a more straightforward solution for Business Analysts to make changes to live campaigns to provide clients with more efficient ad spending. As well as a chance to deprecate legacy systems and remove the need for particular technical skill sets only had by a few.
Through developing an experimental interface, internal product research, and brainstorming sessions, we collected essential data that shed light on the current situation and helped shape the project’s direction.
Working Through
In the project’s initial stages, it was unknown what the actual outcome would be. There were a lot of different avenues that we as a team could have gone down. For us to start shaping a direction, the Lead Engineer and I created an experimental interface that we released to a small group of Data Scientists. We understood how and what optimizations were being done by collecting usage data. Through the collection of this data, we were able to shape a narrative.
Once we had a clear understanding of how and why users might be making optimizations, we were able to start a more formal discovery process. Through this discovery process, User Researchers and I conducted a series of interviews that shed light on current workflows and processes. Those workflows and procedures began to expose gaps and shine a light on areas for improvement.
We conducted further research via contextual inquiries, which gave insight into the primary user and their role within the organization. Once I understood who we were designing for and what they needed, I suggested we conduct a collaborative design workshop.
During this design workshop, as a group, we understood the primary needs of a Business Analyst by performing task modeling exercises. During our conversations, users also exposed their most significant pain points and exposed improvement areas. As a way to collect further information, I provided participants with printed-out templates of a potential interface shell where they could sketch ideas and help shape the project’s overall vision.
Upon completing the workshop, I had a significant amount of data exposing many elements worth considering. With this data, I created an application architecture diagram and high-fidelity interactive prototype that was used as a communication tool setting the tone for the overall project which allowed us to prioritize a direction and minimum viable product.
An interactive prototype created in Figma allowed me to share the overall vision and depth in which this project could cover.
Based on the research, I understood that designing a new product from the ground up could become quite an arduous task that would span a more significant part of a year and require many additional resources. By understanding the core requirements of our user base, we were able to present these findings to leadership and make a case for a new workflow process and a more iterative approach to production.
In doing so, project stakeholders agreed that the main priority would be to create a scalable and functional product centered around a business analyst’s core tasks, allowing for future improvements and enhancements.
My design process began by assimilating all of our findings. Once I was done digesting the data, I created multiple sets of static wireframes used as tools for communicating the vision and further narrowing down the scope.Once I was able to get a clear idea of the main features and functionality required, it was then that I began rapid prototyping in place of wireframes to explore interaction patterns and user flows.
To keep our existing product platform consistent, I shaped a lot of the design off of existing application structures and components. I did most of the work by creating interactive prototypes in Figma. This approach made it easier for all parties to understand the vision clearly.
Upon completing the initial work, I provided components and page models to engineering for use in developing the front-end. Participation in cross-collaborative grooming efforts helped aid in project management and ensured that we met all timelines and milestones.
No further work was scheduled at that time, all deliverables were provided, and Valassis Engineers continued with development. Tasks and deliverables performed were:
- Product reviews—aiding in understanding the current internal ecosystem
- Stakeholder/User interviews—assisting in understanding the goals and needs of both the business and primary user
- Contextual Inquiries—direct observations of the users day to day activities
- Design Workshop—a collaborative approach to solving complex problems and gaining first-hand insights
- Workflow/Task Flow Analysis—showcasing the paths users took to complete tasks
- Application Architecture Diagram—giving insight into the full depth of a comprehensive product
- Interactive Prototypes—acted as visualizations and communication tools
- Usability Tests—provided valuable feedback validating ideas and shaping improvements
Post-launch, the team established a feedback loop and iterative cycle to improve the product.
The Results
In working with a cross-collaborative team at Valassis, broken down into prioritized sprints over two quarters, we were able to build a new product from the ground up. Building this product created a better working environment for Business Analysts making it easier for them to:
- Balance workloads and share internal information
- Monitor and optimize campaign performance
As a result, it is expected that internal teams can communicate easier regarding adjustments and optimizations made to online advertisement campaigns, gain quicker insight into the performance of each campaign, reduce operating costs, and deliver better results for clients.
Reflections
Since this project was a big undertaking with many moving parts, we initially had to whittle down what could be done with the given timeline and budget. While the project went well overall, I learned a lot about the core group and wanted to ensure that the design was scalable within our system. Looking back, one of the main areas we could not improve upon was system communication and feedback.
Given more time, I would have liked to look into ways that we could improve how the system communicates to our users essential and actionable information, as well as a better system for managing alerts and communications.