How I used the metaphor-driven design and devised a new dashboard paradigm to illustrate the link between geolocation and programmatic advertising for geo-targeted CTV campaign analysis.
In order to build a platform to maximise the CTV ad efficiency and conversion for car dealerships I was invited to think out of the box during an ideation phase. I chose to clearly illustrate the relationship between geolocation and programmatic advertising for beginners. My solution involved a novel approach that went beyond traditional dashboards.
My Role
As a Toptal information visualization specialist, I participated in a creative challenge and developed a user-friendly design for a programmatic geolocation campaign analysis tool.
Tools:
Miro, Adobe XD
Methods:
Competitor analysis, getting to know a new domain. Ideation, interactive information visualization, Clickable demo.
The problem
A leading streaming advertising platform tailored for automotive marketers, which streamlines the planning and measurement of CTV campaigns for car brands, discovered that users disregard its recommendations, leading to suboptimal performance. The project brief emphasized that making users recognize the platform's recommendation power is crucial for their future success.
At the start of the ideation phase I carried out a rapid competitor analysis. I participated in competitors demos and direct sales pitches to experience the adtech complexities from a novice's perspective, which indeed I was.
How can we make car dealers understand the power of the platform ad recommendations and empower them to make better decisions?
This overview shows how I acquired extensive knowledge in an unfamiliar field and leveraged my newcomer perspective to empathize with users and simplify a highly complex process. It details my development of a new bottom-up paradigm, utilizing metaphors and spatial information organization, and the approach I adopted to create it.
Process
I decided to create a top-bottom process, where I show the users a bird’s view perspective and enable them to drill down and understand the details in context, contrasting with the conventional bottom-up dashboard approach that requires users to piece together an overall perspective from fragmented information.
Brief Goal
Take complex concepts and convert them to simple, digestible insights that arm clients with
the knowledge to understand how well a campaign is doing and what levers they can pull to do
better. If done right, this will be a white labeled sales tool.
Scope
Each story should be in its dashboard.
Be creative. There are no constraints or boundaries.
Information can be conveyed in many ways, and we want to see your unique flavor.
Design for desktop.
Persona
Car dealership owners using an analytics platform to manage geo targeted campaigns.
Action
My Design Approach
Dashboards give you bite-sized information. As a user, you are supposed to prioritize and discover the underlying ties to build the whole picture. My approach is different. I want the user to inspect a bird' s-eye perspective. I do this by using data stories.
Think about the story of several blind people inspecting an elephant, each touching a different part and convinced that they confront something different. They try to see what’s in front of them, each inspecting a different aspect; none can perceive the whole. Creating a data story enables users to inspect the whole picture, meaning the elephant, and not discreet parts, such as the tail.
That is how a metaphor works; you understand the elephant story and migrate all its aspects to thinking about dashboards and data stories. We’ve established a common language and can discuss further aspects of dashboards and data stories in terms of the elephant story, such as speaking about a learning curve in terms of the anguish the blind people experience or about how to add links between widgets in terms of establishing communication between the blind people in the stories
Plan: Provoke interest, guide, educate
UX methods:
Understand the problem space
Locate the principal factors and their interrelations
Define a bird’s view perspective
Discover a working metaphor to illustrate all levels
Discuss the problem space in terms of ratios and dynamics instead of engaging with discrete info-bytes
Visualize information in context
Task: Media Efficiency
The task involves understanding the interaction between geo-regions (Zip Codes, DMA, State, Country) and four key areas: media spending by an automotive dealership, conversion data (sales and traffic), adherence to recommended media exposure, and volume of media exposure. The objective is to evaluate the campaign's effectiveness and identify growth opportunities by comparing media spend locations, sales conversion areas, and the extent of exposure within recommended geos. Recommendations are tailored based on the dealership's sales footprint, suggesting a radius that matches historical sales data.
Brief - Story 1
Background/Explanation of Geo Regions, listed from smallest to largest:
1. Zip Codes
2. DMA
3. State
4. Country
We want a complex interaction between the four questions from this story.
1. Media Exposure:
Where did the campaign (automotive dealership) spend media dollars?
2. Conversion Data (Sales and foot traffic data):
What were the sales where customers were exposed? Where did web traffic and foot traffic conversions come from?
3. Recommended Media Exposure:
Did the campaign have media exposure in the recommended geo?
How much media exposure did they get in their recommended geo and outside of their recommended geo?
4. Volume of Media Exposure:
Where do the sales come from?
Where is the campaign running?
The data should show where the opportunity for growth is.
FYI - Where our recommendations come from:
Our Geo recommendation comes from their sales footprint. If they sell within 5 miles of their dealership, we recommend 5 miles. If they sell within 30 miles of their dealership, we recommend 30 miles. It’s based on their sales footprint.
Actions
Design Considerations
Limitations and Challenges of Using Zip+4 Centroids in Ad Tech for Geotargeting CTV Performance Analysis.
Limitations
The main task was to leverage insights from a comprehensive competitor analysis I conducted to make informed decisions about our app's UI design. While Zip+4 centroids offer some advantages for geotargeting, they also come with limitations and challenges, especially when analyzing CTV campaign performance. See presentation
Accuracy Zip+4 centroids represent the average location of all addresses within a specific Zip+4 code, not individual households. This can lead to inaccuracies when attributing campaign performance to specific neighborhoods or streets, especially in densely populated areas.
Granularity: Targeting at the Zip+4 level offers limited granularity compared to using precise location data (e.g., individual addresses or GPS coordinates). This can hinder efforts to understand how campaign performance varies within smaller geographic areas.
My solution
Based on the limitations of the Zip code as a geographical principle for spatial info organization (see Design Considerations - Story1), I use the Roman map distance annotation as an inspiration to organize information according to their distance from the dealership.
Mid-fidelity mocks
The map is presented in the context of the distance from the car dealership. This organizational principle allows for comparing additional data layers, such as demographic relevance, within a certain distance of the agency.
Within the 5-mile radius, the dominant demographic consists of young professionals, followed by retirees and families. Predominantly, established professionals are located within this vicinity. In terms of CTV ad targeting, young professionals represent the most receptive audience segment, while retirees demonstrate the lowest engagement rates. Established professionals, however, constitute the primary target demographic for your dealership's advertising efforts. Click 'Recommendations' on the upper right side for tailored campaign strategies.
