Nº 01OverviewFinding the man of your dreams
TrueData's core product is matching our customers with the perfect audiences for them. For a long time, this was a manual process, performed by our wonderful Customer Management team and Sales. Our team would process the results and email them to our customers. As our client list grew, the workload was not scalable for our Customer Management team and we decided to take our internal tool and make it customer facing.
Over the next year and a half we would take this tool from a bare form to a unique tool that solved pain points in ways none of our competitors were.
The tool I was updating looked like this:
- Audince name input
- List of apps your customer would ideally have installed on their mobile devices
- List of apps your customer cannot have installed on their mobile devices
- Age range of targeted audience (check boxes)
- Gender of Target Audience (only M/F options)
- Device Characteristics (Phone manufacturer, and Model)
Nº 02Learning From the Best
The first iteration was an opportunity to build TrueData's first design system, implement new UI to our newly customer-facing product, and nail down the IA. We wanted to get the tooling in our customers hands as quickly as possible, and began testing with them immediately. Talking to 5 customers, I performed qualitative research to learn more about what was needed in the product, what was desired, what our competitors did right, and where our competitors had failed.
This is what we thought our customer's journey looked like:
- Company creates new product
- Marketing team does competitive analysis
- Marketing does research into ideal targeted customers
- Marketing begins marketing plan
- Marketing selects exact makeup of ideal customers
- Marketing delivers advertising campaign
- Succesful Ad campaign
Nº 03Small Changes, Quickly
Our customers needed us to help fix how they select their ideal audience. This process was long and convulted on competitors platforms. This would improve our target metric of outperforming our competitors, and lower our customers cost per click. Additionally we had no way of visualizing for the users the total size of the Audience was. Finally, our aesthetics needed updating, so I built our companies first design system to apply to all designs moving forward.
I started by adding specificity to the Audience Builder. For each selection I included logistical operators such as "and"/"or". I knew not all marketers come from a tech background, and included tooltip hovers and contextual visuals.
Nº 04Getting Feedback
Next, we added an "Audience Scale Meter" to not only show the size of the selected audience, but to Give context to our Marketing customers about what the size of the selected audience means. For example, if the audience is too large, the benefits of targeting becomes nearly useless. If the audience becomes too small, your campaign wont have enough reach (If it gets TOO small, you're invading privacy, and I set up safeguards to prevent individual privacy being invaded).
I presented these designs back to our engineers and our customers and wrote a research document to clarify my findings. The general feedback was:
Nº 05Final StateSCROLL ↓
Actual : 4.7/5
Goal: N/A → 5
Actual : N/A → 2
Goal: N/A → < 1.00%
Actual : N/A → <.0004%
Goal: 0.90% → 1.00%
Actual: 0.90% → 1.24%
Goal: $3.35 → $2.50
Actual: $3.35 → $1.47
Goal: 100% → 120%
Actual: 100% → 180%