Overview
The Problem
While working for Domo, a B2B SaaS company in Utah, I worked closely with their marketing strategy analysts. One of their biggest pain points was understanding the return on company marketing spending. As a booming start-up with a substantial amount of capital, Domo marketers basically had a blank check for their budget.
They needed to know how much they could spend on digital marketing efforts before seeing diminishing returns.
Proposed Solution
The Predictive Marketing ROI app is a data visualization tool designed to help marketing analysts predict the effects of adjusting their marketing spending. Using this tool, analysts are able to predict marketing performance based on their anticipated cost per lead, and marketing funnel conversion rates.
Process
Research
Through several discussions and iterative feedback, I organized relevant metrics into a clear flow of data. The only completely controllable metric is spending. The rest must be predicted based on historic performance and goal setting. I determined each metric could be organized into one of three categories:
1 - Control
Spending
2 - Drivers
Cost Per Lead
Funnel Conversion Rates
3 - Results
Inquiries (INQs)
Sales Accepted Leads (SALs)
Sales Qualified Leads (SQOs)
Wins (New Customers)
As marketers adjust spending, the rest of the metrics change accordingly. Using historic data, marketers can then determine an estimated cost per lead, which in turn provides an estimate of the number of inquiries their spending will produce. From there, marketers again use historic data to determine funnel conversion rates that will ultimately provide a predicted amount of leads and wins generated from their spending.
User Stories
I created user stories based on the most important measurements.
As a marketing analyst, I want to predict the outcome of my spending so that I can maximize inquiries, leads, and/or wins while minimizing my marketing expense.
As a marketing analyst, I want to see the results of adjusting my cost per lead so that I can set a cost per lead goal to maximize my marketing return while minimizing my CPL.
As a marketing analyst, I want to see the results of adjusting my marketing pipeline conversion rates (inquiries to leads, leads to opportunities, and opportunities to wins) so that I can set conversion rate goals to maximize my marketing return.
As a marketing analyst, I want to adjust the historic time frame (i.e. last 3 months, last 6 months, last 365 days, etc.) used in predicting ROI so that I can adjust for anomalies such as changes in marketing strategy or special events.
As a marketing analyst, I want to forecast my inquiries, leads, and wins by cohort so that I can see a trended summary of each while still breaking out which are a result of past marketing efforts and which are coming from my predictive model.
Design
States
Mockup
Additional Domo Projects
While at Domo, I designed and implemented several apps for their App Store. A few are shown here.
Facebook Fan Sentiment
As a digital marketer, you build and maintain a positive fan experience with your Facebook brand. This app can help by providing the insights you need to improve fan sentiment toward your Facebook posts.
Social Performance
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Weather Sales Impact App
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