The goal of this project is to investigate the performance of marketing campaigns at Row Health in order to surface recommendations on marketing budget allocation for 2025 campaigns.
Founded in 2015, Row Health is a healthcare company that focuses on providing accessible and convenient telehealth services. They recently launched a marketing campaign to increase brand awareness through varying categories. They offer a range of health solutions, including 4 different tier plans bronze, silver, gold, and platinum with varying coverage and premiums.
With a new Data Team in place, the company would like a better understanding of their audience from the marketing campaign data to reallocate resources next year. Primarily focused on two objectives 1) minimizing costs from unsuccessful campaigns and high cost per signup and 2) increasing conversion rates in campaigns.
The dataset contains 3 tables: customers, campaigns, and claims including information about campaign performance, customer demographics, and claim data.
In order to evaluate campaign performance, we focused on the following key metrics:
- Campaign Cost: The total cost of a campaign calculated by the number of users that signed up multiplied by the cost per signup
- Claim Amount: The amount paid to customers who are insured at Row Health
- Click Through Rate: The percentage of people that saw a campaign and clicked the link.
Click Through Rate
- Tailored Health Plans had the largest number of impressions at 1.3 Million
- Health For All had the least (120k) amount of impressions but the highest click-through-rate of 36%
- The campaign had the highest signup rate at 2.9%, leading to 3.5K signups
- New Jersey accounts for $7.3M in Total Claims which account for more than 50% of all claims.
- 8,200 Signups came directly from NJ indicating a high amount of conversions
Campaign Cost
- Of the top 5 campaigns, Health for All had the lowest total cost of just over $2k
- While #HealthyLiving cost 120% more for roughly the same number of signups.
- Golden Years Security had the highest cost per signup at $124 with only 23 total signups.
- The bottom performing campaigns accounted for only 9.5% of all signups, but were responsible for $19,000 in total campaign costs
- Health For All had the lowest cost per signup of $0.57
- Cost per Signup is lowest in NJ at $4.10, which is significantly lower in comparison to all other leading states averaging $33.6 per signup
Claim Amounts
- Compare Health Coverage had the highest average claim amount of $410 per claim, 53% higher than the average of $267
- Compare Health Coverage has the highest total claim amount at $3.9M
- Golden Years Security had the lowest total claim amount at $16K
- The average out of pocket percentage of the total claim amount is 38.9%, all campaigns range from 37-44% indicating policy holders have varying levels of affordability
- Of all states New Jersey saw the highest number of claims at 26K, followed by just 3.7K in New York
- Bottom 7 Campaigns: Reallocate $19k worth of ad spend towards high converting campaigns i.e. Health for All, #CoverageMatters, and #HealthyLiving. This reduces expenses and increases opportunity for growth in existing campaigns
- Health for All: Retarget 40K potential customers who clicked on the campaign but did not signup, if those same users convert at a 3% signup rate it would lead to 1,200 new customers.
- #HealthyLiving: Reduce campaign cost per signup by focusing on the engaged audience, by doing so we could increase the conversion rate from 9.6% to between 15% and 25%.
- Campaigns by State: Stop campaigns in states with less than 100 total signups and reallocate capital to target users in New Jersey, New York, Iowa, and North Dakota.
The North Star Metrics for this analysis are Click Through Rate, Cost per Click, Sign up Rate, Cost per Signup. Users have access to filter by Plan, State, and Campaign Type with focuses on the marketing metrics, signup metrics, and customer claims metrics. The interactive dashboard can be found on Tableau Public here.
This presentation was made for our internal teams to get a full campaign analysis and next steps, you can view the full presentation here.
