strategic analysis to make actionable recommendations

Challenge

LinkedIn Learning sends its users dozens of emails, each with different logic, triggers, and levels of personalization. The messages feel disjointed, duplicative, and scattershot.

PROPOSED SOLUTION

LinkedIn Learning needed to understand how their portfolio of emails could work together more effectively to drive north star metrics.

METHod

Evaluate 19 emails, including their content, triggers, and timing. Using work from the User Experience Research team, identify the purpose of each email and how well it fulfills that purpose. Evaluate data metrics for each email.

HOW I COLLABORATED

I worked closely with partners from UX Research, Product Marketing Manager, Data Scientists, and Product Design to collect data.

I performed:

• Quantitative analysis of 5 performance metrics, including OR and CTR

• 2-point qualitative analysis of the purpose of each email and how well it completed that purpose

• Qualitative analysis of each email’s 6 content elements

• Identifying gaps and overlaps in the 19-email portfolio

Results

This project gave LinkedIn Learning its first-ever holistic view of its communication portfolio. I wrote a document outlining dozens of copy experiments to improve the portfolio and elaborated on the 12 most likely to succeed.

We ran 2 of them while I was at LinkedIn.

• Experiment 1 increased its Open Rate by 200%

• Experiment 2 saw a CTR lift of .2%.