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GSA / px-benefit-finder

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v2 Deep Dive Analysis #867

Open nickpistone opened 7 months ago

nickpistone commented 7 months ago

2 months after launch (March 18th), if sufficient data has been collected, conduct deep-dive analysis of Benefit finder pages. This includes looking at combined funnel to see where the main dropoff points are across LEs and languages as well as analyzing specific LEs in both languages. We currently expect to have enough traffic to do this for all LEs in English and Disability in Spanish. DOLO and Retirement in Spanish may not have enough traffic to get reliable insights at that time. But we should at least be able to look at Spanish Disability and compare to English Disability to get a sense for how the two audiences compare.

Questions to answer/metrics to measure: Where are the biggest dropoff points? Are there any major differences between LEs? Do they have the same dropoff points? How close are we to hitting our KPI targets? How many people click on "Review Selections" and how does that correlate with conversion rate? What is the conversion rate for each LE in each language? Conversion rate by traffic channel (for highest-traffic LEs) Conversion rate by device type (for highest-traffic LEs) How many users visited multiple LEs or multiple languages since launch? Visits from partner agencies Engagement Time Engagement Rate Conversion rate during first visit Traffic channels and top sources Traffic coming to BF pages that landed on one of the blogs

fongcindy commented 3 months ago

@nickpistone Is this something you plan to check again (after 1 year?)? We plan to archive this ticket, please advise. Thanks!