COVID-19 vaxfinder dashboard
Overview
This dashboard shows data about the COVID-19 vaccine finder site, including the traffic to the site, how people get to the site, the age group and device information of site users, which city they locate, and how they engage with the site.
Data sources & links
GA vaxfinder.mass.gov view (need access to Google Analytics)
GA All Public Traffic view (need access to Google Analytics)
Dashboard filters
The date selector at the top defaults from 02/11/2021 to today.
Also, a filter of Hostname=vaxfinder.mass.gov
is applied to the whole report, except to the 2 charts showing traffic to mass.gov on page 1.
Page 1: Vaxfinder traffic
The 2 scorecards and the chart at the top show unique pageviews and users to the vaxfinder site.
Below these, the line charts and bar chart show the traffic by hour and by weekday respectively. The middle row shows vaxfinder data, and the bottom row shows Mass.gov data (for comparison).
Page 2: Vaxfinder acquisition and demographics
The top left table shows what page on mass.gov brings people to vaxfinder.mass.gov. A filter of previous page path starts with www.mass.gov AND landing page contains vaxfinder.mass.gov
is applied. (Note that the cross-domain GA data includes hostnames.)
The top right table shows sources of vaxfinder.mass.gov traffic. A filter of landing page contains vaxfinder.mass.gov
is applied.
The map shows where site users are located. The table on the right shows user numbers by region and city. A filter of event action contains click
is applied.
The 4 charts at the bottom show browser information, browser language, device category, and users' age groups.
Page 3: Vaxfinder traffic and engagement
The 4 scorecards summarize button and link clicks. They include:
Clicks on location names (filter:
event category=vaxfinder search locations
ANDevent action RegEx Match link click: ([A-Za-z]*)(:)
)Clicks on "DETAILS" buttons (filter:
event action=link click: DETAILS
)Clicks on "SCHEDULE" buttons (filter:
event action contains link click: SCHEDULE
)Vaxfinder home pageviews (filter:
page=vaxfinder.mass.gov/
)
The "engagement details" section shows what vaccine location people click on, what zip code, and what city or town people search. Each table uses different filters and metrics:
Top Location Link Clicks
Use a filter of
event label Regex Match /locations/
Click number is from unique event number
Details Clicks vs. Location Clicks
Use data blending to create multiple series of events data. To do this, create multiple GA data sets, each of which is filtered to one event.
Zip code searches
Searches is from unique pageview
Use a filter of
page contains ?zip_or_city=0
City/town searches
Searches is from unique pageview
Use a filter of
page contains ?zip_or_city= AND exclude page contains ?zip_or_city=0 AND exclude page contains ?zip_or_city=&
Page 4: Vaxfinder filter and last touch
The 6 scorecards show which filters people use when they search for vaccine locations. The page URL actually reflects which filter(s) people use when they search for the locations, so here we use unique pageviews and apply different filters to show the number of uses.
Show Available Only filter use
filter:
page contains vaccines_available=on
Healthcare Location filter use
filter:
page contains c_checked=on
Mass Vax Site filter use
filter:
page contains mv_checked=on
Local Board of Health filter use
filter:
page contains lboh_checked=on
Retail Pharmacy filter use
filter:
page contains p_checked=on
Show Sites Book filter use (it's a filter released on the site at a later stage)
filter:
page contains is_prereg=on
The table of outbound links from vaxfinder.mass.gov shows what external link (a link that brings people to a different site) people click on.
The table of failover pages shows the error pages and the traffic to those pages.
Page 5: Vaxfinder equity campaigns - Everbridge
The equity campaigns launched on June 17th, 2021 and use UTM codes to track Vaxfinder.mass.gov traffic brought by text messages from Everbridge.
The table at the top shows the key metrics for traffic and the click-through rate by city (where people are when they click on the link from the messages). In order to show the click-through rate in the same table, we use data blending. See below for how to do that.
The table at the bottom shows users by landing page. The reason for having this granular table is because the dimension city in the above table may not be the city embedded in the click URLs in the text messages. We would also like to know what city the users are clicking on. For example, when people click on "vaxfinder.mass.gov/?zip_or_city=worchester", the city could be Worchester or Boston from GA data.
Data blending on traffic and CTR
Under the data source on the left-hand side, click on BLEND DATA.
Choose vaxfinder.mass.gov as the 2 data sources.
Choose City as the Join keys.
On the left, add unique pageviews as the metric and rename it clicks. Add a Google Analytics segment of Sessions with Link Click events, and add the Everbridge campaign filter and Vaxfinder hostname filter to the data source.*
On the right, add users, pageviews, and unique pageviews as the metrics. Add Everbridge campaign filter and Vaxfinder hostname filter to the data source.
Hit "Save".
After having the blended data, add all the required metrics and calculate the CTR (%)
by this formula:
sum(Clicks)/sum(Unique Pageviews).
*How to create the GA segment:
In GA, add a segment
In the Advanced conditions tab, create a filter.
In the filter: Sessions include
event action
contains link click ANDevent category
contains vaxfinder.
*How to create the Everbridge campaign filter and Vaxfinder hostname filter
Everbridge campaigns filter: Include
Source=evb
ANDcampaign=equity
Vaxfinder hostname filter: Include
hostname=vaxfinder.mass.gov
Page 6: Vaxfinder equity campaigns - Nextdoor
This page is set up nearly identically to the previous page (the equity campaign), but the traffic source is different, Nextdoor, is different. The way to create this page is the same as the previous page (p.5). The only thing we need to do is to replace the Everbridge campaign filter with the nextdoor campaign filter: include Source=nd
.
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