How Web Analytics Can Help Improve Your Application and Review Program

Running a successful program requires more than opening applications and waiting for submissions.

Whether you're managing a scholarship, fellowship, grant, award, mentorship program, volunteer recruitment cycle, or another application and review process, you need to understand how people are finding and engaging with your program.

Program administrators may want to know:

• How many people are visiting?

• Where is traffic coming from?

• Which outreach campaigns are generating interest?

• Are people returning to the program?

• Which devices are participants using?

• Which geographic areas are generating traffic?

• When does program activity increase?

• How does traffic relate to applications, submissions, or reviews?

Without analytics, answering these questions can require pulling information from multiple systems—or relying on assumptions.

Web analytics can provide another layer of visibility.

When combined with the application, submission, and review data inside your program management platform, it can help you understand the journey from awareness to participation.

The Challenge: Program Data Doesn't Always Tell the Whole Story

Application management software can tell you a great deal about what happens once someone participates in your program.

For example, you may know:

• How many applications have been started.

• How many applications were submitted.

• Which categories received applications.

• How many reviews have been assigned.

• Which reviews have been completed.

• Whether important deadlines are approaching.

But what happened before someone started an application?

That's where web analytics can add useful context.

1. Are Our Marketing Efforts Driving Traffic?

Program administrators may promote opportunities through:

• Email.

• Social media.

• Partner organizations.

• Association communications.

• Digital advertising.

• Newsletters.

• Events.

• Search engines.

• Alumni or member networks.

Web analytics can help identify which channels and campaigns are generating visits to your program.

For example, you might discover that an email campaign generated a significant increase in traffic, while a social campaign produced relatively few visits.

Or you might find that an outreach partner is sending more visitors than expected.

That information can help answer questions such as:

• Which channels are generating traffic?

• Which campaigns produce the strongest response?

• Are visitors arriving through search?

• Are partner organizations referring visitors?

• Does traffic increase after promotional activities?

• Which outreach efforts should we investigate further?

Traffic alone doesn't prove that a campaign was successful.

The next step is connecting that traffic with meaningful program actions.

2. Are We Reaching the Audiences We Intended to Reach?

Geographic and technology data can help administrators understand more about the audiences reaching their programs.

Depending on available analytics data, you may be able to examine:

• Country.

• Region.

• City.

• Device category.

• Browser.

• Operating system.

• New versus returning users.

This can be especially useful for programs with geographic recruitment objectives.

For example, if a fellowship is actively recruiting candidates nationally but most traffic continues to come from one region, administrators may want to review their outreach strategy.

Similarly, a significant increase in mobile traffic may be a reason to pay additional attention to the mobile application experience.

Be Careful With Demographic Conclusions

Web analytics shouldn't be used to assume that website visitors represent specific demographic groups unless you have reliable data supporting that conclusion.

Geographic data can indicate where traffic is coming from, but it doesn't necessarily tell you whether visitors meet your program's eligibility requirements or represent the candidate groups you want to reach.

Use analytics as a signal that helps you ask better questions—not as proof about who an individual visitor is.

3. Are People Engaging With Our Program Information?

Traffic volume is only one part of the story.

Engagement metrics can help administrators understand how visitors interact with program information.

Useful measures can include:

• Sessions.

• Engaged sessions.

• Average engagement time.

• New and returning users.

• Page views.

• Traffic by device.

• Traffic by source or campaign.

• Configured events and conversions.

These metrics can help identify patterns worth investigating.

For example, if a landing page attracts significant traffic but very few people move toward the application, administrators may want to review the page.

Possible questions include:

• Is the opportunity clearly explained?

• Are eligibility requirements easy to find?

• Is the deadline prominent?

• Is the call to action obvious?

• Are application instructions understandable?

• Does the page work well on mobile devices?

• Are visitors arriving from an appropriate traffic source?

Analytics can tell you what is happening.

Determining why it is happening usually requires additional investigation.

4. Where Are Potential Applicants Dropping Off?

One of the most useful ways to combine analytics and program data is to compare stages of the participant journey.

A simplified journey might look like:

Program page visit → Application page → Application started → Application completed → Application submitted

Tracking these stages can help administrators identify where participation changes significantly.

For example:

High traffic + few application starts

This may suggest that the program page, eligibility requirements, audience targeting, or call to action deserves review.

Many application starts + fewer submissions

This may indicate that administrators should investigate the application experience, requirements, deadlines, communications, or other possible barriers.

Strong desktop participation + weaker mobile participation

This may be a reason to test the experience more closely across devices.

The important point is not to assume the cause from one metric.

A drop-off is a signal for investigation, not an automatic diagnosis.

5. Can We See the Impact of a Campaign Quickly?

Web analytics can be particularly useful when program teams launch time-sensitive outreach.

Imagine applications close in two weeks and submissions are lower than expected.

Your team sends an email reminder, posts on LinkedIn, and asks partner organizations to promote the opportunity.

Analytics can help you see whether traffic changes following those activities.

You might compare:

• Traffic before and after outreach.

• Sessions by source.

• Campaign traffic.

• New versus returning users.

• Geographic activity.

• Device activity.

• Relevant configured events.

That gives the program team faster feedback than waiting until the application deadline to evaluate the entire campaign.

6. What Can Analytics Tell Us About Reviewers?

Analytics can also provide useful context about reviewer activity, but this is an area where interpretation matters.

Web analytics shouldn't be used to determine whether someone performed a good review based solely on time spent in the system.

A reviewer who spends 15 minutes on an application isn't necessarily less thorough than someone who spends 45 minutes.

Instead, combine relevant analytics with program-level review information.

Administrators may want to examine:

• Review assignments.

• Completed reviews.

• Outstanding reviews.

• Reviewer workload.

• Review completion rates.

• Progress toward deadlines.

• Activity across review periods.

These measures are more useful for identifying workflow bottlenecks than attempting to judge reviewer quality based on browsing behavior.

7. Which Metrics Actually Matter?

One of the risks of analytics is measuring everything simply because you can.

Program administrators don't necessarily need dozens of charts.

They need metrics connected to specific questions.

A practical program analytics framework might include:

Awareness

How are people finding the program?

Look at:

• Users.

• Sessions.

• Traffic sources.

• Campaigns.

• Referrals.

• Geographic traffic.

Interest

Are people engaging with the opportunity?

Look at:

• Engaged sessions.

• Engagement time.

• Returning users.

• Relevant page activity.

• Configured events.

Application

Is interest turning into participation?

Look at:

• Applications started.

• Applications completed.

• Applications submitted.

• Relevant conversion events, when configured.

Review

Is the evaluation process progressing?

Look at:

• Reviews assigned.

• Reviews completed.

• Outstanding reviews.

• Reviewer progress.

• Review deadlines.

Program Performance

What can we learn for the next cycle?

Compare:

• Outreach channels.

• Campaign performance.

• Application volume.

• Submission patterns.

• Reviewer progress.

• Program timelines.

• Historical trends.

The goal is to move from collecting data to answering program questions.

How RQ Platform Makes Web Analytics More Accessible

Google Analytics 4 can provide powerful information, but program administrators may not want to spend their time building reports or navigating a separate analytics environment.

RQ Platform's Web Analytics Dashboard helps bring relevant web analytics into a program-focused reporting experience.

Administrators can use analytics to understand areas such as:

• Current program traffic.

• Active and new users.

• Sessions.

• Engagement.

• Traffic by country.

• Traffic trends over time.

• Device activity.

• Channels.

• Campaigns.

Combined with RQ Platform's application and review data, this provides a broader view of how people are discovering and participating in a program.

Instead of looking only at the final submission number, teams can begin examining the journey that produced it.

From Analytics to Action

Analytics are valuable when they lead to better decisions.

Here are a few examples.

Analytics show mobile traffic is increasing.

Action: Test application pages, instructions, forms, and key program information on mobile devices.

A campaign generates traffic but relatively little participation.

Action: Review the campaign audience, message, landing page, eligibility information, and call to action.

Traffic increases significantly immediately before the deadline.

Action: Consider adjusting the communications schedule in the next cycle to encourage earlier participation.

A particular referral source generates consistent traffic.

Action: Consider strengthening that partnership or examining whether similar organizations could help with outreach.

Application starts are strong but submissions lag.

Action: Review the application requirements, instructions, reminders, deadlines, and participant feedback to identify potential barriers.

Analytics don't make the decision for you.

They help show you where to look.

Build a More Complete Picture of Your Program

Submission totals are important, but they represent only one point in the participant journey.

Web analytics can help program administrators understand what happens before a submission:

• How people discovered the program.

• Which outreach generated interest.

• Where visitors came from.

• What devices they used.

• Whether they returned.

• How traffic changed throughout the program cycle.

Combine those insights with application, submission, and review data, and administrators can develop a much more complete understanding of program performance.

That visibility can help teams refine outreach, improve the participant experience, allocate marketing resources more effectively, and make better-informed decisions from one program cycle to the next.