We can capture data, but how do we make it pay off?
In their Big Data Executive Survey 2018, NewVantage Partners queried Fortune 1000 executives on their employment of big data and AI. Respondents showed a healthy appetite for data initiatives, with goals ranging from improved decision making to reduced costs. Of businesses surveyed, 73% said they have received measurable value from these initiatives. Still, many companies struggle to create a data-focused culture that pays off.
In today’s connected, mobile-driven environment, the ability to capture data is effectively limitless. But in our quest to grab information, we snag a lot of useless noise. We often focus narrowly on numbers, too. More clicks. More emails. More video views. But numbers alone don’t indicate success. Counting beans can distract us from the real power of data: to provide deep insight into the behavior of our audience so that we can better serve them.
Defining the Scope of Data Collection
One way to gain efficiency in data analytics is to measure only what matters. Increasingly, one metric we’ve focused on in recruitment is equity: getting sign-ups across the spectrum, from gender and income to zipcode and race. If we want to push the equity meter higher, we need to gather these attributes for analysis. But data collection and storage is only the beginning.
From Data Silos to Feedback Loops
Next, we need to break down silos and look at performance across all our inputs: social media, web, email, and CRM. In our work with the Alzheimer’s Prevention Registry, we use two types of reporting: a weekly report on key drivers such as goal tracking and source comparison, and a monthly analytics dashboard report. These efforts serve as starting points for a team-based discussion: What is the data saying, month-over-month, and year-over-year? What are we doing well? And perhaps more important, what needs improving?
After one such session, Provoc used data in our reporting data warehouse along with geocoding functions to identify the closest study site to potential participants. As APR already understood, people who live closer to study sites were much more likely to enroll. Through collaborative discussions, the team ultimately decided to target outreach efforts within a 50 mile radius of program sites. Additionally, a map of program participation in relation to existing study site partnerships helped to identify potential sites for future efforts.
The Power of Microtargeting
Don’t forget that analytics can move well beyond broad categories such as gender to examine discrete behaviors that impact recruitment program performance. Consider a multi-page online process by which participants give consent. Data analytics reveal that at each stage of this process, participants drop off. We can track drop offs stage by stage to pinpoint weak spots, then adjust content to reduce cognitive load and increase follow-through. This helps us improve overall response rates and adjust forecasting so we can set and achieve specific, measurable goals. And with sharp data collection and analysis, microtargeting can be applied to any number of other interactions as well.
The Future: Mobile Integrated Study Interest Reporting
How does a clinical trial manager leverage analytics to maintain a holistic view of prospective interest in each study? In 2018 we are seeing more requests for study interest reporting, which looks at not just the direct result of recruiting effort in terms of numbers, but in the indirect numbers as well:
- How many people responded to email about a study?
- How many shared it on social media?
- How many people visited a study web page and clicked to indicate “I’m Interested”?
- How many filled out a form?
- How many visited other studies?
- Which kinds of people are interested in which kinds of studies?
Having such data would enable clinical trial managers to measure their efforts at engaging with their audience and building the trust necessary to gain commitment for study participation. And it would allow managers to evaluate the relative cost-effectiveness of web, email, and CRM efforts and shift resources. Ideally, this integrated data would be available not just in monthly reports, but anytime, and preferably in mobile formats. In short, successful recruitment efforts evolve when we pay close attention to data analytics so we can increase study interest and improve participation rates.
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