Full Measure Education Embeds and Democratizes Data

Washington D.C.-based Full Measure Education is breaking new ground in higher education with a platform for better communication with students. Through its platform, institutions can create and manage mobile conversations with students, using data related to student behavior and interests to increase engagement and maximize the impact of staff members. In doing so, Full Measure is helping to boost enrollment, increase completed applications and positively impact students at institutions nationwide.

“With Sisense for Cloud Data Teams, we can get the same visual reports from our data, but it’s in a much more approachable, user-friendly, SQL-based interface that doesn’t require you to be a developer to use or understand. That was our biggest hurdle when I joined, and Sisense for Cloud Data Teams helped us overcome it.”

Angela Virtu
Angela Virtu, Data Scientist at Full Measure Education

Before Angela Virtu took on the role of lead data scientist at Full Measure, the responsibility of analytics fell under the umbrella of the development team. That team’s previous solution helped initially translate data from its relational database, but found that within a few months, no one on the team was actively managing it.

“Our whole goal at that time was to be able to put all our different charts and images into our end product and apps,” said Virtu. “Instead, we had charts that just didn’t work anymore because they were relating to data in tables that were always moving and changing. The team found that the experience with a proprietary data language wasn’t that intuitive, and as a result, no one was truly maintaining it. We had 30+ charts set up, but none of them actually got embedded.”

Virtu was tasked with speeding up the process to help distribute and disseminate the company’s reports and other data to clients in a way that created the least strain on valuable engineering resources. Instead of digging deeper in with their current tech stack, Virtu decided to start from scratch with a solution that would be better aligned with Full Measure’s goals of democratizing data.

“When we had our previous solution, it was this big, intimidating thing that no one else wanted to touch out of fear they’d break something, or that they weren’t capable of getting what they needed,” said Virtu. “With Sisense for Cloud Data Teams, we can get the same visual reports from our data, but it’s in a much more approachable, user-friendly, SQL-based interface that doesn’t require you to be a developer to use or understand. That was our biggest hurdle when I joined, and Sisense for Cloud Data Teams helped us overcome it.”  

With Sisense for Cloud Data Teams, Full Measure is leveraging the Embed API to embed all the charts it emails out to clients directly within its product. When end users log in to the Full Measure site, the first thing they access is a series of dashboards to track critical KPIs, like how many messages went out to students per week, or how many mobile app downloads took place.

“All these metrics are super relevant and important to our customers, and they can get them at a glance now within our product, without needing to keep track of multiple links to click,” said Virtu. “It’s all in one spot, united and integrated. It was also easier because we didn’t have to resort as many dev resources to maintaining databases like with our previous solution – I can set up whatever databases we need to access with Sisense for Cloud Data Teams and it’s much, much easier.”  

Full Measure Education’s business is built on helping its customers understand where the gaps are in the application process. Sometimes, a school’s application is easy, but there’s a large backlog of unprocessed applications – in other cases the process for checklist items like submitting high school transcripts is unclear and causes delays. Without detailed data analysis, it’s hard for schools to know where they need to make investments to improve the process.

“A lot of times, institutions really don’t know where their gaps are, or where they are struggling to get applicants to the next step,” said Virtu. “By using Sisense for Cloud Data Teams to drill down deeper into their data, we can shed more light on where their pain points are and deliver relevant content that really helps them with the gaps in their funnel.”

One of the biggest impacts that the platform has made on Full Measure’s business is enabling more trust and transparency in their work with clients. The company builds large outreach communication campaigns to students that often involve sending thousands of messages on behalf of its institutions, a process that often required laborious internal follow-up to keep track of.

“There used to be a lot of uncertainty between what we said was going to happen and what happens with our campaigns,” said Virtu. “Did this campaign actually go out? Did it get delivered to all 5,000 students we intended to deliver it to? We were wasting time asking questions that should be accessible for everyone to track.”

With Sisense for Cloud Data Teams, they’ve closed that gap instantly – they can detect in real-time how many messages were sent out for a given campaign, understand who viewed messages within their app or externally, and track countless other measures to better understand how students are engaging.   

“Trust and transparency has gone up like tenfold for us with Sisense for Cloud Data Teams, because it saves us a ton of time back and forth with email reports and cuts down on client communication around simple data questions,” said Virtu. “We can now actually talk with them about better, more exciting analysis questions instead of little things we shouldn’t be spending time on. I think that’s really big and it’s becoming a differentiator for us in our space.”

Enabling Data Insights for Every Team

As the head of data science, Virtu manages the data ingestion and infrastructure process to ensure the company has a single source of truth. But once she has created the building blocks, everyone else in the company is empowered to explore and learn from data insights. Virtu says almost everyone at Full Measure uses Sisense for Cloud Data Teams every single day.

The company’s support team uses the platform to track engagement with its customers and to quickly identify errors with campaigns that need to be fixed. The development team uses it to track internal operations efforts, and the sales team uses data as part of their pitches and demos to prospective clients.  

“We go to plenty of conferences and shows to engage with our customers, and at those events, people are really impressed with our analytics and data visualizations,” said Virtu. “It really helps our sales team make it more apparent where the gaps are in their process and illustrate our value to them.”

Meanwhile, Full Measure’s client service team uses the platform as part of their daily interactions with clients. They regularly ship dashboards via email reports, but have started directing more clients to view data directly via embedded dashboards in their product. With Embed API, Full Measure knows they can safely share data without having to worry about security concerns.

“In Higher Ed, it’s important that we don’t have our clients seeing other institutions data,” said Virtu. “With Embed API, we can set that institution’s parameters, so when they log in, it knows which institution they are with so they get a specific dashboard view. That makes life so much easier – our client team doesn’t have to juggle links or reset their filters every time we speak with a new institution.”  

From Simple Data Discovery to Complex Analysis

Moving forward, Full Measure expects they’ll soon be integrating the Data Discovery feature, a drag-and-drop interface for non-technical teams to instantly explore data with no coding required. Virtu anticipates that will free up even more of her time and enable the rest of her team to explore data further.

“Instead of having me making small tweaks to individual dashboards for our managers, our client team could just make those tweaks instead, and I can still manage the backend process to ensure they are exploring data correctly,” said Virtu. “With the rest of our team taking on those basic tasks, I can do more ROI-focused things to prove more worth to our clients.”

For example, one of Virtu’s goals for 2019 is tying data analysis to focus more on long-term outcomes for students. Instead of just looking at which students haven’t completed a FAFSA form yet, she’ll now be analyzing the key characteristics of subgroups like those who have completed every step of an application and end up successfully enrolling in the school. With one query and dashboard in Sisense for Cloud Data Teams, she can quickly pull campaign stats associated with those subgroups and truly understand which tactics were most closely associated with driving the positive outcomes for them.

“It’ll really help us explain the ROI of why mobile communications in Higher Ed matters, why texting students is better than emailing them for these groups, and really visualizing and explaining the value of our entire process,” said Virtu. “With Sisense for Cloud Data Teams, I get to spend more time focusing on bigger, predictive analytics projects like that instead of just being a report monkey.”

As Full Measure continues to expand, Virtu anticipates that Sisense for Cloud Data Teams will continue to play a critical role, in part because of having Python and R directly integrated within the platform. Virtu predominantly uses R Studio to provide regressions and modeling to some of Full Measure’s more top-tier clients. R Studio provides a wealth of visual options for building reports, but she knows that as the company scales and provides that analysis more broadly she’ll need to refine her workflow.

“As we grow, it’s not going to be a good use of my time to keep going back and forth between getting data sets in R Studio and putting everything together in Sisense for Cloud Data Teams,” said Virtu. “Having all of that available now within Sisense for Cloud Data Teams will be huge in helping us get to that next step with complex data analysis.”