About the Company
VSP Global provides access to affordable, high-quality eyecare to over 80 million people across Canada, Australia, United States, United Kingdom, and Ireland. The Shop, VSP Global’s innovation lab, focuses on developing technologies and design for both the physical and digital aspects of eyecare and eyewear.
The Vision and Challenge
The Shop at VSP Global was developing an innovative new product: “Smart Eyewear” focused on health tracking. The Shop was interested in gathering behavioral insights on how their pilot users were using the Smart Eyewear with the goal of improving their product through a customer-oriented growth strategy. Pat Crain, Manager of Software Engineering and Data Science, needed an analytics partner who could move quickly in a competitive market and could customize their process to suit The Shop’s needs. He also needed a partner who could competently compile data from disparate data sources and translate it into meaningful insights at scale.
“What set [InterVision] apart from competing firms was their desire and ability to understand my business context. They spent significant face time early in the project to discover the problems I was facing and my desired technical and business outcomes.”
—Pat Crain, Manager of Software Engineering and Data Science
Crain quickly recognized that InterVision was an excellent cultural fit for The Shop. Not only could InterVision tailor their process to analyze the most relevant data to the project across multiple sources, they were also eager to invest time in truly understanding The Shop’s unique use case.
“[InterVision] was a great fit for the project’s ‘culture.’ They had the right balance of process and agility.”
—Pat Crain, Manager of Software Engineering and Data Science
The Outcome
InterVision began by meeting with Crain and his team to discuss The Shop at VSP Global’s needs, challenges, and goals specific to the project, establishing a baseline understanding.
From there, InterVision developed a comprehensive four-month strategy, dividing the data analysis into two sections: raw analysis and summary analysis.
Raw analysis: Focused on data such as user activity level, usage and engagement metrics, as well as analysis of social features and goal changes. Key metrics, like intensity and drop-off, were also developed to gain a clearer picture of user activity.
Summary analysis: Zeroed in on data such as summary statistics, demographic trends, and personality traits to see how these might impact user engagement.
Just a few of the important data points analyzed included:
- Impact of social features, such as various types of notifications and likes or comments, on activity level
- Demographic trends, like activity intensity, and goal achievement by age and ethnicity
- Factors that typically drive customers to decide on using fitness trackers
- Changes in user preferences on an hourly, daily and weekly basis
In order to provide the most insightful picture of customer usage, InterVision contextually enriched existing data with data from outside sources that revealed the impact of additional factors on engagement.
For example, InterVision enriched the data with weather and air quality information. In addition, both national and local events such as the 2016 presidential debates were analyzed to understand their impact on user activity. To help the team connect the dots, visualize the data, and tell a coherent story, InterVision built a custom data visualization tool using D3.
Exploratory analysis was done using Python. Both Matplotlib and Seaborn were used to generate individual visualizations and cleanly communicate insights.
InterVision’s findings were presented in weekly updates, with supporting visuals and charts that made important trends, opportunities and details quick to digest and easy to understand.
“Their communication, including the weekly updates, was clear, crisp and actionable”
—Pat Crain, Manager of Software Engineering and Data Science
By turning such complex data into simplified visualizations and actionable insights, The Shop was able better understand the “why” and “how” behind the way pilot users interacted with their product, and what they could do to improve the experience.
For Crain, the project was a success that adequately met every one of his objectives and brought forth compelling insights that informed both product strategy and positioning.
“[InterVision] provided insights that were non-obvious; some of which directly informed our product positioning! In the end, we got a much better understanding of how our customers were using our product, features that helped engagement and how demographics trends and personality traits impacted usage”
—Pat Crain, Manager of Software Engineering and Data Science
