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    Episode 4: Enhancing Data Visualization for Better Healthcare and Business Operations

    In healthcare, data visualization significantly accelerates information analysis, maximizes process efficiency, and optimizes costs. It helps organizations view complex data in comprehensible formats to detect anomalies in billing, drive informed decision-making, visualize trends, and walkthrough customer behavior patterns.

    And that’s an interesting point of discussion in the fourth episode of our marketing analytics podcast series – Enhancing Data Visualization for Better Healthcare and Business Operations.


    What you’ll learn:

    • Analyzing Customer Behavior with Data Visualization
    • Simplifying Data Presentation for Business Owners, Patients, and Other Stakeholders
    • Identifying Trends Through Dashboards, Charts, Scatter Plots, and More

    Featured Speakers

    CMO Analytics Podcast – Episode 4 – Transcription

    Shayla: Welcome back to another episode of our six-part marketing analytics podcast series, Marketing Analytics Central – Conversations on Blazing Ahead with Data. My name is Shayla Wentz and I’m your host. In our last episode, Adding AI and Machine Learning to the Marketing Analytics Mix for achieving peak performance, we talked about the role of AI and machine learning in marketing, integrating AI through various tools within an organization’s tech-stack, using AI-powered analytics to gather inputs from different tools and datasets, and more. Today, we’re going to talk about the need to enhance data visualization and truly unleash the power of marketing analytics to ultimately improve healthcare. With me today is marketing expert – David Edelman. David is the former CMO of AETA, a global executive advisor for digital and marketing transformation, and a member of Grazitti’s advisory board. Thank you for joining us today, David.

    David: Pleasure to be here, Shayla.

    Shayla: So David, everyone talks about the importance of the customer journey, but few people in companies talk about how the use of data informs it. Given the complex nature of how customers purchase products in today’s digital world, customer journey analysis is also more complex than traditional marketing analysis. Visualization, as we know, is storytelling with data and is used with varying levels of sophistication by many marketing analytics teams. So when we’re talking about this, why do you think organizations should make data visualization a priority?

    David: Data visualization simplifies and makes transparent key things you need to see in the data. Sometimes it’s specific numbers, but sometimes it’s trends. So let me give you an example. You talked about customer journeys, Shayla. One of the most important things about customer journeys is time. Is having a timestamp around different interactions. How long did they take, what did somebody do beforehand? Did they do it 15 minutes before? Did they do it 15 days before? All of that has different implications for what’s going on with a customer. And if you’re just looking at tables or spreadsheets, you don’t really appreciate that. So one technique, for example, that has come up in customer journey analysis is to create what’s called Sankey diagrams and Sankey diagrams actually show how many people start at a given point and then based on the thickness of the lines, 75% of people went to this, 25% when there. The lines are as long as the duration of time. So you can actually start to see the flow of people through the system that can tell you things. For example, 10% of your customers are not doing what you expected them to do.

    Um, they are calling into the call center after having a challenge or they’re not taking certain action. Um, so that becomes a problem that can be surfaced through that visualization. It can also start to see, show things in terms of understanding spikes. So seeing visualizations such as certain things are going up calls to the call center may be going up or complaints about bills are going up more specifically, or the use of a certain part of the online, um, services, the authenticated online experience is soaring. What’s going on there. Um, and you can understand that maybe it’s good, maybe it’s not, but it allows the organization to much more quickly spot things and take action.

    Shayla: And as we think about that and shift our focus, kind of back to some of the impact of the pandemic, um, we mentioned in our very first step sewed in the series, but data has been at the core of the efforts to understand and predict the impact that this pandemic will have on our businesses, employees, and, you know, our lives in general. And now considering how important data has been in the healthcare industry. How do you think data visualization can help there in terms of improving health care and in terms of organizations wanting to simplify and justify their business decisions while maximizing the return on their operational efforts.

    David: As healthcare gets more digital, there’s going to be an enormous amount of data generated from, for example, wearables or devices in the home that people are going to be using from telehealth interactions that we’ve seen before, from the digitization and tracking of everything that happens within a provider’s context, all of that can be tracked. But especially for an individual patient, we can start using data and visualization to understand how they’re doing, to understand whether or not based on combining data from a number of different things is somebody getting healthier? Are they more nimble in the way they’re able to walk after certain kinds of therapy? Are we seeing certain levels, like a1C for diabetics going down after certain kinds of behaviors? If they’re not that can also create an alarm to figure out how to handle that individual, but also more broadly to inform is the treatment working the way it should more broadly.

    And so with all of this data now the importance of visualizing it so that people on the front lines can help individuals, but then also analyzing it in aggregate to understand things such as weather care management programs, and even certain medications are working in the first place more broadly. We have opportunities to do this now at a scale we could never before. Uh, and with that visualization people who are not necessarily data scientists can look at that data and spot things. I think one of the most important things is bringing that to the front line of interactions, where providers or people in a call center, you call in – boom! that person in the call center can see what’s happened in terms of your journey. Even if they’re not a clinician, they can know there’s an issue and refer you to a clinician. If that’s what needs to happen. So I think this is a tremendous opportunity versus just simply numbers and spreadsheets, making it come to life and bringing it to the front lines and then changing processes and protocols based on that data is now I think the next level of challenge, it’s not just the question of having the data, it’s how you’re going to use that.

    Shayla: Right. Yeah, exactly. You know that you can have all the data in the world, but if you’re not getting any actionable information out of it, it’s not going to do you any good. Um, thank you so much for joining us again today, David. That’s all the time we have for this episode. Be sure to join us next time for Building a Highly Efficient Marketing Analytics Team for Organizational Success.

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