Your Data Is Going Virtual
How VR combines with AI to help marketers do even more with data.
When someone takes a “deep dive” into data, it has never been literal — until now. Data visualization is a growing field that, along with artificial intelligence (AI), is important for helping marketers understand what their data is telling them and literally see what they need to do to optimize their efforts. The next step? Data visualization that let’s people get inside that data.
Data is central to delivering a personalized customer experience, but too often companies find themselves inundated with more data than they know what to do with. Given the advances and proliferation of AI, though, now more than ever people can better understand and visualize data. This makes the data insights you have more readily accessible and actionable, creating greater value for both your brand and your customers.
More data, more problems
If you’re like most marketers, you’re probably struggling to keep from drowning in customer data overload. The real problem, though, isn’t the amount of data — it’s making sense of it all so you can take decisive, meaningful action.
Most marketers spend 10 percent of their budgets on analytics, but only use one-to-three percent of the data collected. While analytics tools are consistently growing in sophistication, the explanatory tools that designers and marketers need to visualize and communicate with data have remained relatively stagnant over the last two-plus decades.
As you start to unpack not just the data, but also the underlying meaning and cause behind your customers’ actions, you need a new way to view, interact with, and engage with existing data. AI can be that solution, helping you get to the true meaning of your data quickly and intuitively, using automated, intelligent data analysis capabilities.
Visualization — the key to understanding data
That analysis, though, is just the beginning. With insights and predictions are so readily available, marketers can now tap into new interactive ways to visualize and interact with data, making it even more “usable.” A good example is graphic and dynamic visualizations.
“Data visualization is a great way to communicate a lot of information very quickly,” says Bernard Kerr, Adobe senior experience designer. Adobe is prototyping in this space with Project New View, which uses new ways to view and interact with data — with a total balance of creativity and data analysis.
Integrating AI in data visualization
The unifying link, then, is AI. Not only can AI automate and simplify data analysis but, in the visualizations landscape, this technology can help make insights and predictions readily available at a speed and scale not seen before. As a result, data is better democratized and can be better utilized to drive efficiency, effectiveness, and more customer-first experiences within an organization.
Given these benefits, it’s no surprise this technology is gaining in adoption. While just 15 percent of enterprises are currently using AI technology, 31 percent plan to use it within the next year. And with this growth, many companies are anticipating the opportunity to understand and manage data through visualization.
Key use cases and unique AI-driven benefits
High-momentum startup Virtualitics, for example, merges AI and AR with big data for clients in finance, pharmaceuticals, and energy. The team recently closed a $7 million funding round, no doubt signaling significant growth in the not-too-distant future.
Beyond Virtualistics, the industry is seeing meaningful movement from Atomic Fund, a crypto investment fund that recently leveraged 3Data’s immersive data visualization platform to explore a data set surrounding a recent Bitcoin market crash.
Rounding out the mix, Kineviz’s GraphXR platform was recently used to visually display an NBC News database that included more than 200,000 tweets — tweets tied to “malicious activity” from Russia-linked accounts during the 2016 U.S. presidential election. And these organizations are just the beginning.
As more companies incorporate both AI and VR, the business case for using them for data visualizations becomes clear: VR for data visualization enables us all to better understand and leverage the vast amount of data we’ve long had at our fingertips. And, with Project New View and Adobe Sensei, that can improve the clarity surrounding data and results — and limit bias.
Project New View: An innovative option in data visualization
Project New View is an experimental project that unifies the data collected in Adobe Experience Cloud — think customer data from websites, apps, campaigns, and stores — and then applies AI for deep insights and predictive outcomes, and a VR interface that makes digesting data interactive, social, visual, and immersive.
For example, to find insights in Project New View, you can ask questions, using voice commands in your natural language. Adobe Sensei will interpret your query, analyze the data, and provide the answer in 3D, which makes it easier to understand and manipulate. “When we represent data visually with attributes like size, shape, and color,” says Dylan DePass, Adobe senior computer scientist, “we activate the visual cortex that’s the part of our brain which allows us to process complex information at higher speeds.”
This process also enables people to better interpret and act on the data. “Just having the chart doesn’t tell us why the data is the way it is,” Dylan adds, citing this as a major visualization limitation. “We want to show someone a chart that clearly favors some data point… and also tell them why the data is the way it is.” With Project New View, he says, “We eliminate another problem that can happen with data visualization — it could be very subjective.”
Improving data consumption and interpretation with self-service
Also critical to the data visualization drive is, again, the democratization of data — bringing everyone into the fold, even if they aren’t data scientists. Slemma dashboards, for example, can host multiple data sources in a single view. From here, virtually any stakeholder or decision-maker can quickly review and make data-driven decisions without lengthy deep dives.
What’s more, Slemma’s data visualization products are designed for self-service. In addition to a library of dashboards and visualization options, people can start from scratch, building and editing charts and dashboards with an intuitive Chart Designer — a designer that’s easy to utilize with or without design talent backing the process.
Slemma isn’t alone. Self-service business intelligence solutions are changing analytics from a specialized and incredibly time-consuming skill into something people can access, interpret, and act on.
Data Viz Project, for example, offers a collection of examples of data visualization techniques — dozens of chart templates from stacked bar charts, to pictorial fractions, to waterfall plots. People can search by family, input, function, and shape, choosing a visualization that syncs with their data, their story, and their audience. Google’s Data Studio offers a similar service, providing easy-to-use report templates based on data sources, including Google and YouTube Analytics and Google Ads.
“Data visualization is not just a problem for creative professionals and data scientists. Students, researchers, journalists, medical professionals, economists, and marketers all want to tell better stories with their data, and Adobe has a role to play,” Bernard says.
In the future, technologies like these will give everyone the creative superpowers to visually communicate their own data stories. This will also empower decision-makers and organizational stakeholders to successfully understand their landscape, find insights, and make better business decisions.