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How to Use Multiexperience for Effective Data Storytelling?

POSTED ON: May 12, 2020 TAG: Data Visualization

There is so much data all around you…

To put it simply, you can generate data from anywhere. But business decisions can’t be made just on numbers. What you need is a story, the process of creating that story, and the art of storytelling. According to one of the data-based articles by Harvard Business Review, numbers need to tell stories. Data storytelling demands you to convey a larger message in a way that lends valuable insights to make the one decision that turns your business into a profit center.

90% of business decision-makers prioritize gut feel over data when the two contradict, says The Economist, Intelligence Unit. This proves data is less important than the story and it is only through multiexperience that data visualization happens, and data tells its own story.

Actionable Decision Making with Multiexperience

What is Multiexperience?

Multiexperience can be defined as the various permutations of modalities, including touch, voice, and gesture, conversational apps at large, and devices that users interact with as they move through their digital journey across multiple touchpoints. In multiexperience application development, multiexperience development platforms (MXDPs) are used to develop fit-for-purpose apps based on touchpoint-specific modalities, while guaranteeing a consistent user experience across mobile, web, conversational, wearable, and immersive touchpoints. This implies MXDPs are not only used to develop web and mobile applications.

Multiexperience is known to be the future of app development. Apps in the legacy app modernization process consider multi-experience, which derives from multiple customer touchpoints like:

  • Wearables
  • Chatbots
  • In-dash apps
  • Social
  • Mixed Reality
  • IoT
  • Voice/VPA
  • Messaging
  • Websites
  • Mobile apps
  • Augmented Reality
  • Virtual Reality

Not only is it important to learn about and employ different sources for data and information centers but understand varied environments for prudent and agile decision-making. Environments can be physical, contextual, or experiential. You can be within the office working on a task, along with your team, on a communication and collaboration platform, while discussing profit margins last month. You can then pull reports from the dashboard, gather more information (if needed), and integrate the report with the analytics experience.

Multiexperience data storytelling is all about giving the right information at the right time to the right person through the right experience. Data-driven storytelling constitutes an underlying data, the intended (or unintended message), and supporting multi and immersive experiences. These experiences are, of course, more than just visualizations.

Remember the formula of Multiexperience Data Storytelling…

Multiexperience Data Storytelling = Visualization (Data Visualization tools like Chatbots, Dashboards) + Narrative (NLP) + Context + Experience

Remember the formula of Multiexperience Data Storytelling

Data visualization comes handy with dashboards. They enable data analysts at data visualization companies to gain insights into the key data facets faster. Through a single-view dashboard, they can use data and information for competitive analysis, identify items that need immediate attention, and see how the business is progressing. Streamlining resources and aptly purposing resources thus becomes easy.

Chatbots show systematic data records, trends, preferences, and metrics. There are several messaging apps within the chatbot that you can use to closely monitor your business. You have access to reports on how your profit margin changed and by what percentage, for instance, or how the user interactions have been over a period.

several messaging apps

Through natural language processing (NLP), you can question your virtual assistant and get answers to several business queries. This technology can turn audio speech or text into structured, encoded information, based on the correct ontology. The software looks at your data and writes a story from it, like a human data analyst. Adoption of artificial intelligence (AI) technologies, such as natural-language generation (NLG), aid enterprises fuel their digital transformation efforts and innovate on how they effectively engage with their customers.

Besides, context cannot be ignored by data scientists and analysts. It becomes relevant to eliminate any unnecessary information. If you don’t consider the surrounding factors of a specific data set, you get an incomplete picture, which shouldn’t be the case to focus on the issue at hand. Context allows you to take a wider view of the issue, gain valuable insights, and understand the reality better.

All these components together form the core of multi-experience data storytelling. But experience carries maximum significance here, which is where immersive analytics comes into the picture.

Immersive analytics is key to data-driven storytelling

According to Gartner, “Immersive Analytics is the use of immersive technologies (typically AR, VR, and MR) to support data exploration, decision making, and collaboration as part of a multiexperience”. Natural language generation (within the environment), augmented analytics (to present the data), and chatbots (to ask what is irrelevant within the data present), form the unique combination of multiexperience within immersive analytics.

Lying at the intersection of the visualization disciplines in hybrid reality, data science, and 3D interfaces and intersection, Immersive Analytics examines how new interaction and display technologies support decision making and analytical reasoning. This science enables you to derive data insights through powerful visualization, interaction, and display techniques.

Immersive analytics solution enables you to intuitively explore big data across several dimensions at once. You gain new insights faster with a single, clear view. For instance, you can view sales data through a spreadsheet, but when you view the same in a 3-D environment, which is more engaging and collaborative, data is clearer, and decisions can be taken faster. Besides, as you use immersive analytics to create immersive data visualizations, it becomes easy to share data with local and remote team members, leading to prudent data-driven decisions.

Immersion and engagement lie at the heart of immersive analytics

There are two kinds of immersion – technological and psychological. Technological immersion relates to virtual reality (VR) technologies that play a critical role in immersing the user in a virtual world. While psychological immersion, better known as engagement, refers to the cognitive state that the user experiences when absorbed by some task or activity. Psychological and technological immersion are relevant to immersion analytics and are also inter-connected.

As you understand that data, by itself, makes no sense, going through the process of data storytelling is crucial. Multiexperience enables data visualization, wherein data tells its own story, allowing you to make informed, actionable business decisions. Multiexperience data storytelling integrates visualization (data visualization software like dashboard, chatbots), narrative (NLP), context (environment), and experience (immersive analytics). Out of all these components, immersive analytics acts as the key to data-driven storytelling.

As the global immersive media market is expected to reach $179 billion by 2022, is your organization ready to explore immersive analytics?

POSTED ON: May 12, 2020 TAG: Data Visualization

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