Most of us hate the way business data is shared with us, and we have brands like Netflix, Google, and Amazon to thank for that! These websites and apps have mastered the art of presentation for digital users with intuitive layouts, action buttons and content prompts and suggestions. Why cannot the same design principles be applied to enterprise data?
We have always liked experience which is more contextual/ personal and does delight us. The same expectation is of a B2B customer as well. Though they have trained themselves on complicated spreadsheets, but they are also looking for a simple answer to their questions.
Hence as UX and Design practitioners it is important that we design data and help people make informed decesions
Businesses use data to understand their target users, discover new trends, and ensure they are on the right track. But in most cases, the data they need is shared in an unsexy, raw form like tabular rows or pivot tables and confusing pie charts. A lot of business-driven decisions are based on tons of data and let’s face it, no one has that much time to go through the data line by line. And more often than not business users will receive data not relevant to their role because the data has not been organized by personas. The issue is we often forget how hard it is to be a consumer of data.
Visualizing and sharing data in a manner that combines large sets of complex data that help users understand and apply the information they have. Data designing is the art of communicating and interpreting raw data into meaningful insights that are easily consumable, harnessing data’s potential as a powerful tool for organizational change
Why is data designing relevant today?
The world has become increasingly connected with smart devices, IoT sensors, and other technologies like AI gaining ground. The volume of data continues to burgeon, with IDC predicting a whopping 163 trillion gigabytes by 2025. The human brain cannot comprehend such large amounts of statistics without drawing some analogy or abstraction. Data visualization and designing can play an important part in creating those abstractions.
UX designers must understand data visualization best practices and determine the best way to present a data set visually, maintaining its appeal and accuracy. Especially when handling very large data sets, developing a cohesive format is vital to creating visualizations that are both useful and visually appealing. Clear visualizations make complex data easier to grasp, and therefore easier to take action on.
Cohesive data for Travel and Hospitality firms
RateGain has been helping the Travel and Hospitality industry understand and view complex data sets with ease. Our latest creation, Demand.ai, takes an innovative approach to solving the data conundrum for travel firms and hotels. It provides a data experience that is personalized, contextual, and relevant and allows users to apply data to daily activities and operations, as well as on-the-shop-floor concerns such as inventory management.
We’ve structured our data visualization process into key stages:
Understand the data
There’s no shortcut to this first step. You need to understand how the data fits together and what needs to be presented and prioritized.
Instead of showing the data, try can create contextual insights.
Graph, Chart, or Something Else?
Creating and maintaining a consistent visual approach that makes sense to the user while maintaining the integrity of the original data can be challenging. Visualizing data and presenting it in a user-friendly format must take into account measurements, date ranges, and time periods so you can develop a meaningful representation.
Tune it to match the user
We invest a lot of effort through consultation and testing before we get a data report right. Every report should speak to its intended audience almost intuitively, and be free from unnecessary statistics and jargon. We also present data in a way that best connects with the target audience in terms of color and other visual elements. We also take special care to make data easy to consume on any kind of mobile device, because the user could get the itch to read anywhere!
Align the design with each brand
Once the sorting of data is complete and we move into the creative aspect of presenting data, we make sure that the report matches the brand and domain
Takeaway: Your data designing cheat sheet
Here’s a quick peek into how we design our data to tell a story to help you get started:
Start with research, identify the users and their goals, and ask questions like:
- Who will use the insights – is it C level or researchers
- How will the hotel or revenue manager use this data?
- What are the kind of questions they want answers to every day?
- How is the data consumed? Is it printed, exported to excel or viewed on the screen? If exported, then why?
- What insights/ data sets are critical to make strategic decisions?
- To track progress, which are the key KPIs which have to be tracked over time?
Then sort out the essential data that can be meaningful, extract the various data points such as:
- What are the main triggers that the user looks into the data?
- What KPIs will help them make the decisions?
- What happens when there is a shift in the numbers?
- What data is nice to have but can be removed. Avoid cluttering the screen
The next step is to understand how to display the data.
- Begin by understanding the function of data visualization i.e, what the users need to see and then pick the type of visualization asset to be used.
- Identify how the users will navigate and interact with the insights/ data, and test the wireframes with users to make adjustments.
- Use visual hierarchy to define the aesthetic, fonts, and colors. Layout should be diened in way to increase scanability
- Pick the right type of visualization for the charts, paying special attention to the visual hierarchy
- Maintain consistency
To take advantage of all the data they have pouring in, many travel firms and hotels see the value of data visualizations in the efficient absorption of vital information, enabling decision-makers to understand complex industry shifts, identify new patterns in consumer behavior, and make data-driven decisions. We believe that data-driven storytelling is a more strategic way to inform the organisation on whats working and what needs attention
If you’d like to know more, just drop in a word at email@example.com.
We have very passionately created this new experience; hope you enjoy it too.
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