Design and distribute any content as a data product

In today’s digital age, the concept of data products has gained significant traction. A data product refers to a product that is built upon data and analytics to provide insights, drive decisions, or create value. This guide outlines the process of designing and distributing content as a data product, focusing on key principles, practical steps, best practices, and how they can be implemented with Storied Data.

 

1. What is a Data Product?

A data product is any tool or application that leverages data to generate insights, drive decision-making, or create value. Examples include:

– Dashboards and Reports

– Recommendation Engines

– Predictive Analytics Tools

– Data-Driven Content (e.g., infographics, interactive visualizations)

 

Of these 4 categories, the first and the last comprise the majority of the data products – over 90%, They can be easily implemented in Storied Data without any coding. The other two categories require additional tools and technologies. 

 

2. Designing a Data Product

 

Step 1: Identify the Objective

– Purpose: Determine the goal of your data product. Is it to inform, persuade, entertain, or solve a problem?

– Audience: Understand your target audience. What are their needs, preferences, and pain points?

 

This is the conceptual phase. It is no different than how physical products are designed. 

 

Step 2: Collect and Analyze Data

– Data Sources: Identify and gather data from reliable sources. Ensure data quality and relevance.

– Data Analysis: Use Storied Data, or other tools and techniques to derive insights from the data. This could involve descriptive analysis and/or data visualization.

 

Step 3: Create the Content

– Format: Decide on the format that best suits your audience and objective (e.g., report, dashboard, interactive visualization, interactive presentation, pixel-perfect document, or a combination of such documents).

– Tools: Utilize Storied Data to package your content as a data product which we also refer to as InfoApp (short for information application). There are other tools that you can use to create different types of data products, but Storied Data is a one-stop-shop for all types of data products.

– Design Principles: Apply design principles such as clarity, accuracy, and aesthetics to make the content engaging and understandable. Branding, layout and UI/UX are key to make your data product distinct and engaging. 

– Mobile Design: As data products command much higher value and attention, you may want to create pixel-perfect mobile view too. While the Storied Data product is one single file, the dual layout gives you precise control over what the user sees on all devices, ensuring consistent quality that cannot be achieved with the automatic responsive templates.. 

 

Step 4: Test and Iterate

– Feedback: Collect feedback from a sample of your target audience.

– Iteration: Make necessary adjustments based on feedback to improve the content.

 

3. Distributing the Data Product

This is the hardest choice as it involves costs and infrastructure. Do want to build full applications or do you want to distribute self-contained InfoApps? The former requires infrastructure and scalability planning for simultaneous users. The latter is scale free distribution, i.e., unlimited number of users can interact with the content and query the data in the InfoApp.

 

Step 1: Choose Distribution Channels

– Digital Platforms: Websites, social media, email newsletters, or data repositories.

– Traditional Media: Printed reports, presentations, or physical media.

Not all data products can be distributed across all digital channels. Only the InfoApps can be distributed across all as each InfoApp is a self-contained HTML file.

 

Step 2: Implement a Distribution Strategy

– Marketing: Utilize marketing strategies to reach your target audience. This could include SEO, social media marketing, content marketing, or partnerships.

– Accessibility: Ensure the data product is accessible to your audience. Consider factors like user interface, device compatibility, and language.

 

Step 3: Monitor and Evaluate

– Metrics: Track key performance indicators (KPIs) such as engagement, reach, and feedback.

– Continuous Improvement: Use the insights gained from monitoring to make ongoing improvements to your data product and distribution strategy.