How Our Digital Economy Creates Data Product Opportunities
As the business world and billions of people continue their digital transformations, we as a creative community across industries also need transformational changes in digital business development and iteration.
A new category of focused, information-rich products known as data products break free from prior business intelligence models by integrating and packaging analytic information and outcomes into unique products and customer experiences.
Svetlana Sicular, research vice president at Gartner, Inc says “data is the source of creativity for data products; data sources are everywhere.” Sumeet Howe, director of data products and strategy at GoodData says, “a data product is an enterprise’s information assets wrapped in engaging analytics that drive significant value to its business network.”
A key notion that's driving the new economy is "unbundling." Chris Saad, head of product for the riding-sharing service Uber, defines the concept this way in an essay, published recently on Medium:
"The process of breaking apart rigid, man-made structures (i.e. "bundles") into individual, atomic parts. With this higher level of granularity, people are more empowered to more efficiently remix and mash-up their favorite things, on demand. This results in deeper personalization and individual freedom."
IT frees us to create personalized experiences in new ways
Information technology is the leading contributor to the unbundling trend, mainly because users no longer need the "centralized command and control provided by traditional, rigid bundles to be able to handle the inefficiencies and complexities of the world," Saad says.
New tools, such as the internet, the web and direct access via personal computers and even smartphones, give users "newfound insight and the power to solve for these complexities on our own in much more efficient and flexible ways," he says.
Data products and smart business applications creator GoodData has taken this unbundling concept to a new level by moving beyond the old business intelligence model that separated analytics tools from the business applications they were analyzing, focusing instead on embedded analytics and data products that monetize and commercialize the distribution of data and analytics.
GoodData: uniting data, analytics and business applications
As GoodData's Blaine Mathieu says in this DataTalk episode, "Data analysts and data scientists used tools that were largely separate from the business applications where the actual work gets done."
GoodData creates smart business applications that embed or wrap analytics around the data generated by a business application, such as an analytics dashboard. These applications create an all-in-one solution with data, analytics and the business application all in one.
Fitbit is a data product example that many of us use to help manage our fitness activity and wellness goals. The wrist device, personal and external data, and smartphone work together to provide relevant information that is personal and insightful and has the potential to change behaviors and lifestyles. Click on the Weekly Stats update sent to me in email that illustrates the point.
A business example is Allocadia, a cloud-based provider of budget-management software for marketing teams. This company partnered with GoodData on a collaborative, secure and easy-to-use customer dashboard.
B2B software provider Demandbase worked with GoodData to create data products for demand generation that deliver analytics to track advertising, web engagement and conversions.
How ‘unbundling’ benefits the agile
The current state of unbundling favors businesses that can turn on a dime to accommodate changing market conditions, respond swiftly to customer needs and experiences and empower their users to analyze and develop their own insights based on using the application instead of waiting for someone else to do it for them.
Speed and agility are essential aspects of GoodData's development process, which can take data product development from initial hypothesis to testing a minimal viable product (MVP) with beta users in six to eight weeks, as Sumeet Howe details in this DataTalk.
In his Medium essay, Saad poses a thought-provoking question to anyone who needs to compete and succeed in this rapidly changing world: "How can you get ahead of the curve and capitalize on the new patterns and tools that emerge?"
One way is to work with a data product developer whose platform gets you as quickly as possible to the point where you have a minimum viable product that you can begin testing, as Sumeet discussed above.
GoodData's three-part platform uses a distribution service that creates, delivers and manages the business application to thousands of users simultaneously, an analytics service built into the application, and an connected insight service that generates live data on what users are doing with the application to fuel new iterations.
“That gives us the feedback mechanism so that when we do want to do iterate on the product, we have real live data about what they're doing in order to do so,” says Jeff Morris, GoodData’s vice president of strategy and success, in this DataTalk. “When you want to build a data product, and speed is of the essence, our time to market is really unbeatable.
- Take a moment to watch the three DataTalk videos included in this post; each one is about 2 minutes long and delivers relevant, useful information.
- See related customer experience post with Drew Neisser.
- Share this post with colleagues and friends interested in digital transformation, customer experience and modern marketing best practices.
- Got a comment or question about using data products to manage your digital business and relationships? Put it in as comments below this post.
- Follow Blaine, Jeff, Sumeet, GoodData and Creatorbase on Twitter to stay up to date on new ideas and insights regarding data products and smart business applications and related creator competency topics.