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 The rise of thing commerce and what it means for software development

As connected devices continue their explosive growth, thing commerce is moving from niche to mainstream. So, what exactly is thing commerce? Thing commerce is where connected machines, such as smart home appliances and industrial equipment, will make buying decisions for people by either taking direction from customers or by following a set of rules, context and individual preferences. Thing Commerce will ultimately include buying things, reporting a problem, requesting services and negotiating a deal.

The rise of Thing Commerce will see more companies and consumers interacting with virtual assistants in smart appliances who can make purchases on their behalf. The days of remembering to buy milk and ensuring that fresh produce is not past its sell-by date will be eradicated. These tasks will all be handled by interconnected machines that will deliver a frictionless commerce experience for customers.

However, before this utopian reality can happen, businesses need to rethink how they develop and test the software and systems to support this new age of commerce. There are three core elements that thing commerce providers must embrace as they build and deliver software and applications:

Test the user experience

With Thing Commerce, there are multiple products and services composed of a variety of technologies from an array of vendors. As a result, development teams across the ecosystem need to reorientate from focusing on testing code compliance to understanding the actual user experience.

Embracing a user-centric approach to testing ensures you identify errors, bugs and performance issues before they have the chance to impact the user experience. This requires adopting an intelligent test automation platform.

Intelligent automation and bug hunting are mission-critical

The only way to truly test the Thing Commerce ecosystem from the user perspective is to utilize an intelligent automation engine. Intelligent AI-driven automation creates a model of user journeys and then automatically generates test cases that provide thorough coverage of the user experience, as well as system performance and functionality.

In addition, the AI algorithms hunt for errors in applications based on user journeys automatically generated from this bug-hunting model. This approach enables teams to quickly find, identify and address problems before release.

Continuous testing, continuous learning and predictive trends

Testing any digital experience is not a one-and-done exercise. It must be a continuous process so that you’re monitoring the digital experience over time. An AI algorithm will watch test results, learn and look for trends. The learning algorithms will enable predictive analytics. For example, it can identify if the increasing delay in a particular workflow is likely to result in the connected system failing to replace out-of-date produce before the family meal.

Final thoughts

Thing Commerce promises a world of possibilities that will free people from many mundane chores. However, for Thing Commerce to realize its potential, it’s essential that organizations change the way they develop software to ensure it delivers a consistent digital experience that delights customers. If not, Thing Commerce might erroneously deliver 20 bottles of milk to a smart fridge, delighting no one and incurring a lot of friction along the way.

All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.

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