5 Ways AR Can Change Brick-and-Mortar Retail

Thanks to the many tech innovations that retailers have integrated into their e-commerce offerings, consumers have become accustomed to a personalized shopping experience. Retailers have struggled to provide this same level of personalization and data insights in their brick-and-mortar stores.

Some of the most compelling tools used in physical stores today leverage artificial intelligence (AI) combined with computer vision applications such as mobile augmented reality (AR) to deliver highly immersive and engaging in-store experiences. These technologies are able to gather much needed in-store data that can be used to personalize the consumer shopping experience, improve product portfolios, and even make back-end systems more efficient.

Like many new technologies, the cost and complexity of AI and AR solutions has followed a cycle. The earliest solutions required significant resources to develop and maintain, and typically weren’t very scalable. Retailers now have access to previously unattainable AR immersive experiences that have moved beyond this early cycle. These solutions are fully productized, general purpose platforms, with reusable core features.

How can traditional brick-and-mortar retailers leverage AR to revolutionize their businesses?

Find a Complete Platform

Many AR technologies are masquerading as a full solution, but actually require teams of developers to create a custom application for one specific use case. We saw many examples of this over the last 10 years as retailers created fun games and seasonal promotions for consumers. However, this often doesn’t present a strong return on investment or a long-term solution for any specific business issue.

The good news is that we're starting to see fully productized AI platforms that include many core features for one license fee and offer a range of applications to address a variety of use cases. The apps may include front-end consumer experiences, employee training apps, and apps that increase efficiencies for business processes such as visual merchandising and product logistics. A complete platform will typically also include administrative tools that provide the controls and permissions to effectively manage applications across different stakeholders.

Prioritize Flexibility

If you have to pay to develop a highly customized application every time you need a new feature, it may get cost prohibitive to scale.

The answer? Consider an AR cloud solution that offers a SaaS business model and lets you "pay as you go" for more flexibility. This model also allows you to start with a pilot-size implementation so you can set goals before having to deploy at a larger scale.

Retailers may choose to start with a front end-consumer app (e.g., AR store navigation, product discovery, etc.) to provide more personalized shopper experiences, but should also pilot AR visual merchandising to reduce costs of testing and executing merchandising strategies. With a flexible business model, much more is possible at a more reasonable cost.

Don’t Forget About Scalability

To reap the real benefits of an AR solution, retailers should also consider platforms that are truly scalable. Software solutions that leverage existing hardware like mobile AR apps are good examples if they don’t require additional hardware (which can make  it  more costly to scale across multiple locations).

The key is to have access to administrative tools that allow for remote monitoring at each store as well as the ability to inject new content remotely for easy updates. With today’s AR cloud capabilities, solutions need to deliver data insights to immediately offer customized content either in-store as consumers navigate, or for employees as they’re helping customers.

With real-time data, retailers can immediately gain learnings that can be fed into their product portfolios and make business processes more efficient.

Execute With Data Integration

AI platforms that gather critical in-store data can  be a good way to integrate all data sets and map the full shopper journey across digital and physical channels. Retailers should be able to integrate their e-commerce data, loyalty program data and any other relevant data sets. To do so, the  AI platform must offer APIs and easy integration in order to avoid huge engineering costs. With the explosion of Internet of Things (IoT) devices, it's important to support the alphabet soup of IoT protocols to ensure the data captured by these agents can be easily integrated.

Make Your Physical Store Digital

AI combined with computer vision platforms has the ability to convert physical stores into intelligent digital environments. These new digital spaces offer many opportunities for new monetization models by creating new digital advertising space and an endless possibility of consumer promotions in-store that combine the digital and physical worlds. The detailed stream of data that's gathered from AI/AR applications, combined with these new digital spaces, give retailers that own and operate their physical spaces a new level of control over these new monetization opportunities. As AR evolves and the physical and digital continue to merge, retailers can reap the benefits of future revenue streams.

We're at the point in development that business-ready AI/AR platforms exist and can offer real value if implemented correctly. To garner the full benefits, retailers should seek fully productized software platforms that leverage existing hardware, offer flexible business models, and provide the ability to automatically scale to multiple locations. This will ensure that retailers gain data insights that can help inform everything from consumer experiences, employee training programs, store design and merchandising strategies, product logistics, store facilities management, and much more.

Emil Alon is the CEO and founder of Resonai, an AR company transforming physical spaces into intelligent digital environments.