Future of Brick and Mortar Begins With Responsive Retail: 7 Questions With JDA

We recently had the pleasure of sitting down with JDA Software GVP Product Strategy Todd McCourtie to discuss the future of brick-and-mortar stores. Successful retailing comes down to one thing: getting the right product into shoppers’ hands. That may sound simple, but success requires inventory accuracy, efficient sales associates and the flexibility to quickly adapt to shoppers’ needs in near-real time. That said, thanks to today’s emerging retail technology solutions I’m convinced that the retail industry’s future has never looked brighter! –Stacey Shulman

A picture of clothes on hangers.

Q: To start off, what are some of the challenges you see brick-and-mortar retailers facing that technology solutions can help solve?

A: Today’s retailers are looking for answers to the same questions that have always challenged the retail industry. How do I manage my inventory? How do I deliver a great customer experience? Moreover, how do I optimize my workforce for maximum results? Technology can help here, but what has really emerged is that as some retailers have tried to solve these challenges they’ve ended up cobbling together islands of technology. So it’s been very difficult for them to get that full 360-degree view of the store that leads to actionable results. I think that’s where we see opportunities emerging through technology solutions that can seamlessly support retailers with their immediate problem, which is how can they make sure they’ve got their inventories in the right place in the store.


Q: Can you talk a bit about how improving inventory management can solve several retail issues at once?

A: There’s a couple things. First, it’s not just a missed sale if the inventory is not in its place, but it affects the customer experience. Whether a retailer offers an inviting and easy-to-understand sales process is completely irrelevant if the product isn’t on the shelf. So, to me, that’s where it starts. If retailers have inventory visibility they can start to do localization because they’re seeing the real-time demand. A great example that focuses on localization is the question of why do sweaters arrive at Phoenix, Arizona, stores in May? It makes absolutely no sense. If near-real-time inventory management solutions are in place, then retailers have insights into the buying habits of individual stores and communities. They can then instantly replenish inventory, or not, based on the demands they’re getting from the store.


Q: How are JDA and Intel technology solutions uniquely positioned to address the localized inventory management solutions you mentioned?

A: I was hoping you’d ask! I’m excited to share that JDA and Intel have teamed up to offer retailers an intelligent technology solution to help manage and overcome age-old business challenges: the JDA Store Optimizer, supported by the Intel Responsive Retail Sensor. It tracks inventory accurately, so you always know where items are located and how many are in stock while also automatically updating store associates’ tasks. Having near-real-time inventory data makes it easy to run lean, save time and money and replenish products as needed with little risk of shortages, overstocking or preventable returns. The JDA Store Optimizer then uses this precise inventory data to automatically identify, prioritize and assign tasks that sales associates need to carry out to optimize operational efficiency, while freeing the store manager to spend more time making decisions that will improve store performance and increase revenue.

To put it simply, we know the future of retail because we’re building it with Intel. So we see the problems of today and both companies see what we need to do to solve them, but with an eye to the future.


Q: Data security is a hot topic these days. How is that being addressed with this retail technology solution?

A: When we deal with privacy, we always talked about opt-in [being] enabled right into the platform. From an application provider perspective, the core platform is built from the ground up with security in mind. We also want to make sure that data can be isolated per application, so that if a retailer has their specific set of data they’re bringing, it’s only for them and they know they can trust that verified data. So, that kind of end-to-end security is built in from the ground up. Then there’s end-to-end data encryption, as well, to help guarantee the security and privacy of the data.


Q: What about privacy? How is that being addressed with this solution?

A: From my perspective, privacy is very personal. Some people are completely OK with giving that away; other people are very guarded about it. Only 43 percent of shoppers say they are comfortable giving up personal data to a retailer — even if it is to improve their shopping experience. This is a relevant and prescient issue to retailers today. And so, when we’ve tried to approach it, we’ve said there needs to be a way to opt in; a loyalty program is a great way to do that, for example.


Q: Can you give us an example of some of the early results you’re seeing from a retailer that has piloted the JDA Store Optimizer?

A: I certainly can. We’re working with a specialty retailer in North America and are excited to see that we’re getting enormous response. I just received an email stating how pleased the associates are in that environment because they’re able to spend more time focusing on relevant customer engagement and that’s great news for us to hear. We know that this is so important from data that we have about customer behavior. Most consumers say that they want associates who are more knowledgeable and will leave a store empty-handed if they do not get the right person with knowledge to help them with purchasing products. A recent study shows that two in three shoppers who tried to find information within a store say they did not find all the information they needed; when they were unable to find the complete information, 43 percent of customers left the store frustrated; 22 percent said they were less likely to buy from that retailer and 41 percent more likely to shop elsewhere. It is so important to have engaged, knowledgeable and able sales associates and the JDA Store Optimizer enables sales associates to get back to the business of being available to customers rather than just running around the store in search of inventory.


Q: How do you see artificial intelligence coming to bear and being a part of this platform in the future?

A: Artificial intelligence can help us precisely because we don’t live in a static world. If store shelves were always perfectly stocked and arranged then we probably wouldn’t have much of a need for it. But we live in reality. People buy things so the stock is changing constantly. Things are shuffled as people look at them. Customer behavior enables an opportunity to use pattern matching and artificial intelligence to really go look at those environments and say, hey, these events have happened where there’s a $ 5 item covering a $ 100 item that was really supposed to be on display; let’s have an associate go fix that to give me insight into the ROI of an endcap. Was it actually stocked properly? Did people interact with it? I think we can learn over time, make it much better and make that store truly responsive. In a way, the store itself is learning. The platform helps the store learn so it can keep up in near-real time with the changes that are happening in consumer behavior and the retail environment. Moreover, there’s no lag time. You’re not being caught unaware.

Visit intel.com/retail to learn more about how Intel technology is shaping the future of responsive retail. To stay informed about Intel IoT developments, subscribe to our RSS feed for email notifications of blog updates, or visit intel.com/IoTLinkedInFacebook and Twitter.

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Facial Recognition and AI Helping Customize Retail Experiences

When shopping online, today’s customers want all the personalization of an in-store experience. And when they walk into a brick-and-mortar store, they want continuity from this online experience, based on the choices they made across all other touchpoints.

Savvy retailers have met these expectations by pulling in incredible amounts of data for highly personalized cross-channel offerings. Online, they’re performing advanced real-time analytics on customer behavior to deliver digital experiences tailored around customers’ interests and needs. In store, they’re using cutting-edge software to understand who’s looking at displays, and to engage, entice, interact and motivate action.

This level of personalization uses artificial intelligence (AI) for facial analytics. It is an essential tool for any retailer who aims to keep up with the changing expectations of digital consumers and find more effective ways to generate revenue. Here’s how the power of AI and facial recognition enable a deeper understanding of customers and provide more personalized experiences.

Two humans look at a tablet.

What visual experiences do

The goal of in-store personalization is to deliver experiences that are as individually tailored as those online. While this might sound like a tall order, the truth is that the latest digital displays can collect analytics and deliver content just as precise as those of any web platform.

Only 13 percent of in-store eye fixations are on signage, and the average shopper looks at signage for only three-tenths of a second. Less than half of those people can remember what they saw on the signs. In short, it’s not what you look at, but what you see, that’s really crucial — and a very effective way to ensure that shoppers see a display is to provide them with targeted content.

It all starts with deep insights about consumers. These can come from digital touchpoints, from in-store analytics or, ideally, from a combination of data from all channels. Taken together this data can reveal trends and deeper customer insights — for example, 50 percent more shoppers engage with alcohol brands on Tuesdays rather than on Thursdays, and they’re two times more likely to browse frozen foods on a Wednesday afternoon. This leads to a better understanding of the customer, greater data personalization, insight and a better overall customer experience.

When you connect online and offline data to arrive at these kinds of insights, you’ll deliver more personalized experiences and establish loyalty for your brand. The next step is to leverage AI to reach the shopper.

AI in retail experience

The latest data shows that interactive digital signage gets more than twice the engagement rate of top social networks. It also gets a dwell time that’s 24 percent higher than Google benchmark data for online rich media. But not all interactive signage gets these impressive results. To really activate the power of this channel, you’ve got to use it to learn about customers — then deliver personalized, customized content that connects with them at the right time.

Many retailers are scrambling to increase personalized experiences and are calling on companies with proven results that offer groundbreaking retail technology, specializing in driving brand and consumer engagement. One of the most powerful tools for in-store personalization is facial facial detection . This technology can play visually interesting content for individual customers, based on past purchases. But that’s only the beginning.

Digital and interactive displays go far beyond facial detection — they can recognize returning customers’ emotions, demographic information, shopping time, location and more. These cognitive analytics enable the display to engage in a real-time feedback loop with the customer, refining its messaging in response to the shopper’s reactions, in order to reach the right consumers with even more precise messaging in the future.

The results speak for themselves. Using a combination of facial recognition, emotion detection and advertising refinement raised the average dwell time per display to an almost-unheard-of 32 seconds. Impressions and engagements also went through the roof, as more shoppers interacted with personalized displays and were far more likely to purchase following those interactions.

Some brands are beginning to go a step even further by adding object detection to their personalization strategy. This can yield even better results, and serve targeted behavior-driven messages to individual customers. All touchpoints in all stores can deliver a single, consistent experience that spans every digital touchpoint and brick-and-mortar location.

This is the level of consistency and personalization demanded by today’s shoppers. Aside from the increase in engagement and revenue, the real value is the ability to build emotional connections with your customers. This personalization is an absolute necessity in the future of retail to keep customers coming back, time and time again.

Visit intel.com/retail to learn more about how Intel technology is shaping the future of responsive retail. To stay informed about Intel IoT developments, subscribe to our RSS feed for email notifications of blog updates, or visit intel.com/IoTLinkedInFacebook and Twitter.

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The Path to the Enlightened City: Smart Streetlamps

For a glimpse of the future, look at the cities of today.

The vast majority of economic activity, innovation, and energy consumption already happens in urban areas, leading 77 million people to relocate from rural to urban areas every year. The number of megacities (containing more than 10 million people) has doubled over the past two decades, with the developing world leading the way.

This represents an incredible opportunity: Cities are more productive, offering jobs, improved quality of life, and escape from poverty for millions around the globe. But the UN warns that urban growth needs to be properly planned to avoid serious issues like pollution, traffic and crime. Given the sheer scale of today’s cities, managing them is no easy task.

An urban scene.

Luckily for mayors around the world, we are seeing Internet of Things (IoT) technology bring the urban landscape into the digital age. The proliferation of connected devices lays the foundation for the “smart city,” which features systematic data collection in real time. This benefits residents and administrators alike, offering instant insights and actionable recommendations that improve the smooth functioning of the city.

While this technology is more critical than ever, rolling out IoT infrastructure can provide a challenge. How can you place new sensors across an entire metropolis?

The answer lies in something unassuming and ubiquitous: the streetlight.

Intel has partnered with General Electric and AT&T to create CityIQ intelligent nodes, which fit onto any streetlight. These nodes can be embedded with a range of cameras, microphones, and sensors, offering the perfect platform for smart city features such as parking assistance, gunshot detection, weather monitoring, emergency response, and much more.

Smart streetlight sensors.

This February, San Diego announced it would upgrade 3,200 streetlights with the new technology, making it the largest known urban sensor program in the world. The city expects more than $ 2.4 million in savings per year in energy costs, which offsets the cost of installation through a 13-year lease purchase agreement. This experience is not unique—connected lighting systems pay for themselves twice as fast as regular lights.

More important, San Diego is establishing a diversified technology hub on every block. City law enforcement can use intelligent nodes to respond faster to emergencies, collect situational intelligence, and detect gunshots. Sensors have the capacity to collect traffic information, reducing congestion and offering data for smarter travel recommendations. Smart streetlights can monitor parking availability, help drivers find a spot, increase city parking revenues, and decrease the environmental and traffic cost of idling cars.

They can also collect air pollution levels on the hyperlocal level, using speakers or push notifications to send alerts to those nearby. Streetlights can be repurposed as Wi-Fi stations and include digital signage, offering new income streams for cities. This is just the beginning: CityIQ’s open architecture means that the possibilities are endless as smart city innovation continues.

With an eye on energy efficiency and cutting costs, many cities are already upgrading their streetlights. Cities can save as much as 80 percent of their lighting costs by switching to smart LED lights, which can dim during off-peak hours to conserve energy. Adding sensors to new lights is the next logical step.

Right now, only 12 percent of the world’s 300 million streetlights have LED lights, and only 2 percent are internet connected. But that’s changing quickly as LED prices have fallen and environmentally friendly regulations kick in. The European Union—the world’s largest economy—now requires its member states to phase out incandescent lighting.

Lighting has a long history of bringing social change. Beginning in the 16th century, streetlights were introduced in an effort to bring law and order to cities. In the 19th century, gaslights changed the nature of work by illuminating entire households, which allowed family members to labor individually rather than in groups. Today we are on the verge of yet another revolution, with streetlights serving as the backbone of the smart city.

For more on Intel IoT developments, subscribe to our RSS feed for email notifications of blog updates, or visit intel.com/IoTLinkedInFacebook, and Twitter.

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Reinvent the In-store Experience by Unlocking the Power of Data-driven Insights

Shopper behavior and spending habits are changing dramatically, causing the retail industry to face a period of significant disruption. As shoppers are empowered by mobile devices, social media and the Internet, they expect retail experiences that combine choice, convenience, superior service, and a clear understanding of their individual preferences. This shift has been heavily influenced by online giant Amazon and other similar companies, which use data-driven insights about product preferences and spending patterns to provide shoppers with enhanced experiences by giving them what they want, when they want it.

This intimate customer knowledge and the effective use of data and technology are paying big dividends for online merchants. Roughly eight in 10 Americans (79 percent) are now online shoppers, up from just 22 percent in June 2000, and 82 percent say they consult online ratings and reviews when buying something for the first time. While online shopping frequently offers lower prices, greater convenience, and many other benefits that brick-and-mortar retailers are struggling to match, 64 percent of Americans say that, all things being equal, they prefer buying from physical stores to shopping online.

With RFID technology, brick-and-mortar retailers can use this preference to their advantage by bringing the best of both the physical and online worlds to their customers, while answering all those age-old questions: How do I keep good track of my inventory? How can I provide a better customer experience to my customers? How do I optimize my workforce to get maximum effect on my bottom line?

Many retailers have reaped the benefits of RFID by taking that critical first step to implement RFID solutions in their stores. When it comes to choosing the right type of RFID investment—fixed/overhead or handheld—retailers should be careful of implementing a handheld solution that’s too basic and does not provide them with the complete picture. Fixed RFID solutions deliver maximum value to the retailer by not just providing ROI stemming from more accurate inventory levels, but through automating many of the store operations to enable associates to focus more attention on the brand, the product, and—most importantly—the customer.

Overhead RFID unlocks a wealth of data in the store, providing information and insight on customer preferences and interaction with product previously relegated to the online shopping space alone. While we are glad that retailers are exploring RFID in their stores, years of research and development in the smart retail space tells us only investing in the right technology will deliver the results and the value in today’s shopping environment. So what is the right option—overhead or handheld?

A person folds a sweater.
Overhead vs. handheld RFID

Overhead RFID has many advantages over handhelds, but in actuality, retailers don’t have to choose one over the other. There is a way to have the best of both worlds, and the most successful deployments will find the right mixture of both solutions. While many retailers may opt for a handheld first with some fixed sensors over portals or a point-of-sale approach due to what can sometimes be perceived as a lower cost barrier and more simplicity (a misconception addressed in a previous blog on RFID technology blog), this can result in a failed attempt to reap upfront benefits while minimizing the investment needed to implement a full overhead solution.

What this strategy also doesn’t address is the fact that consumer shopping patterns and behaviors are always changing, and the way products are placed throughout the store should reflect this reality. A portal might help to determine when an item moves from back stock to the sales floor or when it leaves the store, but where the item is in between those events will remain a mystery.

The winning approach: Augmenting a fixed solution with handhelds

Static point-of-sale stations have existed in retail since the first store ever opened, but—as Intel is deeply familiar with this—brick-and-mortar retailers find themselves at a crossroads with how they deal with online competition. Retailers continue to invest in mobile POS solutions, enabling store associates to assist customers anywhere in the store and reduce the friction of checkout. Many also aim to enable a frictionless self-checkout in the future. In this scenario, when and where the customer transaction takes place in the store is very much to be determined.

Even in a fixed RFID deployment that provides retailers with the real-time data they need, a handheld sensor may sometimes be necessary to search for exceptions in the store. But leading with a handheld solution supplemented with transition-based (portal) sensors will fall short of unlocking the full potential of RFID benefits since it will fail to provide retailers with the store coverage and real-time data ingestion they truly need. Augmenting a fixed solution with handhelds is the true winning approach: It will not only provide retailers with proper store coverage, it’ll give them real-time data ingestion too, hence providing e-commerce quality insights.

Intel Responsive Retail Sensor infographic

Intel RRS

A product like the Intel Responsive Retail Sensor (Intel RRS) could provide a viable long-term solution to retailers, as it delivers accurate, always-on, real-time data that gives brick-and-mortar retailers the best of both worlds—combining the convenience, speed, and selection of online shopping with the person-to-person service and opportunities for customers to touch and try on products that only brick-and-mortar stores provide. Using innovative technology solutions and data-driven insights to bring the advantages of online shopping into their physical locations enables retailers to transform their businesses and reinvent the in-store customer experience.

Visit intel.com/retail to learn more about how Intel technology is shaping the future of responsive retail. To stay informed about Intel IoT developments, subscribe to our RSS feed for email notifications of blog updates, or visit intel.com/IoTLinkedInFacebook and Twitter.

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Intel’s Vision for the Future of Smart Video

What is sight without the power to understand what’s being seen? As the Internet of Things  (loT) revolution continues, smart video technology keeps creating huge amounts of data. But even as these video technologies become more prevalent in cities, industrial facilities, retail stores, and even private homes, it’s still a major challenge to store and analyze that data. Intel answers this challenge with a scalable end-to-end (E2E) solution for secure collection, storage, and analysis of vast volumes of loT video data.

Smarter Industries and Smart Home

Can a better world exist without the proper resources to manage the exponential increase in 1/0?

Smart cameras are critical for making cities safer and more secure. Depending on the size of the city, this metadata can stack up into terabytes— and it all has to be analyzed in order to derive useful results. Within smart cities, smart transportation systems are generating tremendous amounts of data about vehicles, passengers and roads—often creating a full terabyte that needs to be securely collected, processed and stored every single day.

In a wide range of manufacturing sectors, virtualization technology is helping raise efficiency while  lowering the costs of doing business. Smart factories that use this technology can generate a terabyte of data every day. In smart retail,  video generated by digital security and surveillance systems helps keep stores secure and efficient—but  with  more than  75 million video surveillance cameras being sold to retailers in 2018, demand enormous storage capacity.

The loT transformation doesn’t end at the commercial space. The smart home revolution is already well underway. By 2020, the global market for smart home technology is projected to reach 100 billion, and most households will have more than 50 connected devices in the home. As smart homes become commonplace, the amount of data generated by smart devices will grow  exponentially—as will the storage and analysis systems required to deal with that data.


E2E Solutions

Fragmentation is a developer’s nightmare. That’s why Intel believes the only solution, is a holistic E2E approach.

As more industries adopt IP cameras, Intel’s integrated; hardware accelerators deliver the performance needed to process high-definition media in real time. These solutions ensure secure transmission and accurate analysis of data, with the help of a unique architecture in which connectivity, analytics and performance can all expand as needed.

Intel’s “develop first, port fast” toolset powers Intel’s Computer Vision software development kit (SDK). This SDK enables easy video processing, whether for in-store footage or handling security and surveillance applications. All Intel Xeon processors come ready to work with an entire portfolio of specialized libraries, saving developers significant time.

In the loT, security is at a premium. As many security experts know, hackers have already penetrated the ordinary layers of software security, and are now focusing their attacks on connected devices like IP cameras and network video recorders (NVRs). Intel’s entire architecture is designed from the ground up to defend against common forms of attack.


A Future with Intel

Intel technologies are making video data more accessible, analyzable, manageable and actionable for an entire ecosystem of developers. Each one of Intel’s video security and surveillance solutions delivers the performance required to process bandwidth-intensive video at the fastest rates possible.

Intel RealSense cameras are the “eyes” of this intelligent visual system. From handheld devices to snap-on PC cameras and beyond, RealSense makes 3D scanning and interior mapping simple, with imaging-and-feature tracking that make it easy to capture 3D models of real-world objects and rooms.

Movidius MyriadX vision processors (VPUs) are the “visual cortex” of the system, delivering top shelf performance with a very low power thermal footprint. In fact, MyriadX processors offer the best performance per watt of power of any processor under 1.5 watts—a full five times the capacity of Myriad 2 processors. These efficiencies allow more cameras to be installed, increasing in the amount of data captured, stored, and analyzed.

Finally, Intel CPUs act as the system’s “brain,” delivering best-in-class processing power packed into an ultra-thin and lightweight chip. Intel Xeon processors, for example, help deliver real-time analytics, processing for mission-critical tasks and big data insights.

Intel’s diverse portfolio of cameras, vision processors and CPUs provide the tools to make massive amounts of data easy to access, manage, analyze and transform into actionable insights.

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