S P O N S O R E D B YSOURCES: 1-ComputerWorld, “IN PICTURES: Remember this? The rise and fall of Sun Microsystems”; 2-CGT, “Retail and Consumer Goods Analytics Study 2019”; 3-RIS, “Albertsons Gambles on Artificial Intelligence and the Cloud to Transform Shopper Experiences”; 4-Juniper Research, “AI in Retail: Disruption, Analysis and Opportunities: 2018-2022”; 5-Google Cloud Blog, “Introducing the Google Cloud Advanced Solutions Lab in Tokyo: Helping Businesses do More with AI”; 6-ABI Research, “Robotics in E-commerce Fulfillment” ; 7-RIS, “16th Annual Store Experience Study 2019”; 8-RIS, “Retail Robotics: Productivity, Efficiency and Compliance”; 9-Hughes; 10-Towards Data Science, “Disruption in Retail — AI, Machine Learning & Big Data”.

Retailers have enormous data sets. This requires AI-driven cloud-based analytics engines and robust networks

to deliver actionable customer insights to the stores when and where they are needed.

Retailers say cloud infrastructure initiatives are helping to achieve internal data alignment.2

Albertsons has moved its digital workloads to the cloud with a vision to gain additional insight into its data and allow store managers to use predictive scenarios to anticipate and act on revenue-driving opportunities.3

AI doesn’t reside in the store, it lives in the cloud. And sharing AI capabilities across the enterprise to each and every store requires an always on, always available network to deliver superior application performance.

Fast Retailing (Uniqlo) has been applying AI to help with demand forecasting, and sharing the information with every employee, empowering them to be a decision-maker and advocate for the customer.5

These next-gen helpers aren’t possible without resilient and secure cloud connectivity. Robotic and voice platforms reside in the cloud, and their insights/responses must be transmitted to the store to power the customer experience.

BevMo!’s AI-powered robot BevBot! uses a cloud-based data/AI platform to help the specialty beverage retailer efficiently aggregate customer and store insight, and BevBot!’s platform can respond to and interact with customers in real time.9

Macy’s AI-powered shopping assistant platform Macy’s On Call has bilingual support for Spanish-speaking customers, underscoring the importance of personalized service.10

What retailers will spend on AI by 2022; approximately $2 billion was spent in 2018.4

Robots installed in over 50,000 warehouses by 2025, up from 4,000 robotic warehouses

in 2018.6

Retailers investing in

conversational commerce in 2019.7

Will roam the aisles in Stop & Shop and Giant/Martin’s stores to identify hazards and provide reporting that enables corrective action.8

REALITY

ADOPTION

ADOPTION

ADOPTIONRetailers’ In-Store Analytics Maturity2

5% Prescriptive

5% Predictive

30% Investigative

46% Basic

Top 3 Processes Most Powered by Retail Data2

1. Category management2. Forecasting/replenishment3. Planogram management

BILLION

32% 43%

$7.3

Artificial Intelligence (AI)

NEXT-GEN RETAIL EXPERIENCES AREN’T POSSIBLE WITHOUT THE CLOUD AND A POWERFUL NETWORK

SPONSORED CONTENT

Data Analytics

MILLION 4 33%

REALITY

ROBOTS500

“The network is the computer”

John Gage, technology visionary, philanthropist, founder of NetDay, and Chief Researcher

for Sun Microsystems1

Retailers say cloud infrastructure initiatives sit high on their organization’s priority list for the next 12 months .2

REALITY

Automation & Voice Commerce

MAKINGthe “NET” WORK for the STORE of the FUTURE

S P O N S O R E D B YJEFF BRADBURY Sr. Marketing Director at Hughes, works across markets to understand customer needs, tech adoption trends, and the direction of digital transformation to ensure Hughes customers are making the right connection for today and the future.

SPONSORED CONTENT Q&AQ How does an insufficient network affect

cloud applications and the in-store retail experience?

Moving to the cloud affords businesses a lot of benefits, but it comes with one large caveat: you have to have the necessary digital infrastructure to ensure cloud access and performance. In short – no network, no cloud. Fail-ure to match your network performance to your appli-cation portfolio and use patterns impacts connectivity and application performance. Network disruptions often result in failed transactions or sessions and a lack of access to critical cloud data. The right network will main-tain application performance, ensuring that apps deliver the expected user experience. Consider, for instance, a loyalty program transaction. If the app performs slowly, fails to recognize the customer or the session needs to restart, the customer experience suffers. Over the long term, network performance affects productivity, brand reputation and both consumer and employee loyalty.

Q What are some of the uses and advantages of natural language processing (NLP) and voice computing in stores?

I think we all have been surprised how quickly voice computing has taken off, with major offerings from Amazon, Google, Apple and others. NLP systems present some surprising benefits. For example, we are learning that when people are able to execute a task or transac-tion in the ‘moment of discovery’ they are more likely to complete that task successfully. For a retailer, this often converts into a completed sale.

We have seen some ingenious individual applications of voice computing and NLP in retail environments, which generally fall into a few broad categories. Common uses include wayfinding and directions to help customers locate a specific product or merchandise area and in-depth product information like cost, variety and availabil-ity. Retailers also use voice computing as a recommenda-

tion engine – customers may say what they like and ask for similar products. Our customer, BevMo!, runs a voice computing app on its shelves and via its in-store robot that provides recommendations. Finally, voice computing helps empower associates, enabling them to look up cus-tomer information, loyalty details, inventory or product information and shipping data to support mobile order-ing and payment from anywhere in the store.

Q What are some ways retailers are realizing the benefits of cloud-based artificial intelligence (AI) analytics engines and robust networks?

AI-driven analytics help draw out deeper customer insights so retailers can engage the customer with highly relevant offers at the right time, in the right place, via the most effective medium.

We are just at the leading edge of this transformation, but some early advocates are showing what’s possible. The new Nike flagship and Sephora stores in Manhattan are great examples. Both create multiple digital touch-points for customers and provide incentives for visitors to engage via apps while in the store. These brands customize the shopping experience, promoting specific items based on the individual’s purchase history or other data (like Sephora’s selfie-driven “color matching” sys-tem) and sharing loyalty offers, event announcements, and discounts or coupons. Customers can scan and tag items for future consideration, or, using sensor technol-ogy, have them sent automatically to the fitting room once a customer enters the dressing area. This new level of customer engagement is driving loyalty, increasing av-erage transaction size and encouraging repeat purchase, all of which contribute to revenue growth.

But like all cloud-based applications, this requires a ro-bust and reliable network. So if improving your customer experience and growing revenue via next-gen retail tools is on your to-do list, make sure item #1 is getting your digital infrastructure in order.

JEFF BRADBURY Senior Marketing Director, North America, HUGHES NETWORK SYSTEMS

NO NETWORK, NO NEXT-GEN RETAIL