Business Intelligence / Data / Analytics

In order to be successful in today’s omnichannel retail marketplace, merchants must collect information from numerous internal and external sources, then analyze that data. New solutions can help to optimize incoming data in order to deliver the business intelligence and analytics needed to move retail businesses successfully into the future. This section offers feature articles, special reports, industry viewpoints and the latest news to help retailers make sense out of the growing influx of information.

Get Ready, Retailers: Cannabis Sales Could Grow Like A Weed

Cannabis retailing is poised to be a major industry sector: a majority (56%) of U.S. consumers would try cannabis if it were legal, according to a survey by A.T. Kearney. With cannabis already available for medical use in 33 states and recreational use in 10, it’s not too early for retailers to position themselves for this market’s growth.

Data Monetization: Gaining, And Maintaining, A Competitive Edge In The Age Of Amazon And Era Of Consumer Trust

If retailers could improve omnichannel conversations with customers, why wouldn’t they? Because change is difficult, and trying to keep pace in an increasingly complex retail world can be challenging at best. Data monetization is a perfect example. Though an increasing number of change advocates across the retail industry recognize the advantages of monetizing data, for everything from adapting business models for e-Commerce to measuring brand sentiment, not all retailers have successfully kept pace with the changing landscape, and there is more to be learned by all. Those who do “get it” are helping their company leverage this revenue stream in new ways, to compete and differentiate themselves in the competitive retail ecosystem, and are doing so while keeping consumer trust and transparency top of mind. Here’s how.

Is Predictive AI The Next Step For Fashion Design And Curation?

Fashion’s one constant — change — forces everyone within the industry to stay ahead of trends in order to make intelligent business decisions. But designers, marketers and buyers may soon be getting help with some of the “grunt work” involved in analyzing data. A study revealed that AI-powered “classifiers” were more reliable at analyzing garments, and could classify footwear styles and footwear subcategories, more accurately and consistently than apparel professionals, according to EDITED. When compared to humans, the classifiers made, on average: 2.5 percentage points fewer errors when identifying garment types; 9.3 percentage points fewer errors when determining subcategories; and Approximately 6.5 percentage points fewer errors when classifying specific footwear styles.

What Retailers Learned In 2018: It’s All About Customer Data-Driven Strategy

At a recent industry event, I quipped that this is “the best of times and the worst of times” for retailers. Implicit in my comment — which was a paraphrase of the opening lines of A Tale of Two Cities, the Charles Dickens classic about the French Revolution — that the retail industry is undergoing a revolution of its own. Never mind the “retail apocalypse.” What retailers have begun to realize is that the demise of their businesses is not a foregone conclusion. This is a time for retailers to take action, not sit idly on the sidelines. In 2018, we saw more retailers take action by equipping themselves with the most important weapon for battle: customer strategy fueled by customer data science. Why is this happening? It could be that the ever-looming threat of Amazon, which has ventured boldly beyond e-Commerce and into physical spaces as well, with the steady spread of its 4-star stores throughout the U.S. It could also be the emergence of grocery discounters that are forcing retailers everywhere to rethink pricing and overall value propositions for customers. It could also be the example of retailers of all sizes to embrace the art and science of…

Extinction Event Or Golden Opportunity?

There is no question that we live in a data-fueled marketplace, and no better illustration of how the retail landscape has changed than the fact that Walmart employs more data scientists than NASA. They are not just interpreting the vast data signal from online behavior and loyalty app purchases, they are examining the entire business from the aisle to the parking lot — and everything in between. Welcome to the new reality. What’s happening at the largest retailers is merely a reflection of a sea change in the marketplace — one that will lead to extinction for retailers and brands that fail to adapt and change. This demanding new landscape was created by three major forces that retailers must embrace to serve: data convergence and connection, machine learning and personalization at scale.

Addressing The Unique Marketing Challenges Of SMB E-Commerce Merchants

According to the latest numbers from the National Retail Foundation, SMBs make up more than 98% of all retailers today. This feels inflated when you consider all the large merchants in our news feeds every day, but if you look beyond the headlines and consider the vast opportunities offered by the Internet, it isn’t really so shocking. Robust e-Commerce platforms, codeless site design, simple payment systems and a myriad of affordable tools are available today to help ambitious entrepreneurs set up shop and establish a formidable online retail presence quickly and at minimal cost. For most online shoppers, as long as the goods, price and customer experience are up to snuff, sheer size of the merchant has little impact on purchase decisions. This “level playing field” means retailers of every size are competing for the same customers, pitting smaller teams with less money and not enough time against resource-rich retail giants like Amazon and Walmart. This competitive landscape makes marketing even more critical for smaller retailers trying to engage consumers, who often default to omnipresent merchants by habit or convenience.

56% Of ‘Growth CMOs’ Prioritize Data Analysis Ahead Of Brand Building, Storytelling

The tools that are prized by the modern Chief Marketing Officer (CMO) continue to change as marketing becomes ever more technologically oriented. More than half (56%) of “growth CMOs” prioritize data and intelligence analysis as the top skill to help them evolve their growth agenda, according to a survey of 191 global CMOs from CMO Council and Deloitte. Additional mandatory skills include: Market insights and knowledge (50%); Holistic view of the customer journey (49%); Brand building and development (47%); and Storytelling in a digital world (44%). This emphasis on data and analytics has broadened many CMOs’ portfolio. “We are an extremely data-driven company,” said Monica Deretich, VP of Marketing and CRM of the JustFab business at TechStyle Fashion Group in a statement. “Yes, we collect data and feedback directly from our members so we can optimize her experience and keep an eye on the market around us. But as an organization, we are also committed to actively analyzing revenue performance data and looking for signals that identify and support efficiencies.”

Self-Service App Deepens Customer Connections At Fairway Market

Some retailers worry that adopting a self-checkout solution will deprive them of a key point of contact with their customers. Fairway Market, a New York City metro area chain of 15 supermarkets and four wine and spirit stores, wanted to be absolutely sure that wouldn’t happen when it deployed a self-checkout app, because the retailer prides itself on a family atmosphere and a close relationship with shoppers. The retailer is in the process of rolling out its first self-checkout app and will be seeking results that include:

How To Manage Holiday Worker Shortfalls With Analytics

The Black Friday countdown is on, and retailers are facing mounting pressure to get enough seasonal staff in time for the busiest shopping days of 2018. With U.S. consumer confidence reaching an 18-year high, the demand for seasonal workers in stores and distribution centers has become more intense. According to the Bureau of Labor Statistics, there were 835,000 retail job openings across the U.S. in July 2018, about 95,000 more than in July 2017, and 138,000 more than in July 2016. In September, Target announced plans to hire 120,000 seasonal workers for the upcoming holiday season, an increase of 20% from its 2017 hiring commitment.

How Retailers Can Make The Most Of “America’s Hottest Job”

Bloomberg recently declared the data scientist to be “America’s Hottest Job,” citing a national trend of employing those with a master’s degree in applied statistics or similar training by leading companies such as Airbnb and Uber. This hiring trend is driven by company leaders who realize the importance of capturing, understanding and learning from the data they produce to improve operations. While understanding data is indeed key to future success in the retail and CPG industries, there may be better ways for these companies to use their efforts and resources, versus bringing this expensive and scarce talent in-house.

Using Location Intelligence To Boost Retail Efforts

Whether it is McDonald’s determining which locations are ripe for kiosk ordering systems or a mom-and-pop hardware store considering opening a second location, location intelligence and mapping technologies are valuable tools for retail and commercial industries. As over 15,000 users gathered together at Esri’s annual user conference this July know, a company that wants to reach new customers or users, expand offerings or break into a new market must first understand its core customer, and this often involves tapping into demographic information that helps shape smart business decisions. Analysts are able to use location intelligence powered by a modern geographic information system (GIS) to find insight on market conditions. This includes knowing what kind of products a customer browses and buys as well as what he or she cares about, and why he or she might be loyal to a particular brand. It’s a form of modern-day psychology that draws heavily on digital data to find insight on customer groups while respecting individuals’ privacy.

Branch Messenger Unveils Real-Time Payroll Access For Hourly Employees

Branch Messenger has launched the Branch Pay feature, a technology directly connected to an employee’s schedule that is designed to give hourly workers instant access to earnings after each shift. The Branch technology will allow workers to tap into wages at a cadence dictated by the number of hours worked in a given pay period. Requiring no integration with a retailer’s existing payroll system, the employee can opt into Branch Pay after downloading the Branch application and connecting it to their bank account.

How Ashley Stewart Boosts Revenue With Advanced Data Aggregation

Apparel retailer Ashley Stewart, which caters to plus-size black women, has been learning the value of understanding its most loyal customers — some of whom visit the retailer’s stores as many as three times per week. With the help of a customer data platform that aggregates information about both digital and in-store shopping activity, the retailer has been able to leverage that loyalty into increased sales and revenues. Ashley Stewart has used the AgilOne customer data platform for three years to track customer activity in multiple channels. This allows the retailer to, for example, provide customers with easy access to their spending totals during its “Diva Dollars” promotional periods. “The consumers earn ‘Diva Dollars’ for a 45-day period, and then can spend them during a four-day period,” explained Julie Daly, VP E-Commerce at Ashley Stewart. Daly spoke during a panel discussion at the AgilOne Customer Data Platform Summit held earlier this month in New York City.
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