Tag Archives: Retail
By Gary Sankary – Head of Industry Marketing, Retail
Every year, more than 30,000 retail analysts, executives, and professionals meet for three days in New York City’s Javitz Center for the National Retail Federation’s annual Big Show. As a retail veteran, believe me when I say there’s nothing in our industry quite like it. It is the largest and most important trade show of the year for retail and retail technology. Retail professionals from every aspect of the industry come to the show to connect, meet with technology partners, and see what’s new in the industry.
The Esri Retail team is excited to showcase many of the ways ArcGIS can help retailers bring precision to their enterprise and extend their capabilities in merchandising, marketing, operations and business intelligence. With the release of ArcGIS 10.5 and Insights for ArcGIS, it’s never been easier for retailers to understand why things happen where they do.
ArcGIS brings precision to retail by enabling retailers to leverage the power of geography in their decision making and execution. Every retail transaction happens in a location for a reason. By connecting data, events, and transactions, retailers can discover the insights they need to find target customers, drive sales, reduce expenses, and engage with their customers. As retailers continue to develop and execute their strategies to support unified commerce, a location data management strategy enabled by ArcGIS is critical.
Space planning is a key component of the merchandising process. At Esri, we consider space planning in merchandising as those capabilities that support the allocation of space and placement of products in the retailer’s stores.
Best-in-class retailers tightly integrate space planning with their assortment planning and fulfillment capabilities. The amount of space given to a category or product drives the shelf stock by store, which is used, along with demand forecasts and available inventory, to calculate need for fulfillment and ordering.
There are two key capabilities that space planning teams in merchandising support: macro space and micro space.
Macro Space Planning
Retailers typically will create macro space plans that describe the layout of their stores at the category level. This process is hierarchical in nature; store planners and merchants tend to start at the total store and divide up available store space into by merchandise divisions or departments. They will then further break down their space into categories.
For example, in a big box retailer, a department might be Pet Care. Categories within pet care might be dog food, cat food, cat litter, small animal and pet beds, leashes and accessories. Store planning teams will determine the total amount of store footage to allocate to Pets, and to each category. Considerations will be store performance by category, aisle and fixture configuration and the relationship between highly trafficked and less trafficked store locations.
Micro Space Planning
Once the department and category space allocations have been made the micro-space team takes over. Also called planogramming, micro space planning is the process of creating fixture-specific schematics that store merchandisers use for seasonal and new product sets in their stores. Planograms describe the number of facings a given product might have on a shelf, how many items to put on the shelf, what signage is needed, what shelf labels are needed, and where to place them.
How Esri Can Support Space Planning
One of the key strategies that brick-and-mortar retailers are trying to solve today is localization, how to make their individual stores more relevant to the communities and neighborhoods they serve. To accomplish this, retailers need to intersect attributes and data about customers, products and location in order to create a full understanding of who is shopping in their stores and, just as importantly, who is not. Being able to effectively leverage this data enables retailers to more successfully engage and retain their existing customers while creating assortments or marketing messages to reach new customers and grow market share by leveraging their existing investments in store square footage.
By Jessica Wyland
To identify customers, many product manufacturers are turning to location-based data. A recent Harvard Business Review article reported the use of “increasingly granular data, from detailed demographics and psychographics” including age, gender, address, income, and lifestyle.
“You’d be surprised how often a product manufacturer discovers that unexpected consumer groups are accounting for more purchases,” says James Hibbard, an expert in location intelligence and GIS manager for MarketSource.
MarketSource, a proven alternative to sales outsourcing, provides comprehensive solutions for the entire sales ecosystem. Hibbard uses data and maps to help MarketSource’s Fortune 500 clients determine who is actually buying at the retail level. One of the tools Hibbard relies on is ArcGIS Maps for Office.Continue reading
Location analytics helps retailers breathe new life into old strategies.
Online shopping is well understood. We don’t only know how many people visit an online retail site. We also know that changing the size of a picture by a few pixels will generate more sales. We can even see if online shopping carts have been abandoned, what items people have viewed, and how long visitors have stayed on a page to calculate their interest in buying a product.
But when it comes to knowing how many people shop at a physical store, traditionally we scratch our heads. We’ve been trying to figure out those details for more than a hundred years. And don’t get me started on “dark shoppers”—customers that visit a store but don’t purchase. Unlike online shoppers, “dark shoppers” don’t leave an activity trail. There’s been a lot of talk about how in-store beacons will change this, but the jury’s out on how shoppers will respond. Continue reading
While their behaviors confound retailers and marketers, we’re starting to gain a better understanding of what makes this cohort click.
Do you know any Millennials? You might even be a Millennial yourself.
Milliennials are contradictions, alternately described as lazy, entitled, idealistic, close to family, and racially diverse. Pew Research notes that Millennials are not bound to organized politics or religion, support a more activist government, are linked by social media, carry debt, and are optimistic about the future.
Demographers disagree about the exact time frame this huge group encompasses. Some say that Millennials were born between 1982 and sometime in the early 2000s. Pew Research says that Millennials range in age from 18 to 33 years. Continue reading
Finding a balance between consumers and companies when sharing geolocation information in the age of big data analytics.
Recently we returned from a retail conference where we highlighted to attendees the differences in perception and attitudes they have toward location data, depending on whether they are using it in their personal or professional lives.
This was the type of conference where those big-box and household-name retailers you see every day send their people in charge. They meet and discuss different ways to sort out the massive amounts of data they capture from today’s digital world. Their main purpose? Turn that data into hard results. Continue reading
Technology and the great recession have changed retailing forever. Gone is “Clonetown USA” with its repetitive retail landscape replaced and redesigned to engage the customer on their own terms. Today, it’s all about doing business locally, bringing your store to the customer rather than thinking the customer is inclined to seek you and your products out at your store. AppFire caused a major media buzz when they announced in January 2011 that the average Smartphone user spends just over three quarters of their 84 minutes a day using maps, social networking, and other activities immersed in the Web. The least important thing we now do with our phones is talk!
Smartphones have empowered the tech-savvy consumer and as a result stores are porous. According to the Mobile Movement Study, 95 percent of smartphone users have looked for local information and 70 percent use smartphones while shopping in-store to price compare or find the best place to purchase a product. For the retailer the most important statistic is that about the same number visit the business they search and 53 percent actually purchase.
The importance of knowing your neighbor
Dorothy, this isn’t Kansas anymore. It could be Anytown, USA. On my last trip to Kansas, it wasn’t the wheat fields or flatness that amazed me but the repetitive retail landscape. It seemed that every town was a clone of the one I had just left—the same restaurant chains, grocers, drugstores, and general merchants. Was it an unholy alliance? Had real estate developers, government, and retailers reached perfect agreement on what every town needed and limited the choice to a small menu of options? However, the more I looked, the more I found exceptions. The harder I tried to quantify the way towns were similar to each other, the more I noticed the differences and came away knowing that local flavors dominate. Continue reading