By Alex Romanov, CEO, iSIGN Media

Proximity marketing is changing the way retailers reach out to customers. Often linked with digital signage that is equipped with Bluetooth® and WiFi message transmission capabilities, proximity marketing reaches customers when they’re most likely to make a purchase – at the point of sale (POS).  Cash registers generate the ultimate POS data: a record of the actual transaction. So what would happen if you combined the two, merging proximity marketing data with cash register receipts?

First, it’s important to understand what each component brings to the table. An effective proximity marketing strategy transmits offers to customers who come within range of a digital sign equipped with an antenna. A good proximity marketing solution enables merchants to send rich media messages in many forms, including something as simple as an electronic coupon or a more complex transmission, such as a game. 

Customers have the option to accept or decline the message. And since it uses Bluetooth and WiFi technologies, customer privacy is protected; instead of personal information like names and phone numbers, only device signatures are collected. Despite that protection, proximity marketing generates incredibly rich insights on customer behavior, collecting information such as the rate of offer acceptance, customer duration within the store, foot traffic patterns and much more. 

In a sense, proximity marketing functions in the real world much as online cookie tracking functions in the virtual environment, providing merchants with real-time information on where customers go in the retail location, what offers interest them, what areas of the store they visit and for how long. However, one missing piece of the puzzle for brick-and-mortar retailers has, until now, been POS data. 

By merging POS information with proximity marketing data, merchants can get the ultimate customer profile. For example, a grocer with a regular customer who frequently purchases steaks, baking potatoes and red wine would be able to craft a 24-carat offer tailor-made especially for that customer, like a discount on a better vintage Cabernet, or an alert to a sale on artisan sour cream or upscale steak sauce. 

Cash registers have been around for 150 years, but POS technology has advanced rapidly over the past 10 years, and its future evolution is clear: mobile wallets are gaining traction with consumers. Soon, the traditional cash register will be obsolete, with transactions completed electronically between in-store POS technology and mobile phones. This will make merging POS data and proximity marketing information even more seamless – and inevitable. 

In the ecommerce world, merchants have used the insights they gain into consumer behavior online and purchasing data to drive double-digit sales improvements. For example, Walmart used data insights to generate a 10% to 15% increase in completed online sales to drive $1 billion in incremental revenue. 

A similar opportunity exists in the brick-and-mortar environment. The first step is to deploy the right proximity marketing solution to generate rich data on in-store consumer behavior. The next step is to marry that data with POS information. Merchants who combine this data will build the ultimate customer profile – and gain an incredible competitive edge. 

About the Author

Alex Romanov is CEO of iSIGN Media, a leading North American multiplatform advertising solutions company that utilizes Bluetooth, Mobile, Wi-Fi and Location-Aware technologies to deliver rich media, permission-based messages to engage consumers more deeply and cost-effectively. Find out more at http://isignmedia.com

by Jim Malone, VP of Business Development for Retalon

Every year, retailers put fresh spins on evergreen holiday décor, remixing such classics as the Christmas tree and jack-o-lanterns to tempt seasonal shoppers. Though we have yet to see this year’s big trend, it’s probably safe to say it will not be the Christmas Turkey or Thanksgiving Skeleton.

Inventiveness is not so much the issue for retailers as time. With Thanksgiving, Halloween, and Christmas occurring over a period of two months, it’s critical that retailers practice efficient inventory management to move seasonal items at the appropriate moments. Retailers gearing up for big sales days may incur costs if they don’t strategize inventory properly.

Here are three prime examples of where retailers go wrong with seasonal inventory, as well as solutions for better management.

Too often, chain retailers fail to balance inventory between locations: 

It’s common for an item to be sold out in a particular colour or size (SKU) in one store, while it’s in abundance at another location. This imbalance is a double whammy for retailers trying to clear inventory.

The balancing act is especially challenging with holiday inventory, which becomes outdated in the blink of an eye. The fluctuating demand for this nonessential inventory – along with the fact that what’s “hot” can vary by location – makes it extremely difficult to forecast sales using historical data.

Out of stock translates to lost revenue and may push customers toward the competitor. Surplus results in painful markdowns. Worse, by the time businesses realize the imbalance, it’s too late to avoid the associated costs. The sale and the consumer are out the door and bargain basement pricing is inevitable.

It is possible to get ahead of the problem. Retail predictive analytics is an increasingly popular solution for retailers struggling to manage inventory. A Gartner report states that by 2016, 70 percent of the most profitable businesses will manage their processes using real-time predictive technology.

Predictive analytics systems differ from past metrics in that they anticipate the necessary transport of an item before the transfer becomes tedious and overwhelmingly expensive. Inter-store inventory balancing solutions takes into consideration all costs associated with the switch, including logistics, store capacity, demographic diversity and the sizes and colours most likely to sell at individual locations.

The quick succession of fall holidays demands quick turnover. Predictive analytics is especially useful for clearing the bottleneck and selling out seasonal inventory at maximum prices.

Retailers misjudge inventory needs during promotions: 

Retailers often use promotions to generate traffic in their brick-and-mortar stores. After all, what customer can stay away from a great deal, or twenty?

The trouble is most retailers don’t execute promotions profitably. Lacking an integrated inventory management solution, they many times fail to connect pricing and promotions with ordering and replenishment.

By setting needlessly low markdown prices, businesses deplete inventory before demand. This mismatch negatively affects profits and customer relations, since shoppers who arrive a day or two later will not expect items to be out of stock.

Another step in avoiding this dilemma is to consider how media pushes like television ads, Facebook promotions and billboards increase inventory needs. Retail predictive analytics pulls from demand forecasts, replenishment, current inventory levels, promotional media types, price optimization and product cannibalization to determine optimal inventory at the SKU/store level.

Add stock only when it adds value: 

Retailers’ hands are tied when it comes to inventory shipping, a frustrating reality since premature or delayed shipments can have major financial ramifications for businesses. Early shipments bring higher carrying costs, while late or incomplete shipments may ruin promotions by causing items to go out of stock.

In order to protect against shipment problems outside their control, retailers typically add safety stock to inventory. But safety stock also carries a cost, and thus requires optimization. Unfortunately, optimal safety stock proves fairly difficult to calculate.

Overdone safety stock defeats its purpose by making it harder for retailers to optimize their supply chains. The idea of investing in additional inventory with the hope of additional sales is flawed – it creates an endless imbalance between what is needed and what is stocked. Leveraging retail predictive analytics, retailers can better optimize safety stock and keep on-hand only what is needed.

About the Author:

Jim Malone is the Vice President of Business Development at Retalon, the world’s leading provider of predictive analytics for the retail industry. Since 2002, Retalon has optimized pricing, inventory management, merchandising, planning and marketing operations for retail organizations in a variety of industries. Retalon products range from task-oriented solutions to a common analytic platform, resulting in tangible optimization of the supply chain and significant measurable benefits for the entire organization.