P2P Toolkit (October 2020)

A roundup of technology-driven tools that drive consumer understanding, engagement and conversion on every step of the path to purchase.

Let’s say you wake up at 2 a.m. with a hankering for a barbecue-stuffed, beer-can, cheddar-jack cheeseburger. Well, now there’s an app for that. This summer, Phoenix-based Pit Boss Grills (PBG) introduced the Pit Boss app alongside its latest grill collection, the Platinum Series. The app enables users to control the various grilling combinations (pellet grill, gas grill, vertical smoker, etc.), check temperatures and follow step-by-step cooking guidance. Equipped with Bluetooth technology, the app also allows grillers to shop for grill collections, enter giveaways from social media and even turn the grill on from anywhere (a feature that may not thrill your next-door neighbors). But for anyone who likes their tech extra-macho, PBG is ready: “Bigger, hotter, heavier, and now, smarter!”

Have faith: Someday, you, me and shoppers everywhere will be back to crowding store aisles. Anticipating that inevitability, MetroClick/faytech N.A. (a German company with offices in New York City) in July introduced the “Easy Shopper Intelligent Cart” to the U.S. and Canadian markets.

This smart cart is designed to enable cashier-less checkout, a running tab of the basket as it’s in-progress, instant personalized sale and promotion notification, the ability to sync shopping lists, a built-in barcode scanner and interactive navigation. The company says it has successfully operated for three years in Europe, claiming more than 1 million users, 11% revenue bumps and 60% lowered theft rates, on average.

Former Chicago mayor Rahm Emanuel was famous for saying, “Never let a crisis go to waste,” advice that DoorDash seems to have taken to heart during the COVID-19 pandemic. DoorDash is primarily a restaurant food pickup and delivery platform, but in April its appetite for expansion took a sharp turn by adding c-store-item pickup and delivery in roughly 1,100 cities via partnerships with 7-Eleven, Walgreens, CVS, Wawa, PetSmart and others.

In late August, another shoe dropped with the announcement of “DashMart stores,” DoorDash-owned and operated digital c-stores that will carry a mix of 2,500-plus household essentials and local restaurant items, “from ice cream and chips, to cough medicine and dog food, to spice rubs and packaged desserts.” At launch, DashMart will serve eight markets: Chicago; Minneapolis; Columbus, Ohio; Cincinnati; Dallas; Salt Lake City; the greater Phoenix area; and Redwood City, California. Openings are planned for San Diego, Baltimore, Denver, Sacramento and Concord, California.

In May, Stadium, a New York City-based group-lunch-delivery service, launched SnackMagic, a direct-to-consumer start up that delivers a work perk – “fun and unique snacks” – to the homes of employees and clients who work remotely. There’s a selection of 500 SKUs from more than 200 brands that change weekly, including some from established companies like Coca-Cola’s Topo Chico or Tate’s Bake Shop sold by Mondelez International, although most are “off-the-beaten path” brands that are new to the marketplace. The SnackMagic website covers 14 different categories such as bars and bites; meat, fish and jerkies; dried fruits, nuts and granola; sodas, soft drinks and seltzers; and wellness, hemp and CBD. There are also themed groupings such as birthdays, seasons, mom-approved, most unique and keto.

With an average order of $45, the company says it shipped 30,000 boxes – each containing an average of 17 different snacks – in its first six weeks. The company is testing a QR code that people can scan once the box arrives that would bring up a page showing what they ordered and how they can purchase more.

Around Labor Day, Amazon announced a new membership program called “Halo,” a health-and-wellness tracking service built around a data-gathering wrist band. The Halo device will, among other things, track the intensity and duration of a member’s daily movements as well as sedentary time and sleep patterns; measure body fat percentage, said to be a better indicator of health than weight or BMI alone; analyze the qualities of your voice – i.e., “tone” – and thereby assess your “energy and positivity” while communicating; and conduct “Labs,” various science “experiments and challenges” from experts like Lifesum, SWEAT and Headspace.

The voice-tone feature immediately raised eyebrows: Could the police, for example, subpoena this data from spouses whose significant others meet untimely accidents? I dove into the terms of service to see how much data Amazon will share with outsiders, and the company says it won’t, without permission. However, whenever a user links Halo to a third-party service, “You are directing us to share information with that service, such as your Activity Score, Sleep Score, body fat percentage, and completed Labs.” And while nothing in the introductory materials states any retailing motivations behind Halo, if the world’s second-largest store knows exactly how much you’ve porked up since Thanksgiving, often sound “hangry” around 2:30 p.m., or toss & turn most nights – well, you can do the math.

I also think I spotted a “tell” in Halo’s privacy video because the animation illustrating how it all works just happened to revolve around – surprise! – a retail checkout counter.


In August, Janesville, Wisconsin-based Woodman’s Markets began testing multipurpose robots at its Sun Prairie, Wisconsin, and Lakemoor, Illinois, stores, with plans to expand the system to all 18 locations by the end of 2020. The robots, designed by Nicholasville, Kentucky-based Badger Technologies, are said to be able to perform shelf scans, monitor product availability, verify prices and deliver location data within a four-foot section of the aisles. These tasks can be especially time-consuming for Woodman’s because its stores far exceed grocery industry averages both in size (240,000 square feet) and offerings (100,000-plus SKUs per store).

The system, which operates for about 12 hours a day, can track item locations and integrate them daily into the Woodman’s mobile shopping app. Badger Technologies claims that its imaging tools enable the robots to detect out-of-stocks and identify mispriced products with 90%-plus accuracy. The company also notes that the 6-foot-4, 130-pound robots are programmed for “courtesy and politeness,” using light-sensitive sonar sensors to detect people nearby and move out of the way.

Here’s a tech update on some old school merchandising: Waukesha, Wisconsin-based Hamacher Resource Group (HRG) has announced a collaborative relationship with International Paper (IP) designed to help retailers with constrained internal category management teams. HRG’s “Shopper Solution Centers” are curated multi-vendor freestanding displays with product assortments designed to address specific opportunities created by evolving market conditions, seasons and/or lifestyles. Under this quick-response program, HRG will conduct detailed data analysis to anticipate market needs, while IP will handle the manufacturing, delivery and any placement challenges (financial, administrative, logistic, etc.).

Robotic “delivery tugs” that move materials around warehouses have become fairly familiar sights. As of August, however, they’re now moving out onto retail sales floors under a partnership involving San Diego-based Brain Corp., Brooklyn Park, Minnesota-based Dane Technologies and Marengo, Illinois-based UniCarriers Americas. (The companies would not reveal which retailers are involved in the deployments.) The goal is to automate the “last 500 feet” – the distance between the stockroom and store shelves – while ensuring safe navigation in high-traffic commercial locations such as grocery aisles. These delivery tugs can transport up to 1,000 pounds of goods, eliminating the need for employees to make the haul dozens of times a day.

According to Brain Corp. executives, these units do not require any custom infrastructure or specialized training; users simply leverage a patented “teach and repeat” technology that also can be adapted quickly to changes in the store layout. The units also provide cloud-based performance metrics in close to real-time on delivery usage, routes and drop-offs.

In late August, Reckitt Benckiser (RB) announced a partnership that would enable its Mucinex brand to use state-of-the art predictive data in a nationwide supply chain and inventory management system. Mucinex’s new “GeoVitalPredictor” will tap into a 12-week advance forecasting model from Kinsa Inc. to create what it calls “the most sophisticated and informed end-to-end supply delivery process.”

Kinsa manages a system of internet-connected smart thermometers (as many as 2 million this fall, according to projections) that are synched to a mobile app that aggregates early indicators of illness – including fever – to understand where and when illness is spreading. By aggregating health data from as many as 4 million people, Kinsa theoretically will be able to accurately predict where in the U.S. sickness is starting and spreading as far out as 12 weeks in advance. Mucinex plans to use this info to “nimbly direct the supply of its cold and flu remedy” (along with localized, branded healthcare messages) to retail locations in those counties where outbreaks are occurring and demand is mounting.

Singapore-based Trax launched “Dynamic Merchandising” in the U.S. The system combines computer-vision and machine-learning platforms with a crowd-sourced workforce of retail reps to deal with in-store execution issues. According to Trax, its proprietary fine-grained image recognition and machine-learning algorithms can turn photos of retail shelves into actionable store-level insights. It does this by converting real-time information from IoT shelf cameras, store visits and POS data into specific execution orders. The idea is that, rather than follow a dated plan that may have been prepared days or even weeks ahead, the company’s “Prioritization Engines” will identify the right reps for each job (based on skillset and other factors) and send them to stores better prepared for priority tasks.

Anyone sorting through field compliance photos to monitor the placement of promotional displays quickly discovers a lot of clunkers: hopelessly out-of-focus shots, photos of the floor and especially annoying, staff selfies. Over the summer Boston-based One Door added “computer vision” capabilities to its Merchandising Cloud platform, a proprietary AI for image recognition that identifies and flags problematic compliance photos. The system not only automatically IDs bad compliance photos but can immediately ask stores to take new shots in real-time. The model is regularly updated to ensure its image recognition results remain accurate for retailers over time. There also are filtering and indexing options enabling users to find photos by location type, planogram, store cluster and item.