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Retailers using location analytics to improve customer experience

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Consumers are starting to engage with businesses in new ways, using the Internet to post questions or to track orders. Rising consumer expectations in relation to when they will get their goods is driving interest in location analytics.

Retail, as with other sectors, is going through a digital transformation process. This is partly driven by the availability of technology and partly by the sector attempting to adapt to the expectations of consumers. One way in which the sector is starting to measure, develop targets and to improve the experience of consumers is through the application of big data derived from location analytics. Such data is collected by digital technology.

With consumer expectations, a review of behaviors by Gary Sankary for Retail Drive notes that people are increasingly searching for, comparing, and purchasing merchandise online and at any time. This can range from tracking down the location of a department store for an in-stock item by checking a cell phones to having an item delivered.

The consequence of this means there has been a shift in the balance of power towards the consumer. To stay competitive, businesses must ensure they are doing everything possible to interpret and predict customer behavior. This includes the speed of delivery and there are signs that consumers are beginning to expect same day deliveries.

Reacting to this is not straightforward, since retailers require sophisticated digital technology to manage assets, optimize delivery routes and meet customer service expectations. This requires the use of real-time data analysis and interactive maps. From this things need to be controlled in terms of time and also spatially.

For this, intelligent spatial analytics platforms are appearing on the market. To be effective these systems need to optimize deliveries and to signal to customers about any delays. An example comes from Alteryx, which provides a self-service analytics platform that allows for analysis of geospatial data to allow for a variety of data sets to be connected and geocoded. The system also allows for demographic data to be inputted (this might be used on the basis that millennials have faster expectations about delivery times than, say, baby boomers). Another thing the software can do is to create trade areas based on drive time, and blend data by physical proximity.

A different approach comes from Esri, where location analytics are used to determine the best location for a store in relation to a target group of consumers. With this, the company states, sales revenues can be increased by “understanding precisely which customers want which products and services, and targeting marketing to specific customers more effectively.”

A third platform comes from Data Science Studio which utilizes spatial technology to construct visual maps, generated from datasets. Such maps contain engaging and interactive elements like such slide bars and color-coded filtering. In one example application, the U.S. IRS designed a heatmap to display student loan debtacross the U.S. This included an accurate regression model that was used to predict the proportion of student loan debt in a given ZIP code.

Being able to visualize business data against an accurate map is an important step in the digital transformation of retail. For those companies that elect to use such platforms, these types of location analytics help to reveal hidden patterns, relationships and trends; providing important business intelligence for the retail sector.

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IoT + Data = Retail Intelligence

In the equation IoT + X = Intelligence, what role can consumer and supply chain data play as the X factor?

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Valued at USD $10 billion in 2017, the retail segment of the Internet of Things (IoT) market is expected to grow at a phenomenal 19% compounded annual rate and hit $35 billion in 2024. New ways of collecting data at the source are enabling this growth. IoT-embedded sensors on shelves and in refrigerators; store beacons that can sense and measure foot traffic; RFID tags on clothes and smartphones with Bluetooth technology are all collaborators in this dance to log and analyze data. Artificial intelligence can then analyze the sheer volumes of numbers generated and give retailers intelligence to increase efficiencies and sales.

The promise of IoT is that it can enable retailers to improve backend supply chain operations and the customer service experience. The following examples illustrate use cases of both.

Frictionless shopping

Amazon Go is a test case for effective use of RFID tags and store beacons to bypass the checkout process altogether. Every item on the shelves has an RFID tag and when the customer walks out of the store, the products he or she leaves with are scanned and billed to the corresponding Amazon account. The IoT at play here delivers more than a seamless customer experience: it also gives the retailer live status updates about inventory, intelligence that can be relayed up and down the supply chain.

An eye on perishables

IoT-embedded sensors in refrigerators can predict when the machine might be about to malfunction based on current temperature and humidity profiles. A similar IoT-driven system used in warehouses alerts vendors about potential spoilage and can prevent waste. While the edge use case of IoT in driving alerts in real-time is an important one, retailers can also extract long-term intelligence about inventory, store traffic and more simply by reading the data and looking for the corresponding patterns.

Interactive shopping experience

At a time when the drumbeats about the demise of brick-and-mortar stores are growing louder, IoT is injecting some much needed theatre into the customer service experience. Digital mirrors in fitting rooms read RFID tags on the garments customers bring in, pull up those items on the mirror and suggest complementary accessories. Customers can also push a button to request the outfits in a different size or colour. 

If a customer has signed on for notifications from a store, in-store beacons through the customer’s Bluetooth can deliver custom product recommendations through push notifications. Such live interactions increase the value of in-person shopping while also delivering intelligence about shopper behaviour.

While IoT dramatically improves backend efficiencies, the customer-retailer interaction can be much more complicated because of data privacy laws. Customers need to willingly opt in to receive notifications and trade data for the value that retailers deliver. 

IoT is already delivering valuable intelligence to retailers. A major grocery store, for example, saved millions by outfitting in-store refrigeration systems with IoT sensors. As the cost-value ratio of IoT devices decreases, expect retailers to leverage the power of IoT even more to deliver crucial intelligence about customer shopping behaviour and increase transparency in the supply chain.

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IoT + Data Analytics = Store Operations Intelligence

How many times have you visited a grocery store the day before a snowstorm or other major weather event only to find the bread and milk aisles wiped clean? What might be a disappointment for you is also a missed opportunity for grocery stores, an industry with an already razor-thin 2% margin.

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How many times have you visited a grocery store the day before a snowstorm or other major weather event only to find the bread and milk aisles wiped clean? What might be a disappointment for you is also a missed opportunity for grocery stores, an industry with an already razor-thin 2% margin.

Hungry for efficiencies

Inventory management, especially for perishables, is a delicate dance. Too little of it and grocers have lost a revenue opportunity every time a customer leaves empty-handed. Too much of it and grocers lose revenue again, this time from spoilage or having to slash prices to clear shelves. Spoilage is a significant problem — grocery retailers lose an astounding $70 million annually because of food simply going bad. 

Market economics further muddies the picture. A whopping 82% of grocery companies are increasing their stock of fresh foods in response to customer demand so there’s simply more perishables to manage — and therefore more at stake.

To ensure not too much capital is tied up in unsold goods, grocery stores forecast demand and supply based on a variety of conditions, including weather, time of year, and even weekly foot traffic. But as Cognizant as observed, a whole host of additional factors affecting inventory management can drain grocery store revenues.

[Download]: Real Estate Manager Goes Digital

Smart systems

One of Cognizant’s clients, a major supermarket chain, found that working with older equipment also challenged inventory management. 

Internet of Things (IoT)-embedded sensors track ambient temperature, temperature of the food, humidity and even electric current flowing into refrigerators to keep a pulse on perishables. But this leads to grocery stores drowning in data. The sensors cry wolf too often forcing the retailer to waste expensive technician time on every perceived crisis. Such waste happens because too often, sensors do not accurately reflect the whole story. 

Cognizant has shown that data alone is not enough, strategic reading of the data tea leaves also matters in increasing efficiencies. Using the IoT sensors, Cognizant helped the grocery retailer monitor inventory in real time — the pressure on sensitized shelves changes when inventory counts drop — and restock accordingly. Even better, Cognizant’s solution analyzed the data feed in real time, at the edge. Algorithms accounted for many variables including work load, cost of energy at different times of the day, whether the door was open or closed, to recommend intelligent solutions. 

Using edge data analytics and IoT sensors, grocery stores can automate many fixes, proactive reorder inventory and even automatically churn out work orders for technicians only as and when needed.

When inventory management is a delicate and challenging operation, grocery retailers need to be strategic about how they invest precious resources. IoT + edge analytics is a game-changer. It gives retailers the intelligence they need to deploy resources effectively and proactively so they can better cater to demand and cut waste. 

IoT-driven asset management and data analytics will be key to success in the grocery industry. Climate change has increased the clamor for sustainability and less food waste. The timing for smart solutions could not be better.

Read more about Cognizant’s IoT refrigeration solution here.

[Download]: Real Estate Manager Goes Digital

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Punchh raises $40M in funding to augment AI capabilities

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In a bid to bring digital transformation to the brick-and-mortar retail space, startup Punchh has raised $40M in Series C funding, co-led by Adams Street Partners and Sapphire Ventures

The company creates data-driven, AI-powered customer experiences for retailers. Funding will be used to accelerate the development of its customer AI technologies while expanding into new verticals.

Accompanying this funding is news of a partnership with Casey’s General Stores, one of the largest convenience store brands in the United States.

“Consumers expect ubiquity of experiences online and off,” said Shyam Rao, CEO of Punchh in a press release. “In-store retail remains extremely popular and is one of the most powerful relationship building channels ever created. Our platform gives retailers an unparalleled understanding of how customers engage with their brand in the real world, along with the ability to use that understanding to create AI-powered experiences that keep customers coming back for more.”

As VentureBeat reports, Punchh’s products work to “supercharge same-store sales by integrating with existing point-of-sale and ecommerce systems, enabling them to collect in-store and online data that inform customer profiles.”

AI algorithms then optimize these profiles into targeted marketing campaigns and promotions. 

The goal is to promote loyalty which has always been at the core of their business.

While Punchh isn’t the sole venture within the cloud-based customer data management space — SessionM and CleverTap come to mind — Sapphire Ventures’ managing director, president and co-founder Jai Das is keen on the “holistic” nature of the startup.

“Analysts predict ecommerce will account for just 10 percent of total retail sales in 2019, which means about 90 percent of transactions are still taking place in store,” said Das.

This means big-time opportunity in brick-and-mortar retail, with brands consistently looking to better understand their customers, using data to build relationships that translate into lifetime loyalty, and in turn, value for the brand.

“Punchh’s solutions allow retailers to do that in a highly scalable manner, which is why they’re trusted by so many leading brands, and why we’re so optimistic on their long-term growth,” Das said.

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