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What Happens When IoT, Big Data and Retail Location Systems Meet?

The retail industry is in decline. People commonly attribute the decline to three factors: too many malls, customers switching to online shopping and a change in mindset from materialism to experiences. 

But what if we brought the online experience to offline shopping — would that counteract the latter two reasons?

Customer Experience Drives the Way
An estimated 73 percent of shoppers use mobile devices while shopping in a store to check reviews, product datasheets, usage guidelines and more. 

And while shoppers find facial recognition technology 'creepy,' they welcome product descriptions, guidelines for product usage or lists of related products. Even more appreciated are the discounts that pop up while walking the aisles or coupons for products you left abandoned.

Simply put, consumers want digital shopping experiences in physical environments. Online features such as recommendation engines create win-win situations by making purchases easier for customers and bringing high ROI for shop owners. 

But how can we clone these to the offline world?

It's About Time IoT Meets Big Data
The technology is already here. While some companies have already put their faith in iBeacon  technology, the Ultra Wide Band retail location systems (UWB RTLS) bring more accurate distance and location measurement — for example, Sewio, which delivers accuracy within 15 centimeters and 50 millisecond update time. 

Retail stores already track transactional data of their sales and are using floor plan and planogram management systems, including Retail Smart, Oracle Retail Macro Space and others, to plan the product placement of each item group. 

What's missing is a Digital Proximity Engagement Platform to integrate these systems and provide the presentation layer.

How would this work?

Bringing Online Experience to In-Store Shopping
Think of a 10,000 square meter home improvement shop such as Home Depot in the US, or Hornbach in continental Europe. 

Let's say you need a fence screening for your balcony. The shopping cart in store is equipped with a handle-mounted tablet, and as you go from one aisle to the other, the content of its screen updates. Unlike when you use your own mobile device, both of your hands free for shopping. You pass a ceiling fan that grabs your attention, and so the in-store trolley tablet updates with details about the fan. 

Upon reaching the fence screening section, the screen displays all types of fences, featuring the one with the highest margin, but also displays related products: cable ties, flower planters and so on. In short, helpful advice is served to the consumer, with the retailer benefitting from additional revenue opportunities.

From Basic Steps to a Real Omnichannel Solution
What basic use cases of this system would deliver the highest estimated ROI?

Basic Scenarios
1. Recommendation engine
Recommendation engines provide anywhere between 12 to 68 percent of online revenues. Amazon attributes 35 percent of its revenues to its recommendation engine.

And the benefit isn't one-sided. While recommendation engines increase a retailer's revenues, they also provide guidance for customers to make a more informed purchasing decision. This is especially the case in situations like our home improvement scenario above.

2. Location-aware interactive marketing
Marketing messages linked to shopping cart position can include detailed information on the product, including educational content or product reviews. 

The key difference in-store as opposed to the online environment is that the retailer controls the content and its flow. Shoppers are unable to skip to other sites or sources, and instead are channeled to be more receptive to the retailers’ messaging. 

Retailers gain additional revenue from vendors for featuring their specialized content, mirroring existing static in-store merchandising and promotion. This additional location supported channel can be used by retailers and vendors alike. Industry sources have already suggested that 34 percent of companies plan to invest in location-based marketing in 2017.

3. Abandoned Shopping Cart
Online shopping carts have a 68 percent abandonment rate. A brick and mortar store provides a more immediate connection to the customer who has abandoned their physical shopping cart without the need to identify the customer. 

The digital proximity engagement platform can make a simple join between receipt and shopping cart information. In this case, pairing purchase information with motion data which tracks the dwell time at a non-purchased item, would provide the required data to trigger a “second chance” to buy.

Advanced Omnichannel Scenarios
4. NPS questionnaire
A 7 percent increase in Net Promoter Score (NPS) correlates on average with a 1 percent growth in revenue (pdf). However, how often do you get asked an NPS question at a physical store? 

Why not create a feedback loop linked to transactional data and customer's motion? This can be as basic as asking a simple question during or after the shopping experience, with some kind of incentive to aid response rates.

5. Mobile in-store concierge
Even after the tablet has served related content for your purchase, at times customers may require individual assistance. After standing at a particular fixture for more than three minutes, the system can ask if the customer needs help. 

This can be localized to an assistant who has expertise in the product area the customer is interested in, rather than randomly asking a passing member of staff. In doing so, the retailer alleviates some of the service burden on staff and streamlines the process of providing personal assistance and customers get help when needed and from a representative with relevant product knowledge.

6. Closest way to product
The ability to query the product catalog and quickly find the item location and quickest route to it might not be favored by all retailers considering the reduced in store roaming time and lowered chances for impulse purchases. 

However, as customers become more time conscious, the increased customer satisfaction gained from finding solutions quickly will hand the innovative retailer a competitive advantage that in the longer term will outweigh the potential lost revenue from roaming.

7. Indoor Analytics
The list of metrics retailers might use to get customer insights seems exhaustive. The main areas include:

Mapping customers’ motion and subsequent heat mapping the retail layout
Time spent at each zone/item and overall time spent
Once the cashier pairs the tablet to the receipt, the retailer can perform an analysis of a customer’s dwell time on items and cross-reference this against actual purchases versus lost opportunities.

8. Additional features in exchange for logging in
We’ve already replaced paper notes with shopping lists in our mobile devices, but wouldn't it be more convenient and fun to have both hands free to pick up the goods, and have your list projected onto your trolley tablet? A single sign on method could bring content personalization to a new level including productivity features, access to loyalty program data and various new features which deploy gamification techniques.

9. Scanner-enabled features
Finally, home improvement stores already include kiosks where customers can self-scan products to access detailed product specification and benefits, not just pricing info. 

But what if the kiosk walked with you instead of being a static feature in the center of the store? The ability to scan the product on-shelf and then share it easily via instant messaging or social media channels adds an additional dimension to the collaborative shopping experience today’s customers are hungry for.

Who Will Create the Digital Proximity Engagement Platform?
Retailers are keen to adapt online tools to leverage their advantages in the physical retail environment. In a recent survey, 75 percent plan to host a single shared cart across channels within three years. 

What would it take to build a product that joins data from UWB RTLS with a retailer’s planogram software and transactional data? The answer is surprisingly, not much: three developers, one user experience designer, a project manager and a 12 month gestation period to get a functional prototype that will be well on the way to fulfilling the mission of digitizing retailer space.

About the Author
Petr Passinger is CRM Product Manager at Oracle-NetSuite. He was formerly the sales operation leader for Kentico, where he was responsible for the mapping and optimization of the sales funnel and revenue cycle.