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The I to T of retail's IoT

// retail The 1 to Tof the loT Intelligent peroonalization Collecting and analyzing data from an ever-widening range of devices facilitates more intelligent personalization of customer experiences: driving sales and boosting revenue by knowing just what to give each customer - and exactly when to give it to them. I RFID tags forecast to be sold in 2015 Just in time 9.2 BILLON RFID tracks stock movement from distributor, onto the shelf, round the store and out via the POS. Reporting on inventory in real time is easy - as is sending online customers to the nearest store with stock, or delivering related information to in-store customers on connected displays and smart shelves. K K.1.S.S Start with your existing technology: CRM, POS, store WIFI, add more where it makes most sense. You don't need huge capital outlay to benefit from connecting mobile and other devices. 96% of retailers are gearing up for the IoT 67% have already implemented it MY STARBUCKS REWARDS Membership grew 900k in QI to 9m members: 5.5m Gold Members. Loyalty Live data means loyalty programs can be tailored to individual customers, giving them the rewards they're most likely to respond to - and making sure you're not giving away margin unnecessarily. M Marketing content Marketing content can be triggered in a number of ways: by crossing a geofence, coming in range of a beacon or WiFi, or even at particular times or days of the week. It can be further personalized with data drawn from customers' mobiles and your other connected devices... N Networked devices The retail loT starts with mobile as the most detailed - and immediate - source of customer data. However kiosks, beacons, in-store displays, PoS, wearables and more can be networked to send and receive data. And with billions of potential data sources, marketing's only going to get more personal. 2015O 5 billion 2020 25 billion 71% Omnichannel customers want to check in-store As customers we want stock online seamless, consistent CHECK STORE STOCK shopping experiences regardless of channel, so retailers need to present a Buy online & collect unified brand and a 50% consistent experience BUY STORE across all channels or customers want to buy online & pick up devices they use: online, mobile, offline and more. P Prescriptive analytics Feeding the data collected from devices through analytic algorithms and processing via machine learning gives retailers the ideal combination of content, time and place to net results: moving beyond predicting results to modelling the best course of action. Q. DND QR codes gre most used for: Product info Video CRM App download M-commerce Multiple technologies help to engage shoppers and create easier, more engaging retail experiences in store. In-app activities, bar and QR codes (which aren't dead), click and collect, image matching, virtual fitting rooms, offline wishlists - even talking coathangers. R Real-time relevance We've all come to expect that we'll be given what we need when we need it. Without live data, real-time personalization becomes more difficult – if you're just working from past purchases and database demographics you can't accurately predict what will work best for each customer. More, failing to meet customer expectations of relevant, timely information can seriously damage a brand. S The top 500 retailers earned Social networks $3.3 BILLON The key to engaging millennials and Gen Z is social sharing - FOMO and the power of referrals will pull customers in when push- FB occounted for 6sA ing your message won't work. It's way more intuitive to share an ex- perience on a device you have at-hand (or on-wrist) than it is when you get to a computer f 2013 2014 hours later. from social shopping in 2014, a 26% increase on 2013 Transaction history Transactional data is important, which is why most retailers have a lot of it. But it isn't enough, which is why Things are such a big deal. Things will help you get the data you need for ongoing personalization: location, weather, local events, transport conditions and more. Purchase history Social profile Location data Point of sale, eCommerce, Marital status, likes, gender Current location, location history, mCommerce beacon proximity Profile data In-app usage External variables Name, age, any other basic profile info currently collected in-app Viewed items, favorites, offer Local weather, local events, traffic redemption, offers shared conditions VMOD

The I to T of retail's IoT

shared by plexure on Feb 20
It’s no secret that the IoT holds huge promise for bricks and mortar retailers. Faced with falling footfall, declining revenue and increased on- and offline competition, brands with physical locatio...


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