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PREDICTIONS 2019 How will technology drive changes in shopping over the coming year?

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PREDICTIONS 2019 How will technology drive changes in shopping over the coming year?

How will retail change and develop in 2019? We hear from industry insiders and share their predictions for the year ahead. This ongoing series will focus on a different theme each time. Today we’re looking at new ways we might shop over the coming year - and the technologies behind them

 

From the car, as the connected car becomes a shopping platform

Dan Mitchell, global director of retail and CPG, SAS

 

The amount of technology built into modern cars is staggering. And, if your car is connected to your smart phone, it already knows a lot about you, your habits and preferences. Equipped with this knowledge, in the future your car will help you plan and execute a shopping journey more efficiently. For example, many people already use the Waze app for crowdsourcing about speed traps, construction, accidents. Reimagine using that same technology to crowdsource shopping trips and errands: I could grab that prescription while I’m picking up the dry cleaning, then make a grocery run on the way back to buy those steaks that are on sale for dinner tonight. As long as the retailers involved offer something of value to reduce the burden on the consumer – creating a quicker, more accurate shopping experience – consumers will welcome the assistance.

 

IoT in Retail will make shopping less overbearing

Rachit Khare, VP, client solutions (analytics) at The Smart Cube

 

IoT is helping retailers follow customers through their shopping journey – from search/exploration to making a purchase. With rapid advancements in software and increased adoption of wearables, IoT is helping deliver the right message at the right time to the right audience.

 

Consumers are not complaining either, with retailers using technology to make it easier for customers to find the right product and access product information ‘on the go’ or while in store. The challenge for retailers will be to make sense of all the data in order to have a higher ROI. For this, there will be a need for marrying data science with specialist retail experience to provide actionable insights.

 

Peak 2019 will be all about intelligence, not performance

Huw Owen, head of EMEA & APJ at database company Couchbase

 

In 2019 we’ll see a big jump in how retailers use analytics. For example, the Black Friday weekend is becoming less about performance and more about intelligence. Simply ‘keeping the lights on’ for the shopping bonanza is now the norm: while it’s certainly a good thing your online sales don’t collapse, it’s not enough to really differentiate from the competition.

 

With Black Friday sales and promotions starting earlier each year, the real winners will be retailers who use this extra time to deliver real-time, personalised content to customers during the run-up period and on the day itself – since they can tempt people with deals for products they actually want to buy. After all, who wants to see a special offer for shoes they bought last week? One thing’s for sure, bargain prices alone won’t keep customers coming back for more – but they will when attached to the right product.”

 

IoT: Don’t phone home. Figure it out

Atish Gude, chief strategy officer, NetApp

 

Edge devices will get smarter and more capable of making processing and application decisions in real time. Traditional Internet of Things (IoT) devices have been built around an inherent “phone home” paradigm: collect data, send it for processing, wait for instructions. But even with the advent of 5G networks, real-time decisions can’t wait for data to make the round trip to a cloud or data center and back, plus the rate of data growth is increasing. As a result, data processing will have to happen close to the consumer and this will intensify the demand for more data processing capabilities at the edge. IoT devices and applications – with built-in services such as data analysis and data reduction – will get better, faster and smarter about deciding what data requires immediate action, what data gets sent home to the core or to the cloud, and even what data can be discarded.

 

Image: Fotolia

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