Consumer’s shared experiences outweighs company’s brand narratives in any platforms on social media, review sites, product forums, blogs or any other form on-line communication medium. More than ever before the retail sector must invest not only in creating positive brand experiences but also making them shareable and there is no other way to do this better than making them also predictable.
In this age of connected consumerism, new social technologies are empowering consumers and creating new forms of demands. Technology is shaping society and consumer behaviour, changes are happening faster than many companies have to adapt. A phenomenon some came to describe as Digital Darwinism.
Consumer’s shared experiences outweighs company’s brand narratives in any platforms on social media, review sites, product forums, blogs or any other form online communication medium. More than ever before the retail sector must invest not only in creating positive brand experiences but also making them shareable and there is no other way to do this better than making them also predictable.
Many experts in the field believe that machine learning technologies (ML), big data and behavioural analytics aligned to user-experience design discipline could give companies the answer they need, however nothing is a clear cut as it initially might look. In November 2015 Amazon opened its first high street brick-and-mortar books store emulating their online store and strategy has nothing to do with selling books but everything to do with data collection. The success of the first Amazon Books has led to additional three book stores with the fourth was just recently announced in February 2017. The stores resemble traditional book stores but Amazon use online data to determine which titles to stock at the stores. Clearly, Amazon has the intelligence that other brick-and-mortar book stores do not have. The concept of Ebay Virtual Reality department store is also an example of the retailer aiming for, not only creating consumer experience, but also gathering insights data.
When a shopper signs in with their amazon app account, Amazon can immediately associate its online customer records with his or hers to whatever this customer is doing in store. It can then identify customer preferences, buying habits and history, status as an Amazon Prime and/or Amazon credit card member and so on. This is just the start of a highly personalised consumer experience including customised price that fluctuates depending on who is purchasing and when it is being purchase, even who that is likely to being purchased for. Amazon is known for its ability to maximise digital data for price competitiveness. An analysis published in 2013 showed that Amazon changed prices of its products around 2.5 million times a day compared with just over 50,000 total price changes made by brick-and-mortar retailers BestBuy and Wal-Mart throughout November 2013. By understanding customer behaviours from data gathered Amazon can make more accurate recommendations and potentially making every price personalized thus optimising every transaction.
Amazon is just one of the many global brand playing with what is now being called machine learning technologies or just artificial intelligence (AL). According to Bart Selman, professor of computer science at Cornell University
“Artificial Intelligence is moving rapidly from academic research into the real world… computers are starting to ‘hear’ and ‘see’ as humans do… Systems can start to move and operate among us autonomously.”
Amazon is not alone, most IT or internet giants such as Google, Microsoft, Apple and Facebook have been investing billions in AI and deep learning technologies.
Machine learning technologies to improve customer experiences
Within the next few years business gains will more likely to come from getting the right information from and to the right people at the right time. ML will empower companies to find patterns and automate value extraction coming from different areas. Data driven real-time economy will guide savvy companies to run more efficiently as the production of production of goods and services becomes on-demand, predictive behaviour machines will lower the rate of failure.
It is very likely that we will see extremely intelligent supply chain systems, an increased in depth of knowledge in consumer preferences with great capability to build and design meaningful experiences at every touch point of the customer journey. Designing experiences that will be delivered with higher level of customisation. A German food brand MYMUESLI is has started to experiment with augmented product choices by taking their packaging printing process to some of their large stores closer to the end user. Their strategy it to bring production as part of the end-user experience augmenting their products mix of flavours by adding another one extra dimension: packaging. That has given customers a unique opportunity to engage with the whole production including the printing and designing of the packaging.
Is your company machine learning ready?
The future of retail business lies in the ability organisations may have to fight these Darwinian forces operating within their industry or in the wider environment by fast adapting and promoting gradual changes in the organisation. Companies will have to respond fast to the increasing demand from a highly sophisticated and technology empowered consumer by deploying machine learning algorithms, bid data and highly engaged consumer shareable experiences that will appeal to all their human and social needs.
Online giant extending brick-and-mortar footprint (16 February 2017). http://www.chainstoreage.com/article/online-giant-extending-brick-and-mortar-footprint
 Profitero: Amazon changes over 2.5m prices every day in quest to be most competitive. (11 December 2013). http://www.retailtimes.co.uk/profitero-amazon-changes-2-5m-prices-every-day-quest-competitive/