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Re-inventing retail and the future of data driven AI

By James McKeone | Principal Data Scientist

August 16, 2021 | 9 min read

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The new normal of e-commerce has shifted fast and has steered a new reality for consumers and retailers alike. In a recent report by McKinsey, we have vaulted ten years ahead in consumer and business digital penetration in less than three months.

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The comfort and convenience of shopping at home has enabled consumers to be savvier with their shopping habits

Within retail, the pandemic has levelled the playing fields, allowing smaller retailers and brands to compete with bigger names who would previously dominate the digital space.

If we’ve learnt anything from the last 16 months, it’s that e-commerce has become more than a transaction, it’s become an interaction. As consumers, we’ve grown to expect the personalisation and convenience that we’ve solely relied on during the peak of the crisis.

E-commerce expectations and consumer habits

With more free time available and the comfort and convenience of shopping at home has enabled consumers to be savvier with their shopping habits. Pre-pandemic benefits such as free delivery and click and collect were already on the rise. However, the pandemic has increased the need for contactless shopping and deliveries, with over 496 million parcels sent with Royal Mail in just the last three months of 2020.

Consumers now want more flexibility when it comes to their shopping experience. The pandemic pushed retailers to invest in their delivery services or establish a click and collect service. Among consumers who purchased online and picked up their items in-store or curb side, 64% say they are now doing so more often than before the pandemic.

Similarly, the lack of interaction with an in-store assistant or physical product meant that the requirement for updated and accessible websites became an important buying factor. In the same way that personalised communications dominated the market, making the customer feel as though their purchase journey was specifically tailored for them.

As we all spent more time online during the pandemic, we have become even less tolerant to sites or apps that are slow, unresponsive, or unusable. The journey from landing page to checkout needs to be as flawless as possible to meet the standards of the modern consumer. Product descriptions needed to be as detailed as possible, websites need to load in a timely manner, and live chat needs to be always available.

As retailers navigated challenges presented by COVID-19, conversational commerce became particularly invaluable to fully engage with buyers at the pinnacle point in their purchase journey.

From March 16 to July 1, interactions between customers and sellers increased by 85% on Shopify Ping (free messaging app), compared to the year prior. As a result, sales attributed to chat increased by 185% during this time.

Make more data driven decisions

A trend that has evolved heavily over the last decade is the use of AI and machine learning within the retail sector. Advanced AI algorithms examine consumer demographics, social media impressions and digital footprints to decode their interests.

Retailers often require guidance when it comes to making strategic decisions, using a combination of data driven AI and machine learning methods where feasible, coupled with human insight and the awareness of the potential for bias.

This occurs when an algorithm produces results that are systemically prejudiced due to flawed assumptions in the machine learning process.

Among larger companies, the overwhelming amount of data has reached almost unmanageable levels. By merging data integration and AI forecasting as one in the same investment, a stronger and more collaborative relationship can be formed from the outset.

It’s important for AI and machine learning platforms to provide a single source of truth for business decision makers, BOSCO™ uses this methodology and a bespoke built algorithm to incorporate marketing metrics from multiple data sources, delivering actionable insights.

There are countless use cases for AI in marketing, and each of these use cases yields different benefits such as risk reduction, increased speed, greater customer satisfaction and increased revenue.

Focus on sustainability and brand purpose

An increasingly ad fuelled marketing space, paired with the murky distinction between authenticity and sales gimmicks can make it difficult for brands to resonate with their audience.

The future of retail needs to be more authentic, with brands pledging more time into their brand purpose and point of view. This can range from sustainability to a global movement. 64% of consumers said that they would boycott, avoid, or switch brands based on its stand on societal issues.

With the current climate problems, sustainability is also a key area for retailers to explore. 81% of consumers have said that they are more likely to choose a brand with a positive approach to environmental sustainability, showing a clear development in consumer attitudes towards a business’s approach to the environment.

This is particularly prominent in fashion, where there is a huge appetite to ditch ‘fast fashion’. In a bid to improve public perception, Zara (BOSCO™ Index: 674) announced their sustainability goals, vowing that all of their clothes will be made from 100% sustainable fabric by 2025.

One way that retailers are tackling this issue is by offering rental and subscription services. These innovative rental services facilitate the transition to a circular economy. With more of us making sustainable choices, particularly in areas such as fashion and furniture where tastes change so often, items can be returned to the retailer and reused, or recycled in the correct manner.

Utilise technology to integrate the in-store and online experience

From digital screen browsing, easy mobile payments, or ordering online with a seamless delivery or click and collect service, there is a clear disconnect between what consumers expect and what retailers can deliver.

Retailers need to utilise innovative in-store technologies that give shoppers a new level of convenience and a personalised experience, integrating the offline and online environments. This includes tech such as contactless payment systems, digital screens that offer in-store shoppers certain features of online shopping, and augmented reality (AR) systems for testing products, such as trying on clothes or seeing a piece of furniture in their home before purchasing.

IKEA (BOSCO™ Index: 740) launched the IKEA Place app in 2017, allowing consumers to virtually place true-to-scale models of furniture in their own homes, to see how it will fit and look before purchasing.

Today, the app has features that combine AI and AR, and people can do more than just place furniture. Consumers can get smart home furnishing tips and recommendations based on curation, context, and behaviour.

As we return to the high street, consumers want to see more digital and instore integration. 65% of consumers are more comfortable making in-store purchases with digital or contactless payments. Post-shutdown, consumers would like to keep the convenience and speed of ordering digitally and then picking up at or outside the store.

Ultimately, COVID-19 hasn’t been the catalyst for the re-invention of retail or e-commerce. Most of these developments were in place and have simply been accelerated.

Subsequently, retailers should consider adopting the right technology to make both the online and instore experience more absorbing and user friendly. This could mean investing in AI and machine learning platforms to make better strategy decisions when it comes to their interacting with their customers.

In terms of instore success, retailers need to provide sales associates with digital devices to enable them to better help customers find what they need, offering shoppers product recommendations on the next product to buy, or making phones and mobile apps a useful part of the shopping experience.

Such technology not only provides next-level customer experience; it also gives retailers access to valuable data that can feed into personalisation algorithms or be used to optimise their marketing and sales strategies.

BOSCO™ gives brands and agencies the power of predictive analytics, connecting and transforming your marketing data to provide powerful dashboards and insights. Book a demo to find out how BOSCO™ can help your business.

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