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3 Impactful Trends for Personalisation in Retail

Technology

Jul 27, 2022 - 6 minute read

2573 Retail Personalisation 416X300
Rafał Imielski Content Marketing Specialist

He has two years’ experience in copywriting, translation and proofreading. His goal is to help people communicate in a concise and understandable way. Rafał is an archaeology graduate who’s fascinated by both prehistoric and modern technologies. 

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Consumers have grown accustomed to the increasingly personalised experience offered by retailers. Generic messaging and offers are simply not enough anymore, as a result of the raised customer expectations. Retailers need to engage in artificial intelligence (AI) driven personalisation to produce the most relevant and timely communications and special offers for their customers.

In response, retail and tech companies develop new personalisation-focused technologies. Retailers are racing against each other to provide the most delightful customer experience, as it’s one of the best tools to create loyal consumers and brand ambassadors in this ultra-competitive market. Meeting the need for ever more personalised customer experiences is driving innovation among retail organisations that aspire to create a competitive advantage and become leaders in their segment.

This leads to the creation and popularisation of multiple new technologies and approaches. Some of them have the potential to become extremely influential and reshape the way retailers interact with their customers.

Retail Personalisation Trends

At the beginning of the year, we published a report on the most important retail tech trends for 2022. In this article, we’d like to follow up on one of the identified areas — personalisation. This field is changing rapidly as a result of technological developments and innovation. The emerging trends we’d like to cover are best-fit, contextualised pricing, and edge AI.

Best-Fit

The best-fit technology emerged as a way for fashion retailers to help customers find the perfect size and selection of garments when shopping online. It’s a necessary response to a very real industry problem, the increasing number of returns. Retailers have found themselves in a ‘Catch 22’ situation, where returns significantly affect their profit margins and carbon footprint, but limiting access to returns is either prohibited by law or likely to discourage a wide segment of customers.

Poor fit continues to be the most common reason for returning clothing articles. What’s even worse for many retailers, a significant percentage of customers admit to so-called ‘bracketing’ — buying multiple sizes of a particular garment, only to later return the ones that don’t fit. This clearly showcases a lack of trust in the sizes and descriptions presented in the online stores.

The only sustainable way of dealing with this issue is building this trust by providing accurate measurements and recommendations. The best-fit technology can be the perfect response. By utilising 3D data and reliable body measurements, as well as the history of past purchases and returns, the web and mobile apps can produce accurate sizing recommendations.

Technologically speaking, best-fit solutions leverage virtual reality, augmented reality, AI, the internet of things, and computer vision. They can be divided into two major categories: AI-based advisors and body-scanning applications. The former requires the users to measure themselves and input this data, alongside other information and preferences. Then, the solution processes this information, together with purchase and return history, to propose specific products and sizes. The latter utilises the camera on the user’s mobile device. Consumers have to take photos of themselves, so the solution can analyse them and create a 3D model of their figure and body type. This model is later used to provide personalised fit and size recommendations.

Contextualised Pricing and Promotions

While not strictly new, personalised communications and promotions are becoming increasingly important and advanced. It’s especially visible in omnichannel retail. Customers who receive a personalised shopping experience are more satisfied and likely to recommend the brand to their friends. Tapping into this trend can be a crucial differentiator, determining if retailers can survive and thrive in the market. This is becoming relevant not only in fashion but also in other categories, including grocery retail.

Many grocery retailers still struggle with offering personalised or contextualised promotions to their customers. This results from the traditionally siloed processes handling regular pricing and promotions, often based on legacy ERP platforms or even Excel. Such a setup makes it difficult to implement a personalised approach. When it’s combined with poor utilisation of media channels and campaigns, it can contribute to poor performance of marketing activities overall.

In order to make the most out of the personalised promotions, retailers should focus on several key areas:

  • Breaking down the silos related to regular pricing, discounts, and promotions to create holistic revenue management capable of supporting personalisation within a single view.
  • Implementing AI to produce insights that’ll help analyse customer behaviour and buying patterns as well as leverage them to create personalised promotions.
  • Forming a strategic alignment between media activity, marketing campaigns, demand forecasts, and promotions.
  • Putting in place strong customer segmentation practices allowing to provide communication that feels personal with reduced effort.

According to Gartner, a move to contextualised real-time pricing is the best approach to implementing personalised promotions. Retailers, especially the ones aiming to provide an omnichannel experience, should leverage the customers’ mobile devices to deliver relevant, individualised offers at the right time.

Edge AI for Personalised Advertising

Edge computing moves data storage and processing closer to the source of data. It’s a promising approach that can boost response times and improve data security. The combination of edge computing and AI can be a real game changer for retailers, allowing them to offer increasingly personalised services while ensuring privacy and GDPR compliance.

By processing data locally, it’s able to avoid all the risks and setbacks associated with sending consumer data to centres located in other countries. This technology can be most influential for retailers that leverage multiple sales channels but are strongly rooted in the brick-and-mortar experience, with Gartner pointing specifically at shopping malls and theme parks.

The implementation of edge AI can help deliver real-time, highly relevant, and personalised communications to customers while keeping their data safe. However, utilising edge AI to further personalisation in retail often requires the customers to opt into marketing activities on their mobile devices. The main challenge to overcome is the need for customers to download and use the designated apps on their smartphones. Thanks to edge computing, the collected and processed data never leaves the shopping location. This is crucial for privacy-focused users and legal compliance, but it might not be enough to encourage consumers to use the applications. According to Gartner, most customers need a stronger incentive, such as discounts, free products, increased convenience, or unique functionalities, to opt into sharing their data via mobile apps.

In the long term, leveraging the consumers’ smartphones and placing control over the collected data in the users’ hands can increase transparency and contribute to building trust and loyalty. However, the early stages of implementation and getting customer buy-in may require some work.

From the retailer perspective, these apps can be used to deliver relevant ads and communications based on data such as location, buying habits, and time. The edge architecture provides GDPR compliance by creating a layer of obscurity — the advertiser has no way of knowing which communications were served to any individual user. This data never leaves the smartphone. Furthermore, the device owner has full visibility and control over what data is being collected and for what purposes. In the end, this should result in more data-savvy customers and retailers who can deliver a true omnichannel experience while remaining GDPR-compliant.

Conclusion

Technology will continue to play a crucial part in advancing personalisation in retail. Innovative solutions can help tackle some of the most pressing issues, such as growing customer expectations, sustainability, privacy, and diminishing loyalty.

Smartphones and other mobile devices keep growing their already key role even further. Retailers have to create powerful incentives for buyers to download and use their apps while ensuring flawless user experience and transparency, as well as security regarding data. Most customers are willing to use their devices in that manner, as long as they feel that there’s enough in it for them. With that knowledge in hand, coupled with strong retail technology expertise, organisations can find ways to further their personalisation efforts and delight their customers.

References

  1. Emerging Technologies: Emerging Edge AI Use Cases in Retail, Gartner, 2021,
  2. Innovation Insight for Best-Fit Technology for Fashion Retailers, Gartner, 2022,
  3. Personalized Promotions Will Win, but Grocery Retailers Are Not Ready, Gartner, 2022.
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Rafał Imielski Content Marketing Specialist

He has two years’ experience in copywriting, translation and proofreading. His goal is to help people communicate in a concise and understandable way. Rafał is an archaeology graduate who’s fascinated by both prehistoric and modern technologies. 

See all Rafał's posts

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