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GUEST OPINION How a phone camera can predict your customer’s next purchase

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GUEST OPINION How a phone camera can predict your customer’s next purchase
GUEST OPINION How a phone camera can predict your customer’s next purchase
The rise of the smartphone has reshaped retail, but we ain’t seen nothing yet: tapping into all the things a phone can do is the next step in the development of retail, both online and in the High Street. Ofri Ben Porat, CEO, Pixoneye explains

The retail industry has undergone significant changes over the past decade. Retail channels, customer behaviours, and business models have been fundamentally altered by the growth of mobile technology.

The rich trail of data each smartphone user creates through their browsing and purchasing activity has given online retailers a pivotal advantage over traditional bricks and mortar competitors due to their ability to personalise the customer experience and adapt their product and services to market needs.

Last year, in line with general consumer preferences, mobile became the method of choice for e-shoppers as 51%  of online sales involved handheld devices rather than traditional computers or laptops. This was matched with a healthy 12.6% growth in online retail sales.

The appeal of the High Street

Those that predict the imminent death of the High Street may however be overlooking its key attraction – the ability of the in-store experience to satisfy all the senses ahead of making a purchase decision.

In fashion, for example, with such varied influences and styles available, there’s no way a classic target marketing segmentation will tell you what someone likes to wear – you need to see it, feel it, and visualise how it fits with your self-identification and style preferences. This physical experience cannot adequately be replicated online, and so shoppers continue to visit High Street stores, albeit in declining numbers.

For retailers that cater for both online and in-store customers, such as high street department stores, the question becomes how they can offer mobile commerce (m-commerce) whilst maintaining the additional benefit of physical shopping.

In short, can they still deliver a personal shopper experience in a digital world?

Retail in a mobile world

Our smartphone image galleries have in many ways become a reflection of our lives.

Every day we document our lives and activities across multiple channels, whether it be sharing holiday snaps on Facebook or getting a friend’s opinion on a new purchase via WhatsApp or Messenger. Our phone gallery captures many of the details, decisions and nuances of our lives.

Each person’s gallery is unique and distinctively theirs. If someone were to look through your pictures they’d know more about you than from a simple conversation. They’d get an accurate depiction of your interests, tastes, and favoured possessions.

Each image you have stored contains a range of data attributes and meta tags that not only reveal your past purchasing profile, but can also be the key to predicting what purchases you’re likely to make in the future.

Accessing the right data

The challenge for e-retailers has been accessing and analysing this rich trove of data points in a way that protects personal privacy and offers commensurate value to the consumer.

Online businesses need more advanced data to really understand their end user and adapt their offering according to consumer demand. Social media only provides a fragmented snapshot compared to what exists on-device and in closed groups.

Smarter use of data also impacts merchandising. Mobile businesses have limited real estate in which to present product lines to end users, and so must know which offer is most likely to garner clicks and sales. For example, a retailer may have 90,000 SKUs, but can only promote a handful of their product line on screen at any given time.

Without access to the right level of data, retailers are unable to promote the right products to their end users, potentially missing out on critical sales opportunities.

Predicting the customer’s next purchase

Using image recognition and understanding technology, retailers can – with the consumer’s consent – anonymously gain access to the data contained within image galleries. The retailer (or, more accurately, its marketing team) will not see the images themselves, but simply be able to use the data contained within for a full 360 degree, contextual understanding of the individual, their lives and motivations.

In the retail industry, this means that smartphones can effectively play the role of a mobile personal shopper, with the power to predict the individual’s next purchase. The retailer can analyse its customers’ styles, helping them to identify key upcoming moments that will influence imminent purchasing decisions and tailor their offering accordingly.

Is the customer starting a new job and will they need suitable professional attire? Are they about to go on holiday and need a new set of beach clothes? Have they been on a fitness bootcamp ahead of the holiday and will be looking to refresh their wardrobe with slimmer fitting clothing? Do they need appropriate dress clothes for wedding season?

By layering deep learning and artificial intelligence on top of on-device image recognition, retailers can predict these moment. Combined with existing datasets and strategies, this data brings greater relevancy to suggestions and offers that will help retailers to enhance their engagement with new and existing customers.

Satisfying demand through personalisation

Using the data contained within images to predict an individual’s future needs supports retailers to get the most out of m-commerce and satisfy their customers’ needs, before they even arise.

The quality of this data is far superior to the demographical and hyperlocal (e.g. weather, events, etc.) data that retailers have traditionally relied upon to make marketing decisions, and adapts to changes in customers’ lives in real-time.

The key is personalisation. Online, consumers take personalised experiences as a given, and this expectation is increasingly being mirrored in physical environments. Consumers expect brands to understand them, and use the data they provide to offer products and services that are right for them.

Image recognition presents the opportunity for retailers to gain an unprecedented understanding of their end users and present the right content, products and services to them when most relevant, regardless of whether they’re shopping online or in-store.

By offering a more curated and personalised service, retailers can improve the shopping experience for their end users and in turn, increase sales, engagement, and potentially even reduce returns.

In a crowded retail market, it's the brands that are able to predict their customer’s next desires that will reap the benefits of the mobile age.
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