Artificial intelligence (AI)
AI implementation will be pivotal in developing a suite of marketing tools that will include personalised landing pages, personalised in-store greetings and tailored content through utilising customer data from multiple sources.
Shop direct claims to serve 1.2 million versions of its homepage (www.very.co.uk), depending on the visitor’s profile, while ASOS also boasts personalised web pages, showing clothing sizes based on data previously submitted by customers. Amazon attributes 35% of its sales to personalisation strategies, according to McKinsey.
AI also allows for enhanced experiences. Augmented reality (AR) was used to transform an empty store into a virtual Lego clothing pop-up shop. Customers could explore a limited-edition Lego wear line of clothing using Snap on their smartphone.
“The in-store experience has become a crucial differentiator of choice for shoppers.”
AI could also allow consumers to receive greetings in-store, formulated on their previous night’s browser history featuring the latest luxury product line.
Here, the Discovery stage of the customer journey from the consumer perspective will have the shared characteristics of a personalised ‘advice service’ albeit implemented by savvy retailers.
Product Recommendation
One of the most recognised applications of data use is accurate product recommendation. Although AI-powered recommendation engines vary greatly in sophistication, advanced algorithms can account for real-time variables such as:
- customer preferences
- purchasing habits
- gift purchase dates
- social media content
- location and weather
These can then be correlated with other existing customer data or third-party databases, with the goal being to seamlessly link online and in-store activity. This will allow retailers to promote and recommend new products in a way that enables consumers to benefit from a catalogue of ‘self-selected’ products.
There is a trend towards more sophisticated recommendations served to consumers via a multi-platform, multi-device approach, which retailers and brands can assess for maximum impact.
For one customer, a combination of video content and social media might be the most effective way to convert awareness to sales while for another it could simply be email targeting.
However, this new dawn of increasing product recommendation accuracy is predicated on vast quantities of customer data. And, as research reveals, consumers are often reluctant to provide this information, leaving retailers and brands to tread the difficult line between value and intrusion.
Lastly, with numerous high profile organisations suffering from data breaches and third party use of consumer’s data without their knowledge or consent, issues of trust are paramount if retailers are to foster meaningful relationships with their customers.
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This research was conducted by Retail Economics in partnership with Pennigtons Manches Cooper and forms part of a wider piece of research that focusses on the initial stage of the retail customer journey for the fashion industry (stage 1 of 4). It unpacks the key themes that influence consumers and retailers here and identifies future trends in this space. Retail Economics supplied the data sets, collected from a consumer survey of over 2,000 nationally representative individuals in Q1 of 2019.
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