Fashion is such a competitive market that personalisation is essential to stand out.

Customers now expect brands to understand their preferences and deliver experiences tailored to their unique tastes. Artificial Intelligence (AI) plays a crucial role in achieving this level of personalisation, revolutionising how fashion brands interact with their customers. AI enables fashion brands to analyse vast amounts of data and extract meaningful insights to personalise customer interactions.

By delivering relevant content, recommendations, and experiences, brands can build deeper connections with their customers. This leads to higher satisfaction, increased loyalty and higher lifetime value.

I agree with the thesis that Ai personalisation can lead to higher satisfaction, increased loyalty and higher LTV. However, I think this needs to be balanced with product development and end to end customer experience. In my view the best loyalty programme is customers tellin their friends about your product without any incentive. And this is a function of an incredible product. What's more, there is no point having the most sophisticated Ai personalisation if a consumer has a terrible post-purchase experience. So, yes to Ai personalisation. Assuming one is placing the same value on their product and post purchase experience.

1. Flexible Payments = Increased AOV and CVR%

A normal conversion is what… 2%? 98% of the people that visit your site don’t bother buying anything - this is one of the best sources of new potential revenue so brands try all kinds of crazy things to drive this number up. One effective strategy is to use AI-powered content personalisation to highlight flexible payment options early in the shopping journey. 

Example:

For instance, Lords & Labradors (an online pet products retailer) saw a 37% increase in Average Order Value and tripled their conversion rate by using personalised content to promote payment options and incentives across various customer segments​. 

Maybe try:

• Using AI to create and test personalised messages that highlight flexible payment options.

• Segmented Messaging: Tailor messages based on customer segments, such as first-time visitors and returning customers - which segments need to know about available payment options?

2. Personalised Product Recommendations

AI algorithms can analyse customer behaviour, such as browsing history and past purchases, to recommend products likely to appeal to each individual. These personalised recommendations can be displayed on the homepage, product pages, and in follow-up emails, increasing the likelihood of a purchase. For instance, AI can suggest complementary items or outfits based on a customer's purchase history and preferences​.

AI-driven product recommendations can dramatically enhance the shopping experience by making it easier for customers to find items they are likely to purchase. 

Example: 

Skinnydip London, a fashion accessories brand, used AI to personalise their category merchandising, achieving an 8x ROI and covering their annual personalisation technology costs in just one month​.

Maybe try:

• Behavioural Analysis: Using AI to analyse customer behaviour and preferences

• Dynamic Recommendations: Provide real-time, personalised product suggestions on various parts of the website, including homepages, product pages, and emails

• Cross-Selling and Upselling: Recommend complementary products to increase basket size and overall order value

3. Enhancing Marketing Campaigns

Leveraging AI, brands can create highly targeted marketing campaigns that resonate with specific customer segments.

AI helps identify customers who are likely to respond to particular promotions, enabling brands to send personalised emails, social media ads, and SMS messages that speak directly to their interests and needs​ 

Examples: 

Benefit Cosmetics leveraged AI to segment their audience and tailor email campaigns for the launch of their new blush range, resulting in a 50% higher click-through rate and a 40% increase in revenue compared to similar campaigns​. By targeting previous buyers, VIP customers, and new subscribers with different messages, they maximised engagement and drove higher conversion rates. Similarly, boohooMAN leveraged AI to personalise their SMS campaigns, resulting in a 5x overall return on investment and a 25x ROI from their ‘birthday campaign’ flow​.

Maybe try:

• Audience Segmentation: Use AI to segment your audience based on behaviour, purchase history, and engagement levels.

• Personalised Messaging: Tailor email content to match the preferences and needs of different customer segments.

• Campaign Analytics: Use AI-driven analytics and alerts to optimise campaigns based on performance data.

4. Improving On-Site Search and Navigation

AI-driven personalisation can also enhance the on-site search experience, making it easier for customers to find what they are looking for. 

Examples: 

Outside of fashion, this is a very popular tactic where AI is implemented. Castorama, a home improvement retailer, improved their conversion rate by 24% by using AI to personalise their site search​​. HD Supply experienced a 16% increase in revenue from search on their ecommerce website by optimising their search functionality with AI-powered personalisation​​. Similarly, The Vitamin Shoppe saw an 11% increase in add-to-cart rates and a 2% increase in revenue per visitor by using AI to personalise search results and category pages​.

Maybe try:

• Personalised Search Results: Use AI to deliver relevant search results tailored to individual customer preferences.

• Optimised Category Pages: Enhance category pages with personalised content and product recommendations.

Honourable mention in this section

Dynamic Pricing:

While exploring AI-powered Search & Merch, it’s worth exploring your pricing strategy. AI can optimise pricing strategies based on customer data and market conditions. Dynamic pricing algorithms adjust prices in real-time, offering discounts to price-sensitive customers while maintaining higher prices for less sensitive ones. This approach maximises revenue while ensuring competitive pricing.