Key Takeaways:
- AI technologies like machine learning and deep learning can help gain deeper insights into customer behaviour, and engage people through innovative, interactive content.
- Personalisation is more important than ever for customers, and AI simplifies the process of personalising content based on browsing behaviour, purchasing history, and more.
- AI chatbots and predictive content can be used to improve customer service, lead generation, and data collection.
- Image recognition can be used to organise and tag photos, gain visual insights into styles and trends, and deliver unique customer experiences. However, it’s important to remain strategic and judicious in how this technology is deployed to avoid potential issues around bias or privacy.
Artificial Intelligence is rapidly transforming digital marketing and every industry. Technologies like machine learning and deep learning enable marketers to gain much deeper insights into customer behaviour, tailor the user experience to their audience and engage people through innovative interactive content.
AI powers many of the digital marketing tools we use today, from chatbots and predictive analytics to personalised content recommendations and image recognition. Implementing these tools in your digital marketing strategies can help you make stronger connections with your customers, improve their experience with your brand and gain a competitive advantage.
Here, we’ll explore several ways AI enhances and shapes modern digital marketing alongside other transformative tech tools, and how to adopt AI in an online campaign for optimal results in the fashion sector.
Intrinsic links between AI, digital marketing and fashion
AI and digital marketing are intrinsically linked. Digital marketing strategies provide the data that fuels AI technologies, which in turn attract and engage customers. This symbiotic relationship enables marketers to gain deeper insights into their customers and make data-driven decisions to optimise digital marketing strategies and user experiences.
Personalisation is more important than ever for customers, and AI simplifies the process of personalising content, from product recommendations and style trends that align with previous purchases to custom landing pages that are based on search history. But AI can also be used for predictive analysis, using data mining and machine learning to uncover patterns in customer data that humans might miss. This helps predict things like lifetime value of products, customer trends and the effectiveness of marketing campaigns.
AI technologies get smarter over time by continuously learning from huge amounts of customer data, which means fashion marketing campaigns are always optimised to achieve goals such as higher click-through rates, increased time on page for product pages, greater customer satisfaction and, ultimately, more sales.
While AI is shaping fashion marketing in unprecedented ways, human creativity and intuition remain essential. By thoughtfully incorporating AI into their strategies, fashion marketers can transform the customer experience and drive real growth. But they must guide these tools towards what truly resonates with customers and reflects the brand’s voice.
AI chatbots and fashion retailers
AI chatbots have become an important tool for fashion brands to enhance customer service and engagement. Chatbots are software applications powered by AI that can have automated conversations with customers through voice commands or text chats.
Fashion retailers are employing chatbots to help with customer service, lead generation and data collection, helping customers with purchasing decisions. Some well-known examples of fashion retailers using chatbots include Estee Lauder, ASOS and Tommy Hilfiger, giving these brands and more a high-tech way to connect with always-on customers.
When deployed strategically alongside other AI and personalisation initiatives, chatbots can help fashion marketers boost brand loyalty through enhanced customer engagement. But for the relationship to feel truly personal, chatbots need to be designed to reflect a brand’s voice and values with the human touch in mind.
Predictive content for personalisation
One of the biggest applications of AI is in predictive content, to anticipate the type of content that will resonate most with customers and tailor what they see across touchpoints. By analysing data like browsing behaviour, purchasing history and more, AI technologies can predict the products, styles, trends and creative campaigns that individuals will be most interested in and responsive to. Fashion brands are leveraging these predictions to deliver highly personalised content experiences at scale.
AI can be used to track customers’ preferences and segment them into groups based on attributes like style, size, price range and occasion. Fashion retailers like Stitch Fix then recommend different products to customers based on what would suit each group, according to their unique profiles. The more customers shop, the smarter the algorithms become. It’s also being used for curated designs. Italian eCommerce site YOOX employs AI styling within their private label 8 by YOOX. The algorithm identifies the latest trends and generates designs and recommendations based on the data.
AI can also be used for dynamic digital experiences. On brand websites, AI can power digital experiences tailored to predicted interests in real time. As a customer browses, the website experience continuously adapts to suggest the most relevant products, content, sales and promotions matched to that individual’s needs and preferences. Leading brands are already using AI-enabled predictive personalisation to tailor the customer journey.
Image recognition for unique customer experiences
Image recognition uses artificial neural networks to detect, categorise and analyse images. For fashion brands, image recognition provides an automated way to organise and tag photos at scale, gain visual insights into styles and trends, and deliver unique customer experiences. However, it’s important to remain strategic and judicious in how this technology is deployed to avoid potential issues around bias or privacy.
AI modelling tools can analyse millions of images from social media, online news sites, brand campaigns and more to detect emerging colours, prints, textures and styles which can then be leveraged in product designs and marketing campaigns. The vast amount of data that companies are dealing with now makes it impossible for individuals to sift through and make decisions. Fashion tech company Heuritech developed an AI-enabled service to predict clothing trends by analysing millions of images from social media, taking the labour out of vital tasks in the industry.
It’s an effective tool for virtual try-ons and remote changing rooms, and some brands have also started testing ‘body type chatbots’. These recommend size profiles to shoppers, based on body type classification. Bodify, a Kansas-based start-up, is looking to solve the common fit issues that so many online shoppers suffer with. The company asks shoppers for photos and uses computer vision and machine learning to determine their ideal measurements and provides them with a list of brands that fit the size they believe them to be. It’s a way of minimising returns and clothes being thrown away due to size issues, and opens up customers to new brands they may not have been aware of.
Another angle where fashion is utilising AI capabilities is to create AI-generated models that appeal to the real-world diversity expected in attracting customers who come in all shapes, sizes, cultures and social identities. A recent article in The Guardian online highlighted how top brands utilise AI tech to create inclusive computer-generated models to realistically represent diverse sections of modern society.
AI has enormous potential to transform digital marketing for fashion brands when implemented strategically and guided by human judgement. Technologies like machine learning and visual recognition allow fashion marketers to gain deep customer insights, deliver unique experiences at scale and optimise the impact of campaigns. But the success of AI in fashion marketing ultimately depends on how ethically brands choose to apply it.
AI should be viewed as a tool to enhance human skills, not replace them. While AI chatbots can handle basic customer service queries and machine learning powers personalised product recommendations, human curators remain essential to crafting a compelling brand vision. And though image recognition facilitates photo cataloguing and trend forecasting at volume, human creatives are still needed to design what resonates most with customers.
When fashion marketers thoughtfully and ethically incorporate AI into their digital strategies with humanity in mind, the results can be transformational. AI will become essential to forging more personal relationships, gain actionable insights and meet customers in the right place at the right time with the right message.