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How is AI being used for customer engagement?

Digital technology has revolutionised the way fashion brands interact with and engage customers. Now, AI for customer engagement is a further evolution. 

Why AI is important to drive customer engagement?

First of all, what is customer engagement? It is the process by which a brand manages to make customers feel valued, informed and motivated to interact

Underpinning the success of any customer engagement strategy must therefore be a deep understanding of consumers. AI technology is essential to help companies do this. Thanks to AI, companies can access information that would otherwise remain hidden. This information is needed to create more personalised experiences that will increase customer satisfaction and loyalty. From product recommendations to offering discounts or promotions at the right time, personalisation is the key to customer engagement. 

However, customer engagement strategies can be costly for brands in terms of time and resources. Fortunately, artificial intelligence makes it possible to automate tedious tasks such as customer segmentation, part of customer care, or marketing. Thus, companies can focus on higher-level activities that require human judgement and creativity and provide value-added experiences that will keep customers coming back. This also helps achieve higher ROI, especially from marketing activities.

AI for customer engagement: 10 implementations that enhance customer experience 

Wondering how to use AI for customer engagement? Here are some of the most interesting use of it.

Data Analytics

One of the best applications of AI for customer engagement is in data analysis. 

AI-driven analytics allow companies to gain insights into customer behaviour and preferences, enabling them to create more tailored experiences. For example, Natural Language Processing tools can be used for gathering customer feedback and understanding how customers feel about certain products or services. Moreover, predictive analytics allows brands to anticipate customer needs. Both help brands adjust their messaging accordingly. 

Chatbot and virtual assistant

Chatbots and virtual assistants are already used by many companies to provide customers with around-the-clock customer service. Chatbots are able to interact with customers in real-time via messaging apps or websites. They provide customers with 24/7 support, answering questions quickly and accurately without the need for human agents. Virtual assistants can interpret customer queries to provide more detailed information about products and services. They can also provide personalised recommendations, and even help customers complete purchases.

In general, AI-driven automation tools can speed up the process of providing customer support by automating some time-consuming tasks such as responding to common questions or issues.

Personalised recommendations

By leveraging AI technologies, such as Machine Learning, AI-driven platforms can collect data from customers’ past interactions, purchases, or browsing history and use it to make tailored product recommendations.

Omnichannel seamless experience

AI-powered technologies allow businesses to provide a consistent and seamless experience across multiple channels. Natural Language Processing tools can be used to interpret customer queries regardless of the platform or device being used. This helps brands deliver a connected omnichannel experience.

Automated marketing campaigns

AI-driven platforms can automatically target customers with relevant content and product offers based on their previous interactions. 

AI solutions such as Robotic Process Automation (RPA) have become increasingly popular in marketing departments, helping automate mundane tasks such as creating ad campaigns or targeting potential customers. By automating such processes, companies can save time and money while driving higher ROI from their marketing efforts. 

Better CTA and personalised content

AI can be used to incentivise customers to click on a CTA or share UGC by leveraging data analytics and personalisation tools. As we have said, by using AI-based data analytics and predictive analysis, brands can gain insights into customer behaviour and preferences, enabling them to craft personalised messages that are more likely to engage customers. This is useful not only to show the right products but also the right content, increasing interaction and engagement.

Image Recognition Technology

With this technology, customers can take pictures of an outfit they like or find online, then use it as a reference for searching for similar styles in the company’s inventory. This makes the customer experience smoother, more enjoyable, and more satisfying, increasing customer engagement. 

Fraud detection

AI can analyse the huge amount of information online to uncover misuse of copyrighted material. But most of all, it can help detect fraudulent activities in customer transactions, making sure that businesses are not losing money due to illegal purchases. Moreover, it is a powerful tool to fight counterfeiting.

Here in Certilogo, we have been using artificial intelligence for many years to enable consumers to verify the authenticity of products from many of the best-known fashion brands. Our proprietary fraud detection system analyses data in real-time and recognises fake products, as well as any non-compliant distribution of authentic products. All the consumer has to do is scan the marker on the label with their smartphone and access the branded authentication platform. This system transforms the products into connected products that give consumers security but also offers them access to exclusive content, information and services from the brand.

graphic summary of the implementations

The future of AI in fashion

In 2018, the global market for artificial intelligence applied to fashion was estimated at USD 270 million. Forecasts expect it to grow to $4.4 billion by 2027.

As technology advances, AI is being used more widely across the fashion industry for a variety of purposes, from automated styling and design to personalised shopping experiences. The goal is always to create unique customer experiences that build loyalty and drive sales. As fashion continues to use artificial intelligence in innovative ways, it will be interesting to see how far this technology can take the industry.

24 Apr 2023

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