Retail
How AI is transforming the e-commerce customer experience
24 July, 2019 | Written by: Arlene Helbert
Categorized: Artificial Intelligence | Retail
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As little as ten years ago, most of us did not yet own a smartphone. The idea of self-driving cars, drones and augmented reality devices still seemed like the notions of far-fetched science fiction. Fast forward a decade, and few could have predicted how quickly the pace of innovation and change would increase. From Amazon Alexa to Apple Siri, artificial intelligence (AI) services have quickly become an integral part of daily life.
E-commerce is also undergoing a rapid transformation. We have more places and ways to shop than ever before. Inspiring people to take the leap from online browsing to purchasing increasingly depends on connecting with customers on an emotional level. Savvy e-commerce retailers are rapidly becoming aware of the importance of using AI in their marketing strategy. Understanding their customers and knowing what they want allows retailers to enhance their online experience. Let’s take a look at some of the ways in which modern retailers are using AI to achieve exciting results.
Making sense of your data
Retailers have an almost overwhelming amount of customer data at their disposal. In fact a recent study by Domo found that 90% of all data today was created during the last two years.
All this data is great. But how do you connect all the dots and make sense of it all? Mapping the retail customer journey has fast become a crucial component in understanding what your customers want when they visit your website. This mapping is made possible with powerful marketing behavioural analytics solutions. Their AI capabilities can process a wealth of data from multifarious sources in seconds, providing trends and insights not accessible through human analysis alone.
You can see how customers behave while they visit your site, the path they take to conversion or where they struggle. When you map out a customer journey, you are using your existing data to identify different scenarios. You can then plan and anticipate how a customer will behave at every step of the journey. For example, an outdoor clothing retailer can identify where, when and for what activities a customer requires a jacket. Taking into account other factors such as gender and weather, they can recommend highly targeted and personalised selections. This kind of personalisation can also be applied to online content and messaging. This helps to create a truly emotional connection with customers, by targeting them with products they want and sending them email messaging and content they will respond to.
E-commerce site optimisation
Building an emotional rapport with your customers online is essential in order to stay competitive. I recently experienced first-hand how a bad online customer experience can negatively impact brand loyalty. With little time for in-store clothes shopping, I do most of my shopping online and on my mobile phone. Based in Ireland, I’m happy to shop from UK websites and pay in pounds, for better deals. On a recent e-commerce shopping trip, however, I was continuously redirected to the store’s EU page, based on my IP address. It was very difficult to choose the currency I wanted to shop in. Every time I tried to check-out, I was met with errors and the website would crash. I would then be redirected to the EU page, rather than the UK page where I had a full shopping cart waiting to check-out. I had to switch from my preferred mobile to a desktop in order to make the process work. It seemed to me that the retailer didn’t know me or understand my needs. While I provided feedback to the retailer, in truth, after such a bad experience, I haven’t returned to the site since.
Site optimisation uncovers usability flaws like these, and allows you to compare segments side-by-side to optimise the experience. AI empowers online stores to change their layout, offers, and branding to fit each individual customer. It also enables retailers to immediately identify where customers are struggling. In my case, simply having the power to replay my session would quickly have highlighted some crucial design flaws.
Watson AI in action: The Home Shopping Network (HSN)
Watson marketing solutions have been helping retail businesses map online journeys and deliver exceptional customer experiences. One such example is The Home Shopping Network (HSN), which has customers who engage with the brand across an array of digital touchpoints. HSN’s goal as a retailer is to provide great products, combined with great stories and storytellers in order to sell those products. The company wanted that experience to be seamless and consistent across all channels. Like many leading retailers, HSN previously relied on separate processes to power its marketing strategy for each channel. However, this approach made it complicated and labour-intensive to incorporate data on client interactions across different channels. As a result, it was difficult for the retailer to answer questions such as: “Which of our products are most likely to appeal to this shopper?” and: “What kind of message is most likely to resonate with this shopper and thus lead to a purchase?”
HSN used Watson Customer Experience Analytics to understand exactly what its customers wanted. The company was able to replay customer sessions and identify individual customer struggles. It was also able to identify preferences by mapping out retail journeys, thus helping to deliver compelling, tailored and timely messages at every touchpoint. Using powerful Watson AI technology, HSN was able to turn data into meaningful customer insights. For example, customers looking for particular products could be targeted with similar products and messaging. HSN was able to understand not only the behaviour of its customers, but also their preferences in terms of products, content and devices. This knowledge empowered HSN to provide the right message, on the right channel, at the right time, and to the right customer. The AI capabilities of Watson enabled HSN to see the bigger picture and connect the dots for maximum impact. This kind of tailored customer experience helps the retailer show its customers that they really care.
Bringing it all together
AI is changing how today’s customers browse and shop. And, more important, it’s changing how retailers respond to their customers. AI-powered customer analytics can process data that is impossible for a human to comprehend. This gives modern retailers the opportunity to strategically analyse their data to see the bigger picture. AI is transforming the e-commerce customer experience by allowing retailers to create personalised, emotional experiences. Connecting with your customer on an emotional level will create loyal customers who will love your brand for years to come.
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