When competing with top digital retailers like Amazon, innovation, differentiation and providing personalised experiences are key factors to knowing and understanding how the less tangible data points, like quality customer service and overall brand messaging, can work in their favour.
Only a truly personalised, consumer-centric business model will succeed in making a dent in the competition against the online retail giants. Consider this: e-commerce has levelled the selling field. Choice is unlimited, location is irrelevant and even price no longer creates a competitive edge.
The emotional, personalised piece of the puzzle is what appeals to consumers and what ultimately drives revenue. Your audience expects — and will reward — timely, effective communication and an experience that makes them feel as if you genuinely know them, understand their preferences and needs and are attentive to their taste. For example, Millennials prefer to have a personal and emotional connection with the businesses in which they choose to invest their time and money.
The challenge in delivering effective levels of personalisation is doing so without a way to collect and analyse tremendous volumes of customer data. This is where artificial intelligence (AI) steps in to provide the solutions needed to collect and analyse data and thereby help get ahead of the ‘Amazons’ of the world.
Leverage AI to personalise the online retail experience
AI is an umbrella term that encompasses everything from Apple iPhone’s SIRI to self-driving cars. Although a far cry from the robots with human-like characteristics often depicted in science fiction movies, today’s AI technology can still perform some impressive tasks. These include:
Automation
AI has the capability to automate many types of systems or repetitive processes businesses engage in. This is invaluable when it comes to personalisation because in order to provide a truly personal experience, you need to be able to respond to each consumer’s needs at the right moment for them. For example, automated AI processes can identify when a consumer has left an item in their cart but hasn’t checked out. In this case, the automated system will automatically send out an email to gently remind the consumer of his desire to purchase that item.
Machine learning
Machine learning refers to the ability of AI systems to act without programming. This capability is similar to automating predictive analytics. The implications are immense as it is essentially allowing a computer to ‘figure things out for itself’. You simply indicate what type of data to collect and what ‘lessons’ need to be learned as a result of that data. The machine learning AI then leverages that data for continual optimisation — the more data, the more intelligent the AI gets.
Machine vision
With machine vision, computers can use a camera to capture and analyse visual information as if they have eyes of their own. Machine vision can bring about a new era of personalisation in online retail, as it has the ability to significantly reduce the gap between the personalised in-store shopping experience and online shopping from home. Imagine your computer suggesting a pair of jeans to match that top you’re wearing?
Natural language processing
Natural Language Processing (NLP) refers to a computer’s ability to recognise and understand human speech. The most common use of NLP to personalise online retail shopping is the implementation of chatbots. With chatbots, online retailers are able to determine a consumer’s specific needs anytime, anywhere and provide personalised solutions for them.
Examples of personalised AI-powered solutions
AI has the power to collect omni-channel audience data. This includes consumer data collected from a variety of channels such as social media, chatbots, customer service interactions, site-pathing, mobile messaging and really any digital channel that consumers touch. AI can capture data from all of these avenues, collate it, analyse it and present it in a way that makes good business sense. Personalised AI-powered solutions dictate next steps that are immediately apparent and actionable.
This data may be used to personalise a business’s message to each unique consumer. It removes the guesswork from sales and marketing strategies and reveals streamlined, action-orientated plans for success. AI also provides information that helps business owners or sales and marketing teams know which price point delivered at what time will increase the likelihood of a given consumer to purchase.
Our solution, for example, enables online retailers to tap into the power of AI in order to analyse consumer data and provide personalised incentives to each shopper. Using the principles of behavioural economics, messaging is specifically tied to the individual. This is useful to both the seller and the buyer. It’s efficient. It’s streamlined. It saves time and, more importantly, delivers what the consumer needs.
Another example can be seen with US retailer Adore Me, which recently leveraged AI capabilities to create meaningful connections with its customers; using algorithms to scientifically segment customers according to their past and predictive data.
What the future holds
It is possible to compete with Amazon and other major retail giants. The AI and machine learning technology exists. It is simply a matter of having the ability to collect and measure the audience data in an impactful, revenue-driven way that resonates with consumers on a personal level. Perhaps more easily said than done, the important thing is that there exists a real solution. It’s up to e-commerce retailers to adopt these personalised methods if they aim to compete with the big stores of the digital world. By harnessing the power of AI, smaller e-commerce sellers can differentiate themselves and deliver a far more personalised message. Companies can remain competitive by providing consumer-centric service, pricing and solutions.
The time is now. AI is becoming more widely accessible and affordable and it can truly propel e-commerce brands forward.
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