Omnichannel retailers have been trying to bridge this knowledge gap by integrating point of sales and customer relationship management data.
For retailers to deliver a truly omnichannel experience, they must integrate data across channels and evaluate the same. This is easier said than done. While online shopping data has become relatively easy to collect and analyse, there is growing convolution with every new channel, that is being incorporated into our digitalised lives (e.g. smart watches and voice assistants like Amazon Alexa).
In-store shopping data and behaviour is also much harder to track. Omnichannel retailers have been trying to bridge this knowledge gap by integrating point of sales and customer relationship management data.
To complement these initiatives, artificial intelligence is set to supercharge omnichannel analytics, and in turn, omnichannel customer engagement.
“Get closer than ever to your customers. So close that you tell them what they need well before they realise it themselves.” This prominent quote from the late Steve Jobs highlights what retailers should strive to accomplish from a customer engagement standpoint.
With the right mobile strategy, retailers will come closer to shoppers than ever before. Here, AI will help to anticipate needs, well before these needs are fully evident to the shopper. AI has a huge potential impact, and hence it’s no surprise that the technology’s adoption in India is rising. According to a report commissioned by Intel, 70 per cent of Indian organisations will be deploying AI-enabled solutions by 2020.
While making decisions based on data is nothing new, human marketers are simply not equipped to mine terabytes of data at the speed and scale necessary to deliver hyper-personalised engagement to millions of consumers at the same time.
We also have machine learning technology, which can act on data with speed and precision. Being a subset of AI, machine learning involves computer systems that are capable of learning and improving performance through data analysis, without human intervention.
Some tech savvy retailers across our region are already using machine learning to serve dynamic ads on PCs and mobile devices. The algorithms behind these ads learn how individuals respond to various creative versions or featured products. By considering product selection, images, taglines, formatting, colour, copy and call to action, the technology then automatically serves –from trillions of permutations – the ad variation that is most relevant to an individual at a specific point in time.
For instance, machine learning is applied to differentiate between items that are a rare / one-time purchase (e.g. a car or a furniture), as opposed to one that will be regularly replenished (e.g. bread or toilet paper). These insights prevent customers from being overwhelmed by BMW ads when what they really need is to be reminded that they are running out of toothpaste.
In short, AI in the form of machine learning, is already powering retail channels and marketing campaigns. For better engagement across their consumers. We have only just begun to see its influence. Businesses will need to embrace this technology if they want to succeed, or they will risk losing out to competitors who are using it to better engage with their consumers.
The article has been penned down by Siddharth Dabhade, Managing Director, India, Criteo
Live: People Reading Now