Decoding the digital consumer: data, experimentation and AI

“Multiple things are happening at the same time,” says Anja Lambrecht, Professor of Marketing at London Business School. “The amount of data companies have access to has exploded!”

On the plus side, this means brands are now able use targeting to gain a greater understanding of their customers and serve them products that are relevant to them. “It really is about understanding customer segments and niches,” she adds.

Classic marketing aims, in other words, but with exciting new tools in the box. So, how can companies take advantage of the latest technology available? 

“We have information about our consumers, but they’re also very busy,” says Greg Crawford, Professor of Economics at the University of Zurich, and Chief Economist at the fashion platform Zalando, which has more than 50 million active customers, with differing tastes, and a vast number of products – 87,000 T-shirts, to give an example.

“Attention is a real challenge. We want to show them the fashion that’s relevant for them, and we want to give them a convenient payment experience and delivery experience.”

Naturally, the company is harnessing artificial intelligence to determine which items to show where on the platform to optimise sales. “GenAI is really changing the way companies like ours start to think about solving problems,” he says.

The landscape is changing all the time, in companies’ favour. As well as the data on granular consumer needs, they can also experiment to figure out what individual consumers respond to. For example, they can run an A/B test to see if you respond to, say, a 10% discount or a 15% discount offer. Firms can also use AI in unsexy but extremely useful ways to increase efficiency – to speed up coding, for example.

Complement AI with other methods and you’re onto a winner. Using structural models allows you to discern from millions of consumers’ data how attractive an item of clothing is. “The cool thing is you can combine these tools to benchmark against each other and get trustworthy insights and scale,” says Crawford.

It’s also possible to get an idea of what’s likely to prove popular next – to see which of the products you have coming down the line will be hits. Beyond that, you can use data from an established market to make assumptions about a less established market

Digital has also enabled new brands with limited budgets to reach out through new media to specific segments – running a TikTok campaign to specific groups for a new craft beer or cosmetics instead of paying a huge amount for a TV ad that most viewers will ignore.

“For entrepreneurs and young brands, this offers a huge opportunity to launch and grow,” Lambrecht points out.

For firms seeking competitive advantage, these tools are invaluable for growth. As ever, leadership is critically important. Moving to a data-driven way of decision making isn’t just about having the right technical skills within the firm, you need to be able to communicate findings skillfully to the commercial leaders who are making the decisions.

Instilling a data- and test-driven culture is crucial, therefore. Consider what you’re evaluating and which tasks you’re prioritising. “The key part is to know which tools can help you make good decisions,” Lambrecht stresses.

Crawford agrees: “These tools are an unbelievable capability that can provide an innovation engine for the company. It superpowers business decision-making.”