By adopting machine learning, retailers can find segments within their customer base with shared interests. In a period of numerous offers, they can learn which work best – all via push button technology. They can avoid giving away margin unnecessarily when they are at their most strained. 

It’s crunch time in the Retail market. 

With less than 2 weeks to go until Black Friday and Cyber Monday (BFCM) and little over a month left until Christmas, many retailers could well be looking at the next few weeks as make or break. 

However, the deepening cost of living crisis has made it an even more challenging time for retailers. Fresh figures from the British Retail Consortium and KPMG shows that UK retail sales growth has slowed to an annual rate of 2.5% in October, whilst are predicting BFCM sales in the UK to drop from £3.9bn to £3bn. Others have also expressed concern…   

Michael Brandy, Senior Commercial Director at “After a year of price rises and high inflation rates, it comes as no surprise that consumers are planning on cutting back on their Christmas spending this year, and unfortunately retailers are set to bear the brunt of these cuts”

Whilst the collective tightening of purse strings amongst consumers could well result in further declines in Q4, it may also lead to an even more crucial BFCM weekend…

Deann Evans, MD EMEA at Shopify: “our data indicates that this could be a key revenue moment for those who embrace BFCM… shoppers have recently cut back so they are ready to spend during BFCM to get more for their money”

Paul Martin, Head of Retail at KMPG: ““This could herald the most competitive Black Friday period that we’ve seen in a while.”

So how do those who embrace BFCM stay ahead, other than price? And almost as importantly, how do those that don’t embrace it at all keep their customers engaged?

At iota-ML, we’ve always firmly believed that the way to grow faster is through hyper-personalization and communication, a fact backed up by McKinsey. Not only is personalization a “nice to have”, it’s also now seen as a fundamental requirement in retail. 

As a recent BJSS eBook suggested, “As retailers capture increasingly large amounts of data, consumers expect to be provided with a personalised experience, and for their individual needs and values to be understood”

So how can retailers win with their customers in Q4 in an increasingly cost conscious market? By getting the right offers to the right customers at the right time through a hyper-personalised content strategy. 

Sounds tough to accomplish, however iota-ML’s no code data science tool uses machine learning and gen AI to facilitate a hyper-personalised content and CRM strategy, even for the smaller marketing teams. 

If you’d like to explore how iota-ML can help you win even more with your customers, please get in touch.