Despite the widespread take-up of data analytics to improve marketing, companies are leaving customers in their own “digital shadows”, serving them with communications and offers using incomplete data or data that is no longer relevant to their current interests or lifestyles.
Even where the data is relevant, often backward-looking analysis is carried out, meaning the organisation is not establishing the “next best action” for that customer – and things are only likely to get worse under GDPR as firms plan to scale back their data collection.
These are just some of the key findings of a new report by SAS, which shows nine in 10 (93%) businesses are unable to use analytics to accurately predict what individual customers will want in future.
However, more than half (54%) mistakenly believe they are “best-in-class” or “transformational” when it comes to using customer intelligence to shape their marketing campaigns.
Although firms are quick to sign up to buzz topics like AI and real-time customer engagement, many are failing to make good on their promises. For example, while a quarter (25%) claim to calculate new offers based on real-time context, only 10% purposefully introduce new products to see whether customers will try new things.
The majority (61%) base recommendations solely on historical data and previous purchases, meaning customers are likely to receive recommendations based on things they bought previously, no matter what they are looking for now.
However, with GDPR firmly in place, most companies are planning to collect less customer data. Information about customers’ physical location and personal contact details will both see an 8% drop, with basic demographic information and web browsing behaviour close behind at 6% and 7% respectively. That will affect companies’ ability to effectively understand their customers as individuals and tailor their offerings as a result.
SAS UK & Ireland head of customer intelligence Tiffany Carpenter said: “No matter how many organisations say they’re using artificial intelligence and predictive analytics to improve their customer experience, the reality is clearly far behind the talk.
“Too many companies are not using all the information available to make accurate predictions about their customers’ latest tastes and circumstances, trapping them in the digital shadows of their past selves. As a result, businesses are missing out on new revenue streams, not to mention the risk of damaging their customer relationships.
Carpenter added that regardless of the industry, most consumer-facing organisations admit they are still driven by internal sales and targets over customer experience. They need to implement predictive analytics to avoid leaving customers in a rut, she continued.
“It’s essential to incorporate as much data as possible – internal and external, online and offline – in real-time analytics engines to ensure the insights they produce are as accurate as possible. Only then can you achieve the kind of intelligent personalisation that modern consumers now demand.”
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