Most businesses are at risk of trapping their customers in a cycle of repeated recommendations, according to a new report.

Research from analytics firm SAS found 93 per cent of businesses surveyed were unable to use analytics to accurately predict what individual customers will want in future. However, 54 per cent mistakenly believed they are ‘best-in-class’ when it comes to using customer intelligence to shape their campaigns.

Despite a push towards using artificial intelligence (AI), too many customers are being left in their own ‘digital shadows’, stated SAS. They are being served with 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.

“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,” commented Tiffany Carpenter, head of customer intelligence at SAS UK & Ireland. “Too many companies are not using all the information available to make accurate predictions about their customers’ latest tastes and circumstances, as a result, businesses are missing out on new revenue streams, not to mention the risk of damaging their customer relationships.”

SAS surveyed 350 heads of marketing, customer service and experience, digital and data, split equally between the energy, government, insurance, media, retail, telecoms and retail banking sectors.

Although a quarter claimed to calculate new offers based on real-time context, only 10 per cent purposefully introduce new products to see whether customers will try new things. The majority (61 per cent) based recommendations solely on historical data and previous purchases.

The report found that 69 per cent of respondents are planning to enhance their customer experience by implementing AI within the next three years, while 14 per cent already have an AI programme in place for this. In practice, cognitive engines and machine learning are the most common types of AI, with 35 per cent using or planning to use cognitive engines to create chatbot-style solutions that provide human-like interactions, while 28 per cent use or plan to use machine learning to automate analytical insight.

Most companies are planning to collect less customer data as a direct result of General Data Protection Regulation (GDPR). Information about customers’ physical location and personal contact details will both saw an eight per cent drop, with basic demographic information and web browsing behaviour close behind at six and seven per cent respectively.

SAS stated that GDPR presents an opportunity to improve ‘data hygiene’ as companies reduce their data collection habits, which could benefit the customer in the long term.

“Nevertheless, companies will have to balance the need to ease GDPR compliance by collecting less customer information with the need to maintain enough data to enable effective customer analytics,” added the report.

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