Ocado is to use a relationship marketing platform as it looks to engage with its customers in a more meaningful way.
It is working with relationship marketing specialist Selligent to develop personalised shopper marketing campaigns using real-time data drawn from customers’ online behaviour. Those marketing programmes will be delivered across channels including mobile, social and email.
Thomas Thomaidis, head of marketing and grocery insight at Ocado [IRDX ROCA], said: “We are looking forward to taking full advantage of Selligent’s capabilities to have timely, relevant and helpful conversations with our customers across multiple digital channels.”
Ocado will use the platform to target customers with more relevant messaging to help build brand loyalty and consumer engagement. The solution also enables web content and experiences to be personalised around specific interests such as purchase history and grocery preferences. Website data can also be used to customise messaging across other digital channels.
Christopher Baldwin, Head of Marketing, Northern Europe at Selligent, said: “We are delighted to be working with Ocado, an established and well-known brand in households across the UK. Through use of Selligent’s Consumer-First Marketing tools Ocado will be able to deliver consistently personalised and targeted communications across all channels. It will enable them to transform their customer experience by understanding, tailoring and acting upon individual shopper behaviour.”
Selligent works with 700 brands in 30 countries worldwide, employing 500 people across 10 offices around the globe.
This technology builds on Ocado’s use of technology to improve its customer service. Last year Ocado Technology implemented an artificial intelligence programme to better organise customer emails.
The online grocer, a Top100 company in IRUK Top500 research, deployed a machine learning-enhanced contact centre, that uses an AI software model developed in house and using tools from the Google Cloud Platform, to categorise incoming customer emails. Machine-learning helps the system to understand and respond to the natural language that customers use. The AI model parses the email, adding a summary and priority tag (as seen left), leaving customer service staff free to focus on solving problems for customers, rather than spending time categorising thousands of emails manually.