Investopedia, a personal finance site, is the perfect example. The publisher had been hand-curating six different emails to appeal to six segments of readers. It switched to a single template in which content was assigned dynamically, based on the behaviors exhibited by users onsite and in email. This meant that each email contained precisely the content most likely to be most relevant to the reader. Year over year, Investopedia saw a 114% lift in pageviews from email and an 81% increase in sessions from email.

Eves and Gray,  uses interest and behavioural data to encourage repeat purchases. Instead of relying of shoppers perception of what they think they want, E&G use SwiftERM, which relates pre-captured buying habits, with site-visit impressions using every available UTM, to identify imminent, prospective consumer purchase. Using SwiftERM predictive personalisation software, E&G are able to capture masses of additional sales, omission of PPS software would otherwise miss. Customer churn rates drop through the floor, and product returns, because consumers are being offered what they want rather than speculate on, is drastically reduced, delivering a saving not otherwise appreciated in Martech comparison. Basket values escalate too.

Customers expect personalisation. They’ve lost their tolerance for marketing messages that aren’t immediately relevant to them. They expect content, messaging, and experiences to be tailored to their interests. They expect brands to know them individually, not just their demographics.