# Personalising email timing to lift engagement and revenue

> A UK high-street retailer · Retail & Consumer

QuantSpark built a behavioural trigger model that personalises the timing of marketing emails, delivering five times the revenue per send and two and a half times the engagement of standard campaigns.

## At a glance

- **5x** revenue per send versus standard campaigns

## What was the problem?

A UK high-street retailer wanted to grow email revenue and improve customer retention. It needed a scalable way to anticipate customer behaviour and personalise the timing of marketing emails so that messages landed when each customer was most likely to respond.

## What did QuantSpark do?

QuantSpark ran extensive customer analysis to parameterise transaction data and identify meaningful behavioural indicators, including churn probability, product purchase cycles and interest in new-season ranges. Using a combination of machine learning and customer analytics, these parameters became email triggers that serve relevant material at the moment each customer is most likely to buy. The resulting behavioural trigger model powered a suite of automated campaigns embedded within the retailer's existing customer marketing programmes.

## What changed?

Triggered campaigns drive, on average, five times more revenue per send than standard campaigns and two and a half times higher engagement rates.

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Canonical page: https://quantspark.ai/case-studies/email-timing-personalisation-engagement
More about QuantSpark: https://quantspark.ai/llms.txt