Customer Engagement benchmarks are referred to the metrics which measure the success of a campaign.
The most common metrics that enterprise brands measure are:
• Open Rate
• Click-to-Open Rate
• Click-Through Rate
• Conversion Rate
• Unsubscribe Rate

The Customer Engagement Benchmarks Report is your guide to making customer engagement straightforward, personalized, and impactful.

This global report dives into the performance of campaigns across industries like Banking and Finance, Shopping (Retail and E-Commerce), Quick Service Restaurant (QSR), Media & Entertainment, and Travel & Hospitality, offering clear insights into what type of communication works best.

To read the Customer Engagement Benchmark Report for 2026, click on the 'Download Report' button on this page. Once you do, you will be redirected to the regional report hub, where you can read and download your report.

This report analyzes 673 billion messages sent globally (across email, push, in-app, SMS, OSM) over a period of 1 year, covering industries like Banking and Finance, Shopping (Retail and E-Commerce), Quick Service Restaurant (QSR), Media & Entertainment, and Travel & Hospitality.

The regions we covered are:

• Southeast Asia
• India
• Middle East & Africa
• Sub-Saharan Africa
• North America
• Australia
• Latin America
• Europe

We’ve analyzed 3 types of messages (across email, push notifications, SMS, in-app, and on-site messaging) from general broadcast (i.e., without personalization) to those personalized based on behavior and customer journeys.


The aim is to show you the advanced functionalities (powered by AI), actionable strategies, real-world examples, and the need for a single/consolidated martech platform that can do everything from data unification (and management) to orchestrating powerfully personalized campaigns guaranteed to drive business growth!

Personalization is crucial because it cuts through digital noise by making communication relevant. It transforms generic broadcasts that customers ignore into valuable conversations that build loyalty and drive sales.
Here is how it impacts each channel:

• Email: In a crowded inbox, personalization based on a user's purchase or Browse history ensures your message is seen as helpful, not just another promotion.
• Push Notifications: Since they are interruptive, personalization makes them valuable alerts (e.g., a price drop) instead of annoying spam that leads to being disabled.
• SMS: This is a highly personal channel. Personalization makes your message feel like a helpful service (e.g., a shipping update) rather than an intrusive advertisement.
• In-App Messages: Personalization creates a tailored experience within your app, guiding users with relevant tips and feature announcements that boost engagement.
• On-site Messaging: It adapts your digital storefront to the visitor in real-time with relevant offers and content, making them feel understood and reducing bounce rates.

General Broadcast - These are mass messages sent to a broad segment of the audience, often focusing on general updates, promotions, or newsletters.
The personalized email types are:

• Behavior-based Personalization: Triggered by specific customer actions or inactions (e.g., website visits, purchase history, app usage), these communication deliver highly relevant and timely messages.
• Journey-based Personalization: These messages are part of a predefined sequence or flow, designed to guide customers through a specific process, such as onboarding, cart recovery, or nurturing leads.

To personalize effectively, go beyond the name. Use these data-backed strategies:

• Target User Actions: Automate abandoned cart emails and price drop alerts. They drive 8x more opens and 6x more revenue than bulk campaigns.
• Adapt to the Journey Stage: Guide new users with in-app tours and reward VIPs with exclusive SMS offers, as 86% of people say this builds loyalty.
• Use Smart Segments: Group users by purchase history or location for hyper-relevant messaging, which can boost revenue by up to 760%.
• Leverage Real-Time Context: Adapt on-site messages to a user's device or location, since 72% of consumers now only engage with contextual offers.
• Predict with AI: Use AI for product recommendations and to predict customer churn. This model is responsible for 35% of all sales on popular e-commerce platforms.

We have covered 5 metrics in total. They are:

• Open Rate (without and with personalization)
• Click-to-Open Rate (without and with personalization)
• Click-Through Rate (without and with personalization)
• Conversion Rate (without and with personalization)
• Unsubscribe Rate (without and with personalization)