Personalisation Across Channels: How to Deliver the Right Message at the Right Time

Explore personalisation across channels to deliver the right message at the right time for your customers' unique needs.

Tie Soben
8 Min Read
Whether a customer is shopping on a mobile app, browsing a website, interacting on social media, or visiting a store, they expect the brand to recognise them and offer relevant, timely messages.
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Today’s customers expect more than just products—they want personalised experiences that feel tailored to their needs, delivered consistently across all channels. Whether a customer is shopping on a mobile app, browsing a website, interacting on social media, or visiting a store, they expect the brand to recognise them and offer relevant, timely messages.

This article explores what cross-channel personalisation is, why it matters, the technologies that enable it, and how businesses can build effective strategies. It also includes real-world examples and the latest trends shaping the future of personalised marketing.


1. Understanding Cross-Channel Personalisation

Cross-channel personalisation is the practice of delivering customised content and offers across various platforms—email, websites, social media, apps, and in-store touchpoints—based on unified customer data. Unlike single-channel personalisation, this approach ensures a seamless experience wherever the customer interacts with the brand.

A simple example:
A customer browses running shoes on a website, receives an email with a discount for the same product, later sees a retargeted Instagram ad, and visits a store where a salesperson already knows what they were looking at. This is not coincidence—it’s cross-channel personalisation in action.


2. Why Personalisation Is Business-Critical

a. Customer Expectations Are High

According to Salesforce (2023), 73% of customers expect companies to understand their needs, and 62% expect personalised experiences based on their previous interactions.

b. It Drives Loyalty and Sales

Research by McKinsey & Company (2021) found that personalisation can lift revenues by 5–15% and reduce acquisition costs by up to 50%. Moreover, it helps build stronger customer relationships over time.

c. It Increases Marketing Efficiency

Personalised campaigns significantly outperform general messages. Epsilon (2018) reported that 80% of consumers are more likely to purchase from a brand that offers personalised experiences.


3. The Foundations of Cross-Channel Personalisation

a. Unified Customer Data

Successful personalisation requires a single view of the customer. Tools like Segment and Salesforce Data Cloud help businesses collect behavioural, demographic, and transactional data from multiple sources and build complete customer profiles.

b. Real-Time Triggers and Automation

Modern marketing platforms can respond in real time to customer actions, such as:

  • Abandoned carts
  • Product page views
  • Email clicks
  • Mobile app activity

Klaviyo and ActiveCampaign are examples of platforms that automate email, SMS, and push notifications based on behavioural triggers.

c. AI-Powered Recommendations

Artificial intelligence enables personalised product suggestions, email content, and dynamic ads. Platforms like Dynamic Yield and Adobe Target analyse behaviour and automatically adjust what content a user sees.


4. Tools That Enable Effective Personalisation

ToolUse CaseLink
HubSpot CRMUnified customer data and email personalisation
MailchimpBehaviour-based campaigns for small businesses
KlaviyoeCommerce-focused automation
SegmentCustomer data platform (CDP)
BrazeCross-channel customer engagement
OptimizelyWebsite and landing page testing

These platforms allow businesses to personalise communication across email, SMS, web, mobile apps, and more—using real-time behavioural data.


5. Personalisation Strategies That Deliver Results

a. Behaviour-Based Messaging

Rather than sending the same message to everyone, marketers can segment users by action:

  • Browsed a category but didn’t purchase → send reminders or FAQs
  • Completed a purchase → send follow-ups or product care tips
  • Abandoned cart → send a discount or urgency-driven message

Behaviour-triggered emails have a 70.5% higher open rate than traditional bulk emails (Campaign Monitor, 2022).

b. Cross-Device Retargeting

A customer might explore products on mobile, then later receive a desktop ad or app push notification that reinforces that interest. Cross-device personalisation ensures continuity in the journey.

c. Dynamic Website Content

Websites can show different images, text, or recommendations depending on:

  • Referral source (e.g., from Google Ads or social media)
  • Previous visits
  • Customer lifecycle stage

Optimizely and Adobe Experience Manager support dynamic content delivery for personalised user experiences.


6. Real-World Examples of Personalisation at Scale

Netflix

  • Uses AI to create individual homepages, suggest content, and display dynamic thumbnails.
  • More than 80% of streamed content comes from personalised recommendations (Gomez-Uribe & Hunt, 2016).

Amazon

  • Personalises the shopping experience based on browsing, search, and purchase history.
  • Product recommendations account for 35% of total sales (McKinsey & Company, 2021).

Spotify

  • Creates playlists like “Discover Weekly” based on listening history.
  • Over 60 billion songs have been streamed from personalised playlists (Spotify Newsroom, 2023).

7. Challenges and How to Address Them

a. Data Silos and Integration Issues

When data is scattered across platforms, personalisation suffers.

Solution: Use integration tools or a CDP like Segment or Tealium to unify your data sources.

b. Compliance and Privacy Regulations

With GDPR and similar laws, businesses must handle personal data carefully.

Solution: Implement consent-based data collection and clearly communicate how customer data is used. Use tools like OneTrust for data governance.

c. Scaling Content for Segments

Creating custom content for dozens of audience segments is time-consuming.

Solution: Use AI to generate variations, test creatives with A/B tools, and repurpose modular content blocks across channels.


a. Predictive Personalisation

Machine learning will predict user needs and offer products or services before the customer even searches. For example, predicting when someone might reorder a product.

b. Zero-Party and First-Party Data

As third-party cookies fade, brands will rely more on zero-party data (data users voluntarily provide) through surveys and preferences, and first-party data from website and app usage.

c. Personalisation in Voice and AR

Voice assistants like Alexa and Google Assistant are becoming new marketing channels. Personalisation will extend to voice search responses and AR shopping experiences.

d. Hyper-Personalisation

Future strategies will combine location, emotion, time of day, and behaviour to deliver moment-by-moment customised messages—not just based on past behaviour but on predicted needs.


Note

Cross-channel personalisation is no longer a luxury—it’s a core strategy for driving growth, loyalty, and competitive advantage. Brands that master it can create experiences that feel personal, timely, and valuable—leading to higher engagement, better ROI, and longer customer relationships.

To implement it effectively:

  • Unify customer data from all platforms
  • Automate messaging based on behaviour and lifecycle
  • Use AI to deliver real-time recommendations
  • Test and optimise continuously
  • Stay compliant with data privacy laws

Personalisation is about being relevant. And relevance, in today’s world, is everything.


References

Campaign Monitor. (2022). The Ultimate Email Marketing Benchmarks for 2022. Retrieved from https://www.campaignmonitor.com/resources/

Epsilon. (2018). New Epsilon research indicates 80% of consumers are more likely to make a purchase when brands offer personalized experiences. Retrieved from https://us.epsilon.com/pressroom/new-epsilon-research-indicates-80-of-consumers-are-more-likely-to-make-a-purchase

Gomez-Uribe, C. A., & Hunt, N. (2016). The Netflix Recommender System: Algorithms, Business Value, and Innovation. ACM Transactions on Management Information Systems, 6(4), Article 13. https://doi.org/10.1145/2843948

McKinsey & Company. (2021). The Value of Getting Personalization Right—or Wrong—is Multiplying. Retrieved from https://www.mckinsey.com/business-functions/growth-marketing-and-sales/our-insights/the-value-of-getting-personalization-right-or-wrong-is-multiplying

Salesforce. (2023). State of the Connected Customer (5th ed.). Retrieved from https://www.salesforce.com/resources/research-reports/state-of-the-connected-customer/

Spotify Newsroom. (2023). Discover Weekly: 5 Years, 2.3 Billion Hours, and Billions of Discoveries. Retrieved from https://newsroom.spotify.com/2023-07-14/discover-weekly-five-years/

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