Personalisation Tech: The Key To The Future Of Marketing Automation

Personalisation is soon becoming a core strategy for brand marketers today. Personalisation leaders stand to capture a substantial share of the market along with the profits, leaving the slow-movers behind. When brands leverage technology to action on the user data they collect, they (brands) stand to gain big rewards.
Personalisation tech is a bunch of technologies, strung together that facilitates the digital interactions between brands and customers.
Recent studies have shown that 78% of the consumers will engage with offers ONLY if they are personalised to their past experiences with the brand. A survey by Salesforce revealed a vast majority of customers are even willing to share their data with brands for personalized offers and recommendations in return (See image below).
In addition to the above, a majority of the forward-looking brands (see chart below) investing in the personalisation tech, are witnessing unprecedented gains. Nearly a third of the marketers surveyed cite personalisation as most important to marketing in coming years. According to a recent survey, 48% of the US retail marketers reported that personalisation on their websites or apps lifted revenues in excess of 10%.
Today, we see a shift in the industry’s focus. From personalising with just ‘User Context’ & ‘Click-stream data,’ to personalising ‘product recommendations’ based on product affinity. Adding to this, is the development of consistent, personalised experience across all channels – which requires brands to integrate data across all touchpoints and personalise communication, based on user’s response to each channel, is the new standard.
Using Dynamic Product Messaging, a personalisation tech solution that uses customer information and Artificial Intelligence to deliver personalised product recommendations across digital channels to users, brands can send behavior-triggered messages that reach users via the push notification and email channels.
The solution is built atop the platform’s proprietary Sherpa Interaction Graph, which maps each user’s behavior with the products or content from the catalog and powers these product recommendations.
Let us understand this with the example of product recommendations by OYO Rooms –  India’s leading budget hotel booking chain. Dynamic Product Recommendation, in some cases, has helped OYO Rooms observe an uplift of up to 45% in campaign performance.
User Data: OYO Rooms tracked user actions like ‘Booking Confirmed’, ‘Hotel Viewed’, ‘Booking Cancelled’ to reach out to users with dynamic recommendations via emails and push notifications.
 
Segmentation: OYO created segments of users who have recently ‘Viewed’ a hotel but did not complete a booking.
 
AI Personalisation: Using MoEngage Sherpa Interaction graph and Dynamic Product Messaging auto-creates personalized emails with hotel recommendations to users who cancelled the booking.
 
Digital Channels: The recommendations are sent via the email and push notification channel to users.
 
In Conclusion
The market for personalisation is fast-expanding, backed by heightened acceptance by users to receive personalised communication and increased business outcome for brands.
 
Personalisation marries the best of both worlds – for customers as well as brands. The emergence of new technologies will only continue to strengthen the personalisation stack, helping marketers inch closer to their personalisation goals.
 
Perhaps we will, one day see organisations boasting a Chief Personalisation Officer – someone who understands both the technology and the user data to drive personalisation efforts.
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