60% of Generation Z (born between 1995 and 2005) say they want to change the world. They also have access to all the information they need about the brands they interact with. One in six people in France, for example, uses the Yuka app , which lets you scan a product’s barcode to find out how healthy it is. Another app, Good On You , ranks clothing brands based on their ethical principles.
Consumers wouldn’t be too upset if three-quarters of all brands disappeared from the market tomorrow. So companies that want to stand out from the crowd at the start of the decade should be honest about their role in society and how they plan to improve.
Mass personalization
The time is approaching when birthday emails are effective examples of marketing automation machine learning will change marketing beyond recognition. Today, it helps us better understand users’ paths to purchase, increase their engagement, and make key interaction moments more valuable. This gives marketers more opportunities to analyze user behavior and personalize on a mass scale. Responsible use of the information obtained through these technologies will make marketing more personalized, humane, and multi-channel, thanks to unprecedented content personalization. One of the great examples of this is the video campaign of the car brand Škoda .
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It’s been almost 20 years using targeted lists for upselling and cross-selling since Google Images was created . This service offers more than just photos of Versace, Jennifer Lopez, and the dress that “broke the Internet.” Users increasingly use it to find inspiration, get answers to questions, and choose products and services. Statistics confirm this: from 2016 to 2018, image search frequency increased by more than 60% on mobile devices.
The right combination of text and images can produce amazing results. In 2021, the experiment with search visualization will continue, giving marketers and advertisers new opportunities for development in the era of visual content.
Data-driven marketing
Marketers will increasingly use sault data machine learning and automation to achieve their business goals. While rules-based marketing campaigns have delivered strong results in the past, their effectiveness is declining in today’s world. And consumers are becoming accustomed to having advertising messages tailored to their individual needs.
Advertisers who apply machine learning algorithms to their own data can fine-tune their bidding strategies using predictive models. This allows them to drive conversions with the highest value, thereby increasing their return on ad spend and revenue.