Big brands and corporations are long past the point of realizing that they need to invest in personalization and personalized campaigns. Considering the fact that society has moved on from turning into cable TV to Netflix and Spotify instead of the radio, the public craves curated content that largely fits their interests.
Nearly all consumers have reported they’re a lot more likely to make purchases from companies that provide their audiences with customized recommendations and offers, while over half stated that if the content is not personalized, they might not make a purchase.
All the research has shown brands have to create curated and personalized experiences if they want the consumers to keep coming back – whether that means suggesting the next show they’re going to enjoy or automatically showing their order history when they look at their account.
Additionally, with the help of artificial intelligence (AI), brands have a much easier time making relevant recommendations to their consumers, and yet, plenty of brands still have trouble following the data they’re shown.
One of the biggest struggles for companies is toeing the line between being creepily accurate and giving useful recommendations. With consumers leaving trails of data wherever they go online, brands can use this information to better understand how to personalize the content they provide to the target audiences.
In the best-case scenario, targeted ads are made to catch the buyer during the right mindset while they’re scrolling down their social media feeds and then convert their attention into making a purchase. However, plenty of people have expressed their unease of how they talked to someone about something they’re planning on getting, and as soon as they open up their social media feeds, they see a targeted ad specifically for that product, without ever looking it up.
To avoid making customers uncomfortable with personalized ads, companies should be transparent about the type of information they’re collecting and have people opt to give up a certain portion of their personal information and avoid using data gathered through other means.
After successfully walking that narrow path, companies have another challenge, and that’s distributing new and relevant content to the consumers.
To make all content useful for the consumers, the products or services recommendations should be able to identify similar yet different products from their previous purchases or interests that the consumers will be interested in. And to successfully do this, companies should take advantage of artificial intelligence technologies, such as machine learning, visual recognition, or natural language processing (NLP).
Furthermore, brands should also be listening to the consumers, especially things that they’re constantly interested in, such as the shows they watch or the products they regularly buy. To further allow for personalization, the brand can introduce a feature that can allow the consumers to weigh in whether the recommendations fit their interests or not. Through effective personalization, brands can grow, boost their bottom line, and encourage customer loyalty.
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