“The number one benefit of information technology is that it empowers people to do what they want to do. It lets people be creative. It lets them be productive. It lets people learn things they didn’t think they could learn before, and so in a sense it is all about potential“Steve Balmer
Believe it or not, 2019 is almost over. As you think through your marketing and customer communication strategies for the coming year, personalization is undoubtedly top of mind for every customer. According to one annual survey, 89% of marketers believe their prospects and customers expect a more personalized experience.
A personalization strategy is only as good as the technology powering it. So whether you’re a customization professional or you’re just beginning to explore its potential, you need the right technology and underlying platform to execute an effective personalization program.
Here are the few ways in which technology is being used to create tailor-made, personalized experiences:
Product Recommendations for Up-selling and Cross-selling
E-commerce companies deliver tremendous value to their users via personalization. A notable example is the related product recommendations, popularized in 2003 by Amazon. In this case, a user viewing a detailed product page additionally sees the products similar (cross-sell) or complementary (up-sell) to this product.
Personalized E-commerce Search
In this case, a user types a query and gets a ranked list of products relevant for what they put in. They are personalized for the users. For example, if during the same session a user visited a brand elsewhere on the site, the search engine can re-rank the results and feature products coming from the user preferred brand, or factor this information into deciding which sponsored result is most likely to be useful to the user.
Netflix is perhaps the most famous personalization and recommendation engine. However, almost any other media company could benefit from such personalization and matching technology. For the users, the experience is very similar to the ‘Related Products’ recommendations. The only difference is that here instead of products, the service will feature related content such as movies, images, news articles.
Google and its search algorithms were one of the first to implement customization when it came to search results. Today, we can see personalized search suggestions based on any location. For instance, if we search for ‘hotels for executives’, the Promoted Result shown at the top of the search page does feature a hotel that is supposed to be for executives, rather than just the highest bidding ad.
It is worth noticing that the results are personalized even though the user isn’t identified. However, the results would have been much more relevant had we done this. It is likely that the website would have shown the hotels based on past travel history, rating, and other inferred preferences.
The power of a social network comes from the network effect and the connectivity of its members. Therefore, intelligent social networks such as Facebook, Pinterest, Twitter, LinkedIn, etc. invest serious R&D efforts to increase the connectivity of the social graph. The ‘People you may know’ (LinkedIn) or ‘Who to follow’ (Twitter) suggestions are great examples of this functionality as they facilitate more and more relevant connections between their users.
As you evaluate your personalization technology needs for the next year, keep this list in mind. These are the solutions that offer a single unified platform, in-depth behavioral data, omnichannel capabilities, customizable machine learning algorithms, and integrated and comprehensive testing. These are all the successful personalization platforms where technology is being used.
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