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Published April 19, 2018
We will now demonstrate how identity matching can help you make more relevant offers to a customer on the web channel.
U+ is a retail bank. The bank uses its corporate website as one of its marketing and advertising channels.
Banner ads and side-bar ads are used to present marketing content to prospects and customers.
Troy is a customer of U+ Bank. Today he has not yet logged-in to the website. He’s browsing as an anonymous user. At this moment, a generic promotional message is displayed at the top of the page. The generic message is the offer the bank displays when the identity of the visitor is unknown. Troy is visiting the web site to find out if the bank offers credit cards with better benefits than the one he currently has. So he visits the credit card section to check the available options.
Based on the context of the page he is visiting, a generic credit card offer is displayed in the side bar. However, it is not necessarily the one he will be most interested in or mostly likely to accept.
Troy is not persuaded by the available options shown on the promotional message. He now wants to log in to his account to carry out some routine transactions.
On the index page, notice that the credit card offer is now displayed instead of the generic offer that was displayed earlier.
This new offer is based on Troy’s recent anonymous visit to the credit card section of the website.
Once Troy is logged in, his identity is known.
The browsing information captured when he was an anonymous visitor is now combined with the demographic and other information known about him by the bank. This combined information is used to recommend an offer that is more relevant to Troy’s situation. This time Troy is curious to find out more and clicks on the promotional message. Through the use of identity matching, the offer impression turned into an offer click-through. And it is now likely to become an offer conversion for U+ Bank.
To summarize, identity matching can suggest the best offer for a website visitor at every step of their journey. When the visitor is identified as a known customer, the combined information is used to make more relevant recommendations.
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