It’s getting harder and harder to put relevant online advertising in front of people. According to a recent Yahoo study, less than forty percent of online users see ads as relevant to them. So how do you solve this?
Social sites can create a feed that users want to see. If you want this kind of personalization for your advertising, then you need information and insights that tie your ad decisions to real data. This could be profile based data pulled from your customer database or behavior based data that looks at how people interact with you. You can social media data when someone uses Facebook or Google to sign into your website or sign up for a promotion. This is very powerful because it gives you an even bigger picture of a person’s preferences by pulling data from those sites.
That’s all perfect for making an immediate connection with your advertising, but what if you wanted to take it a step further and predict which type of messaging users will respond to? You can achieve this by adding the layer of automated learning to the user profile system. You can not only track the effectiveness of your advertising but by pulling this data back to the user profile, you can have the system access it to get smarter more stylish patterns.
What if you were able to go beyond sharper profiles and got feedback from the audience? Collaborative marketing actively involves the consumer in the conversation. Like personalized advertising, collaborative marketing can reach the consumer as a person, not a demographic. Techniques for collaborative marketing can involve getting customer feedback or engaging them in an active social media strategy to keep the conversation and consumer interest going on. This type of engagement helps qualify leads that can drive interested prospects deeper through the sales funnel.