Paid Social Media Hack .7: Increase Commercial Intent Using In-Market Segments Social media advertising presents amazing opportunities for advertisers due to the enormous size of their audiences, but these platforms lack the kind of commercial intent offered by search ads. So what do we do? We narrow the field to users who are ready to buy by using in-market segments. Facebook partners with data brokers to provide advertisers with detailed information on purchase histories of its users. This means that marketers can target increasingly granular audiences based on the things they’ve bought, places they’ve gone, and virtually anything else tied to their credit card statements.
This allows us to create
highly specific audience segments. This is an example of a segment I use to advertise WordStream’s services on Facebook. In this case, I’m targeting people who’ve bought business marketing software: Paid social media Facebook custom audience This gives me a potential Facebook audience of 6.1 million people! You can see how Facebook has partnered with Epsilon to access this kind of purchasing data, as well as a description of the audience segment and the source of the data. You can do something similar in Twitter, too. They actually use the same audience data as Facebook! Here’s another example, this time for a coffee retailer that’s going after people who’ve bought coffee as part of the behavioral profile data owned by Datalogix accessed by japan phone number Twitter: Paid social media Twitter user behavior targeting You can target custom audiences as broad or as narrow as you like.
Remember, though
that the more specific you get, the smaller the audience is likely to be. Paid Social Media Hack .6: Demographic Targeting Similar to custom audiences, you can (and should) be targeting custom audiences based on demographic data. AdWords advertisers are no strangers to demographic targeting options, but Twitter and Facebook go a little deeper iran phone number than Google does (for now), offering advertisers the choice to target users based on a whole bunch of different data points. You can target users based on level of education, household size, income, “life events” like getting married or the birth of your first kid, even net worth.
