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Rule Number 1: Use Standardized Tagging

In the political world, more and more people are talking about the idea of data tags. These tags are little pieces of information that fill out what you know about a person. One tag might be age. One might be party affiliation. Another might be most important issue facing the United States today, etc. These little bits of information, when analyzed and utilized effectively, can lend extreme power to a campaign.

This, however, begs the question: What is required to effectively utilize a data tagging system? There are many ways to effectively utilize data tags, but they all are based on one overarching principle. That principle is standardization. You must have a standardized tag that means one thing.

If you want to use any tagging system effectively, your primary focus should be standardization.  This is because the primary purpose for data tagging is so you can easily categorize groups of individuals at a glance. Consider this example: You want to find out how many people in your constituency are primarily concerned with taxes. Naturally, since you have data tags on your voters, you search for the tag “taxes.”  However, people entering the data have used all kinds of different tags for the issue of taxes.  Some have used “lower taxes,” “small business tax breaks,” or just “tax breaks.”  You are now either missing significant portions of your constituency, or you are being inefficient by having to search four different terms.

Having said this, there is nothing wrong with the tag, “lower taxes,” for example. Think of your tagging system as a very narrow search term. Will you ever want to send this person a mailer about what you plan to do with taxes generally? Then use the tag “taxes.”  Do you want to send this person information about how you are specifically going to lighten taxes on small businesses? Use “small business tax breaks” also. There is absolutely no reason why you shouldn’t have more than one tag about an individual topic, but make sure that you cover all your bases.

Think of data tags like hashtags on Twitter. You can put multiple hashtags in one tweet about a single topic. All that means is that your tweet will turn up in a few different searches. But if you want to search for all the tweets regarding a particular conference, for example, wouldn’t it be nice if that conference had one standard hashtag? No one searches all four random hashtags that people come up with for events. Standardization is key to any tagging system.