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Television Household Data: Buyer Info or Demographic?

July 28th, 2015   ||    by Jennifer Goforth Gregory

As programmatic TV buying becomes more prevalent and the amount of television household data available increases, the question on advertisers’ minds is not whether to use automated options, but rather “which programmatic buying approach is the best strategy?” One strategy is to base purchasing decisions on viewers’ demographic data, while another approach is to use their buying behavior as the cornerstone.

Using Household and Demographic Data

By basing programmatic buying decisions on television household data, you are likely to reach a wider audience than when you target buying behavior. This type of data and approach is especially beneficial to local broadcast stations, which can now use household data along with the traditional demographic data to maximize their inventory. By further targeting specific demographics, stations can uncover the value in spots that are outside of the coveted primetime slots.

Key data points in this category include:

  • Geographical location
  • Age
  • Number of people in household
  • Income
  • Homeowner or renter

These data points are useful for targeting broader audiences or using multiple household/demographic data points to reach a more specific group. For example, a company selling high-end kitchen appliances may use this type of data to buy a spot with a high concentration of individuals over 35 years old that own a home and have an annual income over $100,000. One major benefit to utilizing these basic data points is that demographic information does not typically change quickly, making it easier to establish a solid audience of target customers.

Using Buying Behavior Data

When you glean television household data from current buying behavior, you create a more accurate representation of the actual interests and needs of a specific group. This data will help you narrow down the focus for your advertising and identify more niche spots. These spots are usually more effective than premium spots due to the large concentration of potential customers. Advertisers using this data may learn that their target customer is more likely to tune into a mid-morning spot than the highly priced primetime spot. Spending can be reallocated to programs where the niche consumer is tuned in, which uses their advertising dollars more efficiently.

Some categories of buying behavior you should focus on when performing data analyses are:

  • Companies followed on social media
  • Amount spent on certain products
  • Potential interest in buying specific products based on searches

This data is typically mined from social media, but can also come from more concrete sources on actual purchases. Buying behavior data is also especially useful when combined with predictive analytics to determine what a customer is likely to do in the future based on past purchase and online behavior.

By accessing key data points and mining demographic information, you can adjust your strategy to better reach your target audience and increase the overall efficacy of your ad campaign.

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