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Tunnl | Products | Media Optimization | Cost

The Cost of Media Optimization: An Explanation of Smart TV Targeting

August 10th, 2021 | 4 min. read

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Since you’re reading this, you’ve probably already asked yourself, "How much does media optimization cost?"  It’s a reasonable one: data is costly.

The infrastructure to host and manage TV data is elaborate. Teaching an agency to use it well can be difficult. 

We know these things because Tunnl offered the first local media optimization solution for campaigns and causes like yours. The reality, however, is this: even though Tunnl pioneered this space, there are other options ranging in price and quality for you to consider.

What drives costs, and is it worth the expense?

By the end of this article, you’ll at least have a framework to consider this question — if not the answer for your upcoming campaign.

What drives the cost of media optimization?

As with any product, the cost of goods sold is the driver of the total cost of the project. In this case, those costs come in the form of data.

Most media optimization solutions rely on “observed media consumption data” as the primary input to a media optimization solution. This is the type of data created by:

  • Set-top boxes
  • Smart TVs
  • Other connected devices
  • TV guides

Depending on your provider, this data is used to produce a “ranker” of top-performing TV inventory for your media buyer to prioritize, or to generate “custom TV ratings.” These are projections of how likely an audience is to be watching certain programs on TV.

What would make media optimization cheaper?

The quickest path to making media optimization solutions cheaper is to use less data to drive the product. Less data means fewer costs, meaning cheaper prices.

How some media optimization solutions use less data to keep prices low:

In most scenarios, less data means foregoing local market measurement for a national panel that can be modeled down to the local level. In layman’s terms, this means looking at how an audience nationally consumes content and applying it to the local media markets like Des Moines or Tallahassee.

In other scenarios, less data means working with a single data provider. This can result in implicit biases in the data source itself that would be corrected if other data was included. For example, some data sets, like one from a prominent TV guide provider, skew older, whiter, wealthier, and more urban. This makes it unreliable for measuring how younger, more diverse audiences consume content.

In the case of the cheapest media optimization solutions, both of these paths are taken — they single-source their data nationally and model it down to the local level when necessary.

How Tunnl uses automation and scale to reduce prices:

At Tunnl, we have taken a different approach to reduce costs. We continue to multi-source our data and maintain a large enough panel to match local audiences to local viewership data. This eliminates the need to model down national data to the local level. We do this because we have seen time and again how viewership patterns vary by audience and by market. We do not believe in sacrificing these insights for our clients.

Cost reductions, then, come in the form of continued investment in:

  • automation
  • improved data warehousing and processing
  • leveraging the scale of our business with our data providers

This approach has produced real results. Since 2014, the average price of our media optimization products has dropped by over 30%.

What would make media optimization more expensive?

The cost of media optimization can be driven up by two factors: 

  1. The amount of data required
  2. Whether you will leverage custom or off-the-shelf solutions.

What is the geographic footprint of your campaign?

The amount of data required is a fairly straightforward consideration. Are you running a campaign in a single media market? A single state? Several states? Or several media markets across several states?

The larger the footprint of your campaign, the more data we will have to deploy to accurately measure the viewership behaviors of your audiences in each of those markets. This drives up our costs and makes it more expensive for you.

Do you need a custom solution, or will prebuilt audiences work for you?

Choosing between custom or standard, off-the-shelf solutions comes down to your budget and strategic imperatives.

Standard Audiences

Most of our clients use our standard audiences. They are pre-matched into Tunnl's viewership data for an always-on ratings solution. This data is readily available for you but is also available to any other advertiser who would like to purchase access to the data. This is why it is cheaper to use our prebuilt, standard audiences as opposed to custom ones.

Custom Audiences

Media optimization gets more expensive when clients use custom audiences. These audiences are unique to you, and therefore require a unique match process and ratings projection for your project only. 

In most cases, Tunnl is the one building these custom audiences for our clients. Although, sometimes clients bring audiences they already have for us to plug into our process. In either instance, building a unique process and custom matching audiences drives up our costs - making it more expensive for you.

Okay, so how much will media optimization cost my campaign?

Great question. Here’s what you can expect:

  • For optimization in a single media market, prices range from $30,000 - $40,000.
  • For optimization in most states, prices range from $125,000-$150,000.
  • For an optimization project that covers several states, we can streamline processing costs and reduce the cost-per-state.

 

Do you have questions? Want to get started? Let's talk. Email us at sales@tunnldata.com.