Optimizing Your Multichannel Media Mix

First, the good news: Marketers typically have an abundance of historical campaign data. Marketing partners gather information from direct programs, media planners capture mass marketing presence, and sales knows who bought and when. Information about the customer is everywhere – information that takes time, effort and expense to capture.

And now for the bad news: Your data isn’t being used effectively if it doesn’t help you determine how you should allocate your cross-channel media spend. In fact, when it comes to media placement, most enterprises simply replicate previous plans based on gut feel and qualitative factors, including personal preferences and beliefs.

Sound familiar? If so, you are not alone.

Fortunately, it is possible to use your data to optimize your media mix allocation strategy and quantify the impact of your spend for each media channel, whether it’s direct mail, print, TV, radio, interactive or any other channel. Better yet, media mix modeling is a continuous process – and can be done on a monthly basis or even every two weeks.

Optimizing your media mix can realize powerful marketing program ROI of 20% or higher. For example, one financial services company was able to secure significantly higher response rates from a direct mail campaign by synchronizing the delivery dates with its TV campaign. In some cases, other marketers were able to drive higher ROI by shifting their media spend from TV to direct mail and other direct channels.

While you need complete integration of all internal and external information to be effective, all marketers can learn from these practices. In planning your next multichannel marketing program, consider the following:

  • Competitor data: What are you spending on your marketing vis-a-vis your competitors? Competitor spend data is available for most industries and should be regarded as a critical input into the media planning and optimization process. Media effectiveness directly correlates to a merchant’s share of voice in the marketplace.
  • Response data: How far can you drill down into your data? Data should be provided at the lowest level of granularity – by week, by campaign, by offer, by creative. Other performance metrics, such as revenue or profit, can also be modeled if this type of data is available.
  • Historical media spend data: Most companies have this information, but lack easy access to it. The data needs to be provided at a weekly level, at an absolute minimum, and should be combined into a single data infrastructure with your other data.
  • Additional data: You must ensure that you capture plenty of detail about your specific media placements and program rollouts by region. You will also need to track when changes to your offer/creative/campaigns were made.

In addition to media allocation, your data can show how media efforts interact, indicate seasonal differences and determine your share of voice relative to the competition. With the right combination of data and analysis, it’s possible to measure the effectiveness of your media allocation on a monthly, weekly or even daily basis. So try throwing your assumptions and old patterns aside and take a quantitative approach to media planning!

Ozgur Dogan is senior director of database marketing solutions for Lanham, MD-based database marking company Merkle.

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