The media environment is saturated. With so many ways to reach consumers, it’s hard to stay organized in a scattered ecosystem but remember: approaching your marketing strategy with a silo approach will only hurt your campaigns this year. Why keep your social, search and display data in separate buckets? All channels for your paid media campaigns share rich audience data— apply your insight from one platform to another, with cross-channel strategies. Instead of spending months on developing an audience targeting list, create a targeting list using existing conversion data. With new machine learning tools, you don’t need to take on the laborious task of analyzing every touchpoint of your audience. Here are 3 ways to implement these strategies into your paid media campaigns:
- Use the data extracted from your social and content marketing campaigns in harmony with your paid search campaigns.
Let’s say your Facebook campaign performs well with a certain demographic. You can apply this to your search and display campaigns, and see if it produces the same results. Maybe you notice a certain image and ad copy generates high volume conversions for your Facebook ad campaigns. If your paid search/display campaigns underperforming, try using the same creative assets and copy from your Facebook campaign to see if it improves performance. Simultaneously, running your Facebook ads with other campaigns can augment your paid search performance, and as a result, decrease your cost per acquisition (CPA). Using your Facebook ads as your paid search/display ads can increase search volume, as well as reinforce your brand in SERPs (search engine results page).
- Control for different parameters within your campaign by use of machine learning.
There are many different parameters within ad targeting groups: geolocation, processing system, device, income, gender, and so much more. You can control for these parameters in each channel and see if certain targeting groups convert more frequently than others. Completing this manually is a very tedious process. But marketers don’t need to do this: marketing automation tools powered by machine learning can control every data touch point you can think of. This is also another opportunity to apply insight you find in one channel to another. You might find that a certain target group may be more likely to purchase something they see on Facebook as opposed to a YouTube ad. Track and measure your cross-channel conversions to establish which blend of marketing renders optimal campaign performance.
- Establish Brand Awareness on Facebook. Then, Retarget!
Facebook as an ad platform is great for developing retargeting lists. When building your Facebook campaign, pixel the corresponding landing page and set up your Adwords audience to initiate remarketing once your remarketing list has been finalized. Determine the high volume keywords from your search campaign, or search query reports and incorporate them into your cross-channel ad copy. Use the process to target your audience for your retargeting campaign: Model off existing conversions. With the Facebook, Analytics and Adwords data you’ve incurred from new conversions, you can retarget an audience identical to your new customers. If someone clicked on your paid search ad on Google, you can retarget this user on Facebook. That way, you aren’t annoying them with another paid search ad, but catching them with a creative ad on a different platform.
A cross-channel campaign targets individuals as they progress through the engagement funnel, which means every channel should have consistent messaging. Consider how each channel is used and keep a constant theme, but always adapt each graphics and ad copy to the respective content style of each channel. By revamping your campaign strategy with this new marketing funnel, you’ll see better results in a shorter duration of time.
Also published on Medium.