Ask any marketer, picking the best channels to reach and motivate customers is hard. Worse, if the CMO bets wrong, she's out of the job in 18 months.
While media planning, creating content, placing buys, and measuring is vital, there's something even more crucial: getting around that cycle quickly. That gives marketers a chance to adjust spend and improve results—more kicks at the can.
But making the connection between marketing campaigns and results—quantifying impact—is a struggle. A combined total of 65% of marketing executives polled for the CMO Survey in early 2020 said they hadn't been able to measure the impact (21.2%), or that they had a "good sense" of impact, but no concrete numbers (43.8%).
Media planning in the dark?
How can you allocate a media spend objectively to produce the best results if you can't measure its impact? There are two main hurdles:
1. Getting the information needed to decide where to spend dollars across different geographies, channels, and date/time periods. Answers to questions like:
-
Which TV stations were over/under-invested?
-
Which digital buys led to the largest incremental sales increase?
-
What geographies responded best to OOH investments?
-
Which messages prompted in-store vs. online sales?
-
What's more productive—a Mothers' Day campaign or back-to-school?
2. Getting that information fast enough to be able to adjust spending if a campaign isn't performing
Can modeling help?
Yes, models help marketers make educated guesses about which types of media buys will generate the best results, based on past performance. The most widely used are media mix modeling (MMM) and digital attribution modeling.
MMM pulls together two to three years of data covering offline (print, direct mail, traditional TV and radio) and online (email, social, mobile) channels. It also reports offline and online sales and factors in outside influences like seasonality and events. It calls out high-level insights and trends good for setting a strategic direction.
But it's not built to be updated as a campaign plays out. And it doesn't dig into information about, for example, which particular TV spot was most effective.
Digital attribution, on the other hand, follows consumer activity online, i.e., clicks, time spent on a website, purchases, etc. It spits out that data within seven to nine days, so tactics and spend can be adjusted quickly. It also produces granular insights, like which ad size/placement on the page performed best.
But it can't factor in outside events/influences and doesn't look at offline media or sales. More importantly, it can’t get access to all consumer behaviors online because of proprietary online advertising platforms, the so-called walled gardens, of Amazon, Google, and Facebook.
So with MMM, marketers can make strategic online and offline changes annually, and with digital attribution, they can make tactical online-only changes every week or so.
Is it possible to pull more levers more often?
Yes, marketers can make more adjustments by using strategies to get them around the media cycle quicker and drive stronger returns. Here are the key ones.
Step up research, analytics, and testing.
Build out a system of measurement tools and techniques that give you the answers you need, when you need them. This is usually not one monolithic model but rather a series of hierarchical ones. Then test. If you aren't completely confident in what the models are saying, vary things. Use a bold series of tests to either support shifts in the plan or reinforce your original decisions. Lastly, research—ask customers and prospects what they're thinking. Focused, timely research helps you understand attitudes and, to some extent, behaviors, that will help shape a strong media plan.
Don't settle for a national plan & reporting.
National media plans are easier to execute but don't do a good job of factoring in local behaviors, characteristics, and events (weather, celebrations, etc.) These considerations are especially important for personalization, social, and mobile media. It's also harder to get fast, usable data by DMA or sub-DMA when the starting framework is a national media buy. And when you plan by DMA and sub-DMA, it's easier and less expensive to experiment and test, as described.
Re-unite creative / production with media services
Digital disruption led to a crop of specialized media buying-only agencies. Marketers started using them because of their expertise, while creative was handled by someone else. But separating media planning from creative strategy/production adds another layer to an already complex process. That layer means more time. If marketers can bring creative and content production into the media planning and buying cycle, they automatically save time. They can then out-pace everyone who can't do that.
Integrating creative strategy and content production into the media planning/execution cycle, using better analytics, and keeping a local focus offer the best way to out-market the competition.
via https://www.aiupnow.com
, Khareem Sudlow