Media + PR + Analytics

Why Reach and Frequency Don’t Matter in Digital Media

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Lindsay Ferris

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Almost anyone who’s worked in consumer marketing for more than, say, five years has probably evaluated a media plan and asked: “what’s the reach and frequency on that?”

That’s because we were all taught to evaluate a plan as a simple formula that described two things:

  • The percentage of consumers who are likely to see your ad (reach)
  • How many times each consumer would likely see your ad (frequency)

For better or worse, traditional media targeting is very inexact, so we need a methodology to help us compare one media plan to another, and this is the one we came up with.

The REACH part of the traditional media equation is pretty clear-cut, but let’s delve into the FREQUENCY part a little further.

Think about a typical consumer who is happily sitting on her couch watching her favorite program on TV:  The likelihood she’ll see an ad, drop the remote, get into her car and drive to the store to purchase toothpaste (for example) is virtually zero.

Frankly, the distance between the comfy couch and the grocery store is just too vast for us to expect that a simple ad exposure will drive purchase. So, FREQUENCY is important to plant the brand in her head so that when she does go to the grocery store five days later to buy toothpaste, she remembers something about the brand and is more likely to purchase it.

But what about digital media?

Digital media planning works quite differently. Let’s use display ads (also known as banner ads) as an example.

First, let’s clear up a common misperception about banner ads: People often think of them as “little print ads.”  They’re not. First of all, by themselves, banner ads are just not very good at building awareness.

Side note: if you want to build brand awareness, you really need to consider adding something like print, TV or outdoor to your plan to provide a rich media mix.

If we’re comparing banners to more familiar media forms, they’re really more like a direct mail piece – which, for anyone who’s ever received a home equity line solicitation just after purchasing a home knows, is a very precisely targeted message. And as you’ve also experienced, it’s designed to entice you to “act now!”

The direct marketing analogy is also useful when we think about other factors like testing and response rates. As with direct marketing, click through rates for a simple display ad are typically in the 0.08-0.10% range, depending on the partner’s platform, the targeting and the message (rich display ads can garner higher rates).

Also, as with direct marketing vehicles, we can use A/B testing to learn which version of a message gets the BEST response rate. That said, there are significant differences between display advertising and direct marketing, namely: The data we use to target consumers, and how fast we can do it.

How digital media spurs action

OK, so let’s jump back to our consumer on the couch. During the commercial break (if she doesn’t happen to skip through it), she sees an ad for a new brand of baby wipes.

Even if she does have a 3-month-old, she’s not likely to jump off the couch and head to the store for baby wipes because she saw an ad. But, as we all know, she’ll more than likely have her phone in her hand.

Now, let’s just say we serve her an ad promoting a “subscription” for baby wipes at a discounted rate with free shipping – is she likely to buy? Well, if through the miracle of “big data” we know that she’s been buying diapers and formula, and she’s liked a diaper brand’s Facebook posts three times in the last three weeks, then the answer is YES, she is more likely to buy. Especially if she can do so with the click of a button, without ever leaving the couch.

Through the aforementioned miracle of “big data” we can use digital media planning techniques to target consumers that are much more sophisticated and relevant than typical inputs for a traditional media plan. Here we’re talking about factors like gender, age and household income.

To build a digital target consumer profile, we typically compile several different “targeting layers” to create a tight definition of our likely purchaser.

For our baby wipes buyer, the targeting layers might look like this:

  • She lives within 40 miles of a major metro area

    (We can’t ship free to remote cabins in the woods. Sorry Alaskan Bush People.)

  • She “liked” a diaper brand’s social post

  • She purchased a competing brand of wipes in the past 30 days

  • She also purchased diapers and diaper cream – online

  • She buys natural and organic products (Did we mention the wipes are compostable?)

What happens next depends on algorithms: Once our creative goes live, algorithms will seek out ONLY the consumers who fit the multi-variate profile above, targeting them in optimal online places, at optimal times.

Always be optimizing

Over time, we may see that past purchases of natural and organic products produce low click-through or engagement rates. But “liking” diaper brands on social media and purchasing diapers and diaper cream produce high engagement rates. So, the algorithm will adjust to find other consumers with other targeting layers who closely match the profile of the consumers who click.

Additionally, the algorithm will tell the real humans monitoring this campaign the average number of interactions a consumer had with our touch points before buying, how long the process took, what else they were interested in, etc. This information helps optimize the overall digital mix.

Then, the algorithm keeps adjusting to obtain the best engagement rates. Creative testing adds another layer of fine-tuning to the plan, but we’ll save that discussion for another blog post.

The entire digital media planning process is very dynamic: The algorithm optimizes, creative is revised, impression weights are tweaked and actual people keep a close watch on the process to look for insights in the data.

Because in the end, the goal is to reach ONLY the people who are likely to engage or buy, NOT to reach a universe of people who we want to make aware of our brand.

Bringing it all together

OK, let’s recap what we’ve learned so far:

  1. Display ads (or banner ads) are not little print ads (designed to generate brand awareness). They are direct response ads (designed to generate action).
  2. Digital media is not planned based on demographics alone. It is planned based on demographics plus behavioral characteristics.
  3. Traditional media (TV, print, radio, outdoor, etc.) is designed to reach AS MANY consumers in a given universe as possible, but display media is designed to reach ONLY very specific individuals, and no one else.

Now that we understand how effectively big data can target people down to the individual level, we can address the question of why “REACH and FREQUENCY” are not useful criteria when evaluating digital media plans.

If you’ve read this far, you’ve probably figured out why REACH is an irrelevant measure when it comes to digital media. Simply put, we don’t want to reach as many people as possible. We want to limit reach to only the intended audience.

As for FREQUENCY, our goal is not to imprint our brand into consumers’ brains (that’s the job of awareness-building media), our goal is to get consumers to engage. And getting consumers to engage is not a function of repeated exposures, it’s a function of delivering the right exposures and finding consumers when they’re ready to take action.

If they’re not ready to take action (maybe their child is out of diapers!), more exposures are not likely to change that. Instead, our impressions are better used to find other consumers who are ready to take action.

The next time you’re evaluating a display media plan, pay close attention to the targeting layers recommended within the plan. That’s where success lies.

And if it’s reach and frequency you seek, look seriously at adding other tactics to your plan.

Lindsay Ferris

Alter ego: Liz Lemon.

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