Effective frequency, by advertising industry definition, is the number of times a person is exposed to an advertising message before a response is made and before exposure is considered wasteful.

In his 1965 ‘The Impact of Television Advertising: Learning Without Involvement” Herbert Krugman declared a ‘three hit theory’ - that there are only three levels of frequency exposure in psychological terms: Curiosity, recognition and decision.

Having learned the hard way by running thousands of campaigns, that there are diminishing returns beyond the first impression, finding the optimal frequency of an ad, and therefore its maximum efficiency, is pretty much the Holy Grail for media planners.

As an industry we know that repeated exposure to ads, specifically at key points in the purchase cycle can positively change consumer awareness and attitudes towards a brand. Over exposure however, can create negative sentiment.

Ultimately effective frequency is affected by a number of factors:

· How difficult the audience is to reach
· How established is the brand
· How complicated is the message
· Whether the market is already saturated
· Nature and format of creative message

It’s also important to note that increasing frequency, increases the budget, but if care is taken to identify the target consumer before any ad exposure, then waste may be reduced and it can restabilise budget levels.

Frequency vs. brand lift

Using data collected from over 50 campaigns across the UK, Ireland, US, Canada and Australia, Qriously tracked the number of impressions required to deliver positive attitudinal shifts across a variety of metrics, from awareness to intent.

What the results showed was that with frequency levels between 15-25 generating the highest levels of response, it goes against Krugman’s ageing theory. While many will initially be concerned about over exposure to consumers it’s important to highlight mobile’s unique characteristics that lend it to unorthodox levels of exposure to generate results.

The modest size of mobile ad formats in relation to other formats in integrated campaigns, mean that the impact is smaller and so greater frequency is required to make an impression on the consumer.
Secondly, the data, which compares screen size and CTR, suggests that larger screen size generally delivers higher impact, something relatively straightforward. This means that we can expect that when advertising makes its debut on wearable devices, that frequency levels on these devices will need to be much higher to reach the desired campaign metrics.

To make a substantial impact with mobile advertising, frequency levels must be increased beyond Krugman’s standard model. Across the campaign data, we can typically see the best results, whether brand or performance led, at frequencies between 15-20 impressions. Low consideration product categories, like insurance for example, require even higher levels, typically 20-30 impressions to move the needle in a positive direction. How do Click Through Rates (CTR) compare to these frequencies though?

The research collected helps to dispel the idea that high frequency levels on mobile leads to overexposure. Considering the stable long tail, CTR doesn’t fall substantially below normative values, even at high frequencies. This builds on the hypothesis that consumers will continue to engage with mobile ads at what planners might traditionally consider to be extreme frequency levels.

The majority of campaigns, including those traded programmatically, are usually capped somewhere between three and seven impressions per consumer. From this data, applying Krugman’s legacy approach to mobile, excludes the opportunity to convert a substantial long tail of consumers who require greater exposure.

Unless a consumer is in market, no amount of impressions will help produce the desired effect. Brands can help improve the likelihood of this by finding ‘hand raisers’. Before any ad exposure, simply ask consumers within the same ad unit, if they’re in market for your brand category. This all but guarantees the impression will be served to the correct target every time and ensures the optimal number of impressions are delivered at just the right time in the purchase cycle.

Does brand category influence optimal frequency

It’s widely accepted that consumers respond to and interact with, ads for different brand categories with predictable levels of varying interest. Finance for example is typically low, especially in sub categories like insurance. Entertainment on the other hand is generally a high interest category. Variation between categories means that it’s likely there’s an optimal level of frequency that drives the highest mean CTR, per brand category.

The common thread between them is the fact the sales decision cycle is longer than other categories in the study, therefore giving more opportunity to attract clicks.

Categories with long sales cycles typically have more opportunities to engage consumers found in classically defined mobile context e.g. downtime while commuting and retargeting ensures they click more frequently.

For many years, digital media planners have blindly followed Krugman’s model and ignored a crucial moving variable; screens have become smaller and more personal.

We know that ad impacts behave very differently on mobile and if marketers are serious about getting the best from what is the fastest growing medium on the planet, then frequency levels and caps should be revisited as a matter of urgency. This of course has even more serious consequences for agencies using programmatic trading as they may very well be running sub-optimal campaigns at mass-scale.

The next five years will see the internet deliver more advertising to consumers through a multitude of novel touch points. Thermostats and smoke alarms are just the beginning and soon it will be difficult to buy a domestic product that isn’t ‘smart’. Our coffee makers, washing machines, ever our freezers will be connected on Wi-Fi and will contain a multitude of sensors, delivering data, including advertising, to our smartphones and screens around the house. Caffeinated, cleanly clothed and well-fed planners may very well need to rethink their frequency assumptions.


By Chris Bourke, Commercial Director EMEA at Qriously. 

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