5 Advertising Game Changers

June 5, 2014

I speak frequently at advertising industry events, and probably the single most frequent question I get is this:

 “What are the biggest game changers in advertising that you believe will permanently change the way that CMO’s and their Marketing organization’s operate in the future?”

From conversations with many CMO’s, Media Heads, Agency Research Heads, etc., I see 5 big trends that will forever change advertising as we’ve known it for the past 50 years.


 5 Advertising Game Changers

1.  Content:  More Than a Pipeline – Advertisers used to think of media plans as analogous to a “pipeline.” Advertisers produced ads, and publishers provided content, which acted as a “pipe” to pump the message to end consumers. This is an overly simplistic view of media plans; a better analogy would be content as a “trampoline,” where content provides “bounce” to advertising effectiveness.

It does so in two ways: attentiveness and context. When viewers pay more attention to content, they also tend to pay more attention to the ads in that content. So, content or programs which have higher attentiveness also drive high ad performance. Similarly, program context also impacts ad performance. Benefit consistency (sports clothes in sports programs; weight loss foods in weight loss programs, etc.) help ads outperform the same ads in content with less relevant context.

Attentiveness and context are not new concepts. But measurement of them is, and advertisers are increasingly taking advantage of this knowledge.

2.  Media Planning: More than Audiences – All of the media agencies are being asked for more from their clients—more cost savings, more foresight, more analytics, but more than anything—more brand and sales impact from their media plans. This means that traditional media planning is morphing from being mostly about audience and costs—e.g. reach, frequency, GRP’s and cost per 1000, to brand or sales impact.

This has two implications. First, agencies are beginning to incorporate impact based metrics into their media plans. Instead of GRP’s, there will be “effective GRP’s,” where brand or sales impact is factored in. Second, agencies and advertisers will begin to pre-test media plans. Instead of simply looking at audience and cost metrics, agencies and advertisers will begin using simulations to look at projected brand and sales impact as well.

3.  Real Time: More than After the Fact – Everything is moving digital, and one of the benefits of digital is measuring your advertising with granularity and speed.

Two examples: Currently, over 20% of display ads are auctioned thru Real Time Bidding DSP/SSP platforms. Buying audiences in real time is going to get even bigger and more granular, as DSP/SSP platforms become more sophisticated and are fueled by increasingly granular data sets.

And, audiences won’t just be bought in real time, they’ll also be bought for sales impact. Digital attribution modeling now employs daily regression modeling at the individual person level to measure sales impact by touchpoint, including by web site and placement. The move to real time is real, inexorable and now.

4.  Single Source:  More than Guesswork – Connecting—literally—the ads people are exposed to with the goods and services they buy—has always been deemed the holy grail. This “single source” data at the individual or household level is finally here—at scale, providing unparalleled insights into how advertising works.

Enabled by privacy protected loyalty and credit card buying data plus viewing panels and set top box viewing data, it will help agencies and advertisers understand which audiences most respond volumetrically to the advertising, which ads drive the most volume, which programs or web sites deliver the most lift, what role exposure frequency plays in driving sales, etc.

While still early in the adoption phase, single source is poised to finally provide extraordinary insight into how to improve advertising effectiveness.

5.  Audiences:  More than Demo’s – Digital audience buying is already focused on all kinds of characteristics that go well beyond basic demo’s. For example, re-targeting uses viewer browser shopping behavior to target future ads (I shopped for a bike on Web site X, so I see bike ads outside of site X in the days and weeks following).

The data sets used to buy audiences are getting richer and more granular. You can already buy digital audiences based on TV viewing behavior (e.g. buy digital audiences unlikely to have seen your TV advertising), offline buyer behavior (e.g. heavy category consumer who have not bought your brand), geography, etc.

The Game Changers Converge

If you’re feeling that these five game changers seem to overlap to some degree, you’d be right. While they are all different concepts, they are mutually reinforcing and, when taken together, are amplifying and accelerating changes to the advertising eco-system. For example, when advertisers launch a new campaign, within the first week they can:

  • Use single source to quantify how web site content impacts ad performance.
  • Measure this daily to get a read across all sites in their plan.
  • Use real time bidding to bid for the most volumetrically responsive sites.
  • Bid for audiences most likely to have not seen their TV ads to extend reach.
  • Leverage all of this learning in their next impact based media plan.

Where to start ? It sounds almost overwhelming. Well, you can always take Muhammad Ali’s sage advice: “it isn’t the mountains ahead to climb that wear you out, it’s the pebble in your shoe.” In other words, get started small and get started now !

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Neuroscience in Advertising: Making the :15 the New :30

August 5, 2013

The :15 second TV commercial has a lot in common with cubic zirconium—a cheaper and lower quality “look-alike” that is almost instantly recognizable by anyone as anything but the real thing.

Often treated as an afterthought by Marketers and Agencies alike, the :15 TV spot is usually just a cut down version of the :30, rarely copy tested, but assumed to be at least 50% as good as the :30 from which it’s derived.

But the truth is that most Marketers have no idea how good, or bad, their :15’s really are. It’s as if everyone just blindly assumes the best, without thinking about the worst. Fifteen second ads adhere to the same basic principles of success as :30’s, but just get much less attention.

An Improvement — Real Time :15 vs. :30 Optimization

Things have improved somewhat over the past few years. With the advent of real time TV ad effectiveness measurement, Marketers can now monitor the performance of their :30’s and :15’s on a weekly or bi-weekly basis, so they can understand relative differences in performance.

This enables you to see when your 15’s perform well enough to warrant moving out of your :30’s and into 100% focus on your :15’s. But all of this is after the fact. What’s really needed is better :15 design beforehand. But how?

Neuroscience & Copy Testing

Neuroscience has had any number of fits and starts over the past few years when applied to Marketing. But one area where there has been substantial and undeniable progress is in the area of copy testing. Possibly the most advanced technique uses EEG measures of brain activity to understand how viewers are responding to advertising. This approach uses EEG to identify and capture responses to brain stimuli in fractions of a second.

In particular, EEG based copy testing can measure three things extremely well:

  1. Attention – When and how much viewer attention is paid to an ad. This is key to knowing if someone even notices or pays attention to your ad in the first place.
  2. Memory – Whether a viewers memory is activated in response to viewing an ad. Without memory, it’s unlikely that an ad will influence much future behavior.
  3. Emotion – To what degree a viewer is drawn to or pulls away from the ad stimulus. Attention and memory are important, but so is positive emotional attraction.

Taken together, these three measures are key to effective ads. They relate directly to whether someone pays attention to the ad, whether the ad is stored in long term memory, and whether the ad elicits a positive emotional response.

Importantly, EEG based copy testing measures viewer’s brain waves in milliseconds throughout the commercial. Typically, a viewer’s brain waves looks like a series of peaks and valleys as the viewer responds to different parts of the commercial. These peaks and valleys correspond to the parts of the commercial that are most and least effective as measured by attention, memory and emotion.

The Optimal :15 TV Spot

Back to the :30 vs. :15 conundrum: how do you design a better :15 TV spot? Well, it’s not as difficult as rocket science, but it’s essentially an exercise in brain wave assessment. Simply put, you cut out the ads “valleys” and keep the “peaks.”

Neuroscience based copy testing has advanced to the point where it can algorithmically eliminate the weakest portions of the :30 TV commercial while keeping the strongest ones for the new :15. This re-cut commercial is then edited by the Agency creatives for story flow, continuity, and visual seamlessness into a final spot.

The Neuroscience Based :15 TV Commercial – How Good ?

At this point, you might be asking: “but how good, really, are these cut down neuroscience based ads? It all sounds like a big black box.”

Based on Nielsen NeuroFocus (disclosure: I work at Nielsen) testing of both original :30 TV spots and the EEG-optimized :15’s, here is what we see:

  • ~90% of neuroscience optimized :15 ads test just as well as their :30 counterparts
  • A significant number of optimized :15 ads actually test better than their :30 counterparts

Upside for Marketers

So, the next time you see your Ad Agency, tell them that you have a “present” for them—neuroscience-based :15’s. They’re definitely a lot more valuable than regular “cubic zirconium” :15’s and, more importantly, viewers will respond as if they’re :30 “diamonds in the rough.”

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Your Ad Spending: How Much is Just Right ?

August 9, 2010

Are you spending too much or too little on advertising? Don’t know the answer to this question? You’re not alone–it’s a big issue for almost all Marketers. Think about it for a minute: how do you make this decision for your brands?

How Much Should Your Brand Spend on Advertising?

The most common answer for many, it seems, is “whatever we can afford.” This is certainly the practical answer, and often the reality of managing a brand in a business environment that demands annual revenue and profit growth, but is it the right one?

There’s little glamour in this question, but I would argue that it’s a huge profit lever for Marketers that is rarely addressed in a systematic and rigorous manner. If you’re focused on improving Marketing ROI, it’s a question that deserves your time and thought.

The Usual Budget Approach

Many Marketers work backwards from a communications goal to determine ad spending levels. If we need 80% awareness to achieve our volume forecast, we can calculate the required GRP’s to achieve this. And, given our target audience and media strategy, we can then calculate the cost of the planned GRP’s. Presto—we know how much we need to spend. Or do we?

Advertising Spend: Volume Forecast & Planned GRPs

Requirements of Advertising Budgeting

How might CMO’s and Marketing leaders better defend their advertising spend levels? I’m always a fan of solutions that are:

  • Derived from empirical data and research
  • Connected to real business outcomes – revenue and profit
  • Are simple and practically possible to execute

Are there approaches to determining your advertising spend level that meet these requirements?

Advertising Responsiveness & Spending

One of the more rigorous approaches I’ve seen  to determining ad spend levels was written about by Malcolm Wright in the June 2009 Journal of Advertising Research. To greatly simplify, and avoid making anyone go thru the algebraic equations used (although you’re welcome to read about them here), Wright argues that advertising spend should be set based on:

  • Advertising elasticity as a % of gross profit

This requires that we know our gross profit—which every Marketer should know. But it also requires that we know advertising elasticity for our brand. This is a trickier topic.

Advertising Elasticity – What is it and how Can It be Measured ?

Advertising elasticity is simply the change in volume divided by the change in associated advertising spend. It’s essentially a return on advertising spend metric.

Within the CPG category, there have been a substantial number of studies done on advertising elasticity. These studies used rigorous single source data where it’s possible to observe what people watch and what people buy at the household level, and thus measure advertising elasticity with precision.

Household Level Research: Measuring Advertising Elasticity

What’s Known About Advertising Elasticity

These collective results show that the average advertising elasticity across 186 different studies is about .11. This means that for every $1 invested in advertising, sales increased by an average of $0.11.

Like all averages, it’s useful to deconstruct the .11 advertising elasticity to see differences under different conditions. For example:

  • Established vs. New Products – Using the case examples above, the average advertising elasticity for established products was .05. For new products, it was .24. So, new products are obviously much more responsive to advertising than established ones, and advertising levels should be set accordingly higher.
  • Cluttered vs. Non-Cluttered Environments – Another key factor in the studies was the impact of competitive clutter. In low clutter environments where competitors were not advertising heavily, advertising elasticity was .15. It was only .07 in a highly cluttered environment.

Competitive Clutter: Does Your Brand's Advertising Break Through?

Advertising Elasticity for Your Brand

The ideal is that you use single source research to measure advertising elasticity for your brand—and then use this learning to set affordable and appropriate spend levels.

Of course, this takes time and money and isn’t always affordable for small brands. For others, here’s a few useful guidelines:

  1. Start with the Advertising Elasticity Norms – A good starting place is the .11 average advertising elasticity norm. If you know nothing else about your CPG brand’s ad elasticity, you can assume that you should be spending about 11% of gross profit on advertising.
  2. Adjust for Other Meta Learnings – Adjust the ad spend up or down based on whether your advertising is for an established brand or is less than 3 years old. Consider whether your brand operates in a highly cluttered versus less cluttered environment. Review any additional learnings about differences in advertising elasticity by category, geography, etc. Make adjustments to the .11 as appropriate.
  3. Modify for Creative Strength – If your brand does copy testing, consider how your ad scored versus historical norms for the category or your brand. If your brand is well above norms, you should consider adjusting upward from the .11. If your brand scored below norm, reconsider whether you should be advertising at all until you get better creative.

Advertising Elasticity Guidelines: Copy Testing & Brand Learnings

I’ve spent enough time in Marketing to know that advertising spend is as much art as it is science. That said, there’s a big opportunity for CMO’s and their Marketing teams to be more rigorous in setting budget levels.

There’s financial upside to this exercise. Spending too much is wasteful and inefficient. Spending too little is missing a significant revenue and profit opportunity. Answering the “how much should I spend?” question is about getting your spend just right.

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The Genetic Markers of High Advertising ROI Brands

April 12, 2010

When I was in 8th grade, I was a pretty good basketball player who aspired to the NBA, but never noticed that my father was only 5’10” tall. The more scientists learn about our genes, the more they learn that while they’re not destiny, they do increase the likelihood that we will turn out a certain way. 

In a similar vein, TV Advertising has genetic tendencies–that is, certain characteristics tend to be associated with high ROI advertising brands. In June, I’m leading a series of Marketing ROI sessions at Nielsen’s annual Consumer 360 event in Las Vegas (Disclosure: I work for Nielsen). In preparation, I’ve been reviewing what we know about Advertising ROI from Market Mix Modeling. And learnings clearly point to a set of “genetic markers” of TV Advertising ROI. 

Market Mix Modeling — What Is It ?

Market Mix Modeling, if you’re not familiar with it, uses Marketing inputs and retail scanner data to build regression models which show how each Marketing element impacts revenue and, ultimately, Marketing return on investment. These models have become increasingly sophisticated and can now answer questions about ROMI by media channel, trade promotion, consumer promotion, FSI, etc. Most major CPG companies and many companies in other industries now routinely use MMM to evaluate the effectiveness of their Marketing mix.  

The Principles of Market Mix Modeling

So, back to the question: Assuming quality creative (always the most important factor), what are the genetic markers of brands with high TV advertising ROI? In a previous post, “The 5 Truths of TV Advertising Effectiveness,” I discussed whether TV advertising works as well today as 15 years ago. But beyond this, Marketing Mix Modeling can provide some answers not just about whether TV advertising is effective, but what kinds of brands and situations it’s most effective for.  

TV Advertising ROI is Highest:

1.  When Brands are Large — Larger brands ($200M+ in revenue) deliver higher ROI’s from TV advertising than smaller brands (<$50M in revenue). Why ?  

  • First, they have more users for advertising to influence. Advertising doesn’t just cause more consumers to buy your brand (or not). Beyond building penetration, effective advertising also builds purchase frequency and transaction size. Larger brands generally have more users, and therefore, more opportunities for advertising to build consumption through changes in purchase frequency and amount.
  • Second, it’s easier for larger brands to pay out the advertising investment. Simple math shows that a +10% revenue lift on a larger $200M brand ($20M) yields more revenue than the same lift on a $50M brand ($5M). So, on a fixed advertising spend, big brands can more easily achieve a good financial return.

TV Advertising ROI: Large Brands Have Large ROI

2.  When Purchase Frequency is High — Higher purchase frequency brands and categories tend to have strong Advertising ROI’s compared to low purchase frequency categories and brands.  

Higher purchase frequency brand consumers are likely more loyal to your brand (they’re buying it more frequently), and therefore, more predisposed to your brand and more likely to respond to your advertising. Also, a higher category purchase frequency means there are more buying opportunities for your advertising to influence consumers to buy your brand.  

3. When the Category is Expandable — Some categories are easily expandable (e.g. movies) while others are not (e.g. prescription medicine). Advertising ROI’s tend to be higher in expandable categories.  

And, big brands tend to benefit the most from category consumption increases, so the big brand effect mentioned above is doubly important (see Mike Ferry’s Guest Post “5 Ways Market Leading Brands Can Drive Growth“). 

4.  When Seasonal Category Consumption Is Higher than Media Costs — Many categories have seasonal consumption spikes. When the increase in category seasonal consumption is higher than the comparable seasonal increase in media costs, this presents an opportunity. Advertising ROI tends to be higher for brands that advertise during these seasonal consumption/media increase periods of imbalance.  

5. When the Brand has the Halo of a Masterbrand — Brands within a “Masterbrand” tend to have higher TV advertising ROI’s than brands without one. The halo effect of other brands within the Masterbrand have a clearly positive ROI impact on individual brands.  

But, Trade Promotions Are Even Better — Or Are They ?

Perhaps the most discouraging learning for Marketers who are big believers in advertising is this:  on average, MMM shows that advertising ROI is less than trade promotion ROI. And for some Marketers, that leads to the obvious: more and more trade spending and less and less advertising. Is this a good thing?  

Definitely not. MMM work clearly shows that there is a strong relationship between the % volume sold on promotion and regular price elasticity. Consumers aren’t stupid. If your brand is frequently on promotion, consumers learn that it’s only a matter of time until the next great deal–and they wait until it comes along.This points to another important way that Advertising works–it reduces price elasticity. It does so by reminding consumers of your brand’s benefit, getting current users to continue buying, encouraging them to buy more frequently and even buying more per buying occasion. 

Genetic Markers of High Advertising ROI Brands — Destiny or Hard Work ?

So, if your brand has the right genetic markers–is big, part of a large Masterbrand,  or lives in a category with seasonal consumption/media increase imbalances, high purchase frequency and expandable consumption–you’re in luck. For everyone else, don’t despair, it’s still possible to have high Advertising ROI.  After all, even the sons of 5’10” fathers make it to the NBA, just not very often and not without a lot of hard work.  

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