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.

tv-everywhere

 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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Using TV Data to Optimize Digital

January 5, 2014

As the TV and digital worlds begin to merge, one of the more interesting new capabilities that advertisers and their agencies should be exploring is using TV audience viewing data to plan and buy digital audiences to increase total campaign effectiveness.

Videology's Mark McKee on Bringing TV data into Digital

Videology’s Mark McKee on Bringing TV data into Digital

In this BeetTV video, Videology’s Mark McKee explains some of the thinking behind this.

Using TV data to Optimize Digital

This  is important because historically, TV and Online planning and buying were done separately in most cases, missing a great opportunity to extend reach beyond random duplication of audiences. I wrote about this opportunity in a separate blog post earlier this year.

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Shifting Digital Accountability to Brand Marketers

June 3, 2013

Growing up, when I was pestering my parents about something that I just really, really had to have (like a real, live pet monkey), they would often say:

“Be careful what you ask for; you might just get it.”

Brand Marketers have been asking for lots more from digital—but have largely been unmoved by the response, and their anemic spending shows it.

Shifting Digital Accountability to Brand Marketers

Shifting Digital Accountability to Brand Marketers

They ARE shifting more money into digital, particularly as on-line video, mobile and social explode.  But their digital spending has lagged their direct marketing counterparts, as they continue to look for more evidence of the efficacy of digital advertising.

The accountability debate is shifting quickly though, from digital publishers and measurement companies to the Brand Marketers themselves.

What do Brand Marketers Need?

1.  Audience Delivery – Much has been written recently about the issues and opportunities associated with digital audience delivery. Any reader of the advertising and media press knows that large numbers of digital ads are not delivered to their intended audience, and many aren’t even viewable—a real embarrassment to many who prided digital on its precise targeting.

But the fact that we are even talking (or writing about) this topic says a lot about how to solve the problem. We can now measure how well, or how poorly, individual sites perform in delivering digital advertising to their intended audience—on a daily basis. And, with metrics that are common across platforms—e.g. reach, frequency, GRP’s against key demographic targets, Brand Marketers can now much better understand the relative performance of different media.

2.  Brand Impact – Brand Marketers care not just about sales, but about their brand or, more specifically, brand equity. They want to know that digital advertising has equal or more brand building impact than the alternative mediums.

Digital brand building metrics have now equaled and, in some cases, surpassed metrics from other mediums. Brands can not only measure increases in awareness, brand recall and other traditional ad effectiveness metrics, but can now also link ad exposure directly to traditional brand equity metrics. Given these tools, Brand Marketers should be confident that they can really understand the impact of digital advertising on their brand KPI’s.

3.  Sales Impact – Not surprisingly, while Brand Marketers want to see that digital advertising builds their brand, they also want to know that their brand building efforts result in sales. There are multiple approaches available for measuring the sales impact of digital advertising.

Traditional Market Mix Modeling (MMM) is one, and it’s particularly effective at giving brand builders a relative understanding of how digital advertising compares to other traditional mediums such as TV and Print. That is, for every $1 invested in digital, what on or off-line sales return do I get and how does that compare to other media?

A newer approach for Brand Marketers is Attribution Modeling, which models individuals’ exposure to different digital touch-points against sales. Ironically, attribution modeling was first advocated by direct marketers who were trying to understand the contribution of different digital exposures to search based click-thru.

The advantage of attribution modeling is that it can typically measure more granular digital activities than MMM and the impact of cross-platform exposure on sales—e.g. it can “attribute” impact to different touch-points and combinations thereof.

In either case, there really is no excuse now for not understanding the sales impact of your digital advertising—ROI measurement in digital is very good–even for brand based advertising.

4.  Real Time Optimization – One of Marketers biggest frustrations across all media has been their inability to quickly understand advertising and media performance, and then make improvements in-flight.

Digital, in theory, should be great at this, and in fact has made great strides with real-time bidding (RTB). RTB uses real time performance metrics (click thru, etc.) by site, placement, etc. to understand how to bid and re-allocate spend to the best performing placements just as its name implies—in real time. But again, these gains have mostly been in the direct response world, leaving brand marketers to wonder about what could have been.

Well, direct marketing to the rescue. Real time optimization is now the domain of the Brand Marketer. Brands can now select a few key brand metrics, measure impact continuously across creative units, sites, exposure frequency, and audience, and optimize in real time to improve results.

Optimization can be done manually by the Agency, or via demand side platforms. Some progressive agencies have even take this further by collaborating with publishers on real time optimization to deliver much stronger brand results.

Shifting Accountability to Brand Marketers

Brand Marketers used to have a real issue with digital—accountability. “What does it do for my brand ? How does it impact my sales?” Fair questions that, frankly, weren’t being answered very well until recently. Hence, the slower adoption of digital by the brand focused Marketing community.

The accountability debate has shifted—to Brand Marketers. There really is no reason, at least no measurement reason, that Brand Marketers shouldn’t be playing in digital—in a big way. Now Brand Marketers need to be accountable for measuring, understanding and improving the impact of their digital advertising.

And, let’s hope they fare better than I did with my monkey request. Because while my pet monkey was a lot of fun (and a blast at show and tell), I also spent an awful lot of time cleaning up his messes—at meal time and otherwise !

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Linear TV vs. On-Line Video Advertising — Which is More Effective?

April 5, 2010

Did You Know That:

  • On-line video ad spending grew +41% in 2009 — even during a down advertising year?
  • 72% of all internet users in the U.S. viewed on-line video last year?
  • More U.S. consumers watch video on the web than watch recorded TV on DVR’s?

All of this adds up to something very interesting: On-Line Video advertising is growing like a weed. Which raises another question: how does On-Line Video advertising work versus Linear TV advertising? 

On-Line Video Ads -- How Do They Compare to Linear TV Ads ?

My colleague David Kaplan of Nielsen IAG (disclosure: I work for Nielsen) partnered with Beth Uyenco, Global Research Director from Microsoft, to compare the effectiveness of Linear TV advertising and On-Line Video advertising in a recent presentation to the Advertising Research Foundation (ARF). 

Research Approach — What Was Measured

Kaplan and Uyenco used Nielsen IAG’s U.S. on-line panel to measure TV and web video advertising data from November 2007 to May 2009, across 238 brands, 412 products, and 951 advertising executions.  For each ad, they measured the same effectiveness metrics: general recall, brand recall, message recall and likeability. Key measurement metrics were identical across the two mediums. 

On-Line Video Advertising -- Why Is It More Effective ?

Key Learnings — Linear TV vs. On-Line Video

1.  On-Line Video Outperformed Linear TV — Remember that this was an “apples-to-apples” comparison which compared the exact same creative execution across the two mediums. On-Line Video scored higher than Linear TV ads, on average, for: 

  • General Recall:        65% vs. 46%
  • Brand Recall:           50% vs. 28%
  • Message Recall:      39% vs. 21%
  • Likeability:               26% vs. 14%

2.  The On-Line Video Advantage was Largest Among 13-24 year olds — Among younger consumers, On-Line Video outperformed Linear TV advertising by greater than 2 to 1. On-Line Video’s advantage cut across all age groups, but was smallest among  50+ year olds. 

3.  Re-purposed TV Ads Outperformed Web Original and Flash Animation Ads — This was one of the most interesting learnings of the study. Even when controlling for prior TV ad exposure, a re-purposed TV ad shown on web video performed better than ads created specifically for the web. What does this say about Marketers understanding of digital creative ? 

4.  Linear TV + Web Video Ads are More Effective Than Linear TV Alone — Consumers exposed to ads in both mediums had higher general recall, brand recall, message recall and likeability than consumers exposed to TV alone. Once again, the data clearly shows the advantage of a cross-platform, integrated marketing approach. 

Why Is On-Line Video More Effective ?

There are a number of reasons which could explain On-Line Video ad superiority: 

  • Higher Program Engagement — As I’ve discussed in a previous blog post, Why Your Brand Should Understand TV Program Engagement, research shows that the more engaged consumers are in a program, the more likely they are to remember the ads in the program. Nielsen IAG research shows that on-line video program engagement is +13% higher than the broadcast TV primetime norm. So, this higher engagement naturally drives higher ad recall.
  • Inability to Skip Advertising — If you’ve watched any On-Line Video, you know that you can’t easily skip the ads. I think the impact of DVR ad skipping on ads is over-rated, but the lack of DVR like ad skipping has to benefit On-Line Video ads.
  • Reduced Ad Clutter — On-Line Video has about 1/2 the ads per hour than regular network TV. Various research studies over the years have shown that there is a small, but significant, impact of clutter on advertising effectiveness.
  • Presence of Companion Ads — On-Line Video ads are more likely to have companion ads in the same program. The presence of companion ads increases ad effectiveness versus a single exposure alone. However, even when they controlled for a single ad exposure, On-Line Video still significantly outperformed Linear TV.

Now, before you think about running out and building your next campaign around On-Line Video, consider this: the average consumer spends only2% of the time viewing web video as they do TV. The practical implication of this is that most brands can’t deliver a high reach media plan with web video alone. 

But the facts remain: On-Line Video ads are more effective than Linear TV ads, especially among 13-24 year olds. As well, On-Line Video ads work synergistically with TV, and perhaps best of all, TV ads can be re-purposed on-line and actually score better than creative that’s been created specifically for the on-line medium. 

Can It Last ?

Some of the factors contributing to On-Line Video’s advantage, such as higher program engagement scores, are unlikely to change anytime soon. But others, like reduced ad clutter, will probably erode over time. Content providers are not making much money with their content on-line, and some are experimenting with more ads per hour. So, any advantage due to less clutter is likely to be short-lived. 

Nonetheless, with it’s higher performance versus Linear TV and spectacular growth rates, I think it’s only a matter of time On-Line Video ads become a signficant part of every smart CMO’s marketing mix. 

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Learning From the Dynamics of Viral Marketing

January 25, 2010

In what context do viral marketing strategies work? How do on-line product recommendations develop, multiply, spread and ultimately, dwindle and die? And, can Marketers influence any of this?  

These were important questions posed by Leskovec, Adamic, and Huberman in their 2008 study “The Dynamics of Viral Marketing.” This is one of the few studies I’ve seen to actually study how on-line recommendations grow virally and how this growth impacts purchase behavior throughout the viral network.  

Viral Marketing -- When and Where Does it Work?

 

Admittedly, the study had limitations, notably that it was only four categories, just measured on-line viral activity, and included a discount incentive to help motivate purchase. But, even with these limitations, it uncovered deeper insights into the systematic patterns in knowledge sharing and persuasion online—all of which are of high interest to Marketers.  

What Did the Study Entail?

Lescovec et al. examined an online recommendation network composed of 4 million people who made 16 million recommendations for 0.5 million products. Each time a consumer purchased a book, music, or movie, he or she could  send e-mails recommending the item to friends. The first person to purchase the same item through a referral link received a 10% discount.  

What was Measured

  • When and at what price a product was purchased
  • If the product was recommended to others
  • Whether the recommendation resulted in a subsequent purchase and discount

They then modeled the effectiveness of recommendations as a function of the total number of previously exchanged recommendations.  

Recommendation Networks Grow Slowly Over Time.

 

Important Viral Network Learnings & Insights

Finding #1:  Consumers recommended a large number of products to the same group of people. As a result, recommendation networks became heavily locally-based. For example, in the DVD recommendation network there are 182,000 pairs that exchanged more than 10 recommendations.  

Consumers Tend to Recommend Products to the Same People

 

Finding #2: Recommendation networks centered on a specific product category. That is, the people tended to focus on recommending a particular product category and thus created a “community of interest.” Having said this, most all networks shared recommendations for all types of products.  

Finding #3: Trust, influence, and perception of “spam” affected purchase. As people exchanged more recommendations, the likelihood they would purchase the product increased due to a growing foundation of trust. However, purchase likelihood increased, peaked, and then fell as consumers received additional recommendations for a specific product. A few recommendations built credibility; too many appeared as “spam.”  

Finding #4:  Most recommendation chains didn’t grow very large. In fact, most terminated with the initial product purchase, and even the largest connected networks were very small as a percentage of the total population.  

Recommendation Chains Don’t Typically Grow Very Large

 

Finding #5: 20% of recommendations accounted for 50% of sales. This is not far from the usual 80-20 rule, where the top 20% of products account for 80% of sales.  

What are the ‘Viral’ Implications for Marketers?

1. Identify the “Amplifiers.” Given that 20% of recommendations generate 50% of sales, it’s key to figure out whom the amplifiers are and focus your efforts on them.  

2. Determine Where the “Amplifiers” Congregate. Where do they exchange product information? On what platforms do they consume media? Web behavior can be linked to off-line purchase panels to quantify the effectiveness of recommendations (see “What Really Drives Web Advertising ROI”).  

3. Take Online Recommendation Networks to the next level Through Social Media Marketing. Marketers should explore development of models to measure recommendation systems on Twitter, Facebook, Foursquare, and the larger online arena. Through broader web 2.0 outreach, marketers can quantify consumer engagement on recommendation networks by volume, reach, tone, and source.  

Marketers can optimize paid media and earned media with viral marketing.

 

4. Be Wary of Creating “Recommendation-Fatigue.” A fine line exists between trust and influence in recommending a product and what is widely considered “spam.” Consumer engagement via any online channel must be done with careful consideration of earned media and buzz promotion.  

Viral Marketing: Limitations…

What’s not yet so clear from the research is how to minimize transmission “breakdown” – e.g. how do you minimize the likelihood that a product recommendation is the last one. As the research showed, most viral networks don’t grow very large. Marketers will only invest significant money if they can truly scale viral marketing programs.  

…And Future Opportunities

With the right tools and metrics, marketers can diversify their marketing plans to incorporate viral marketing strategies. The research clearly shows that viral marketing can build unique and niche recommendation networks, bolster consumer engagement, and lift sales.  

And as consumers continue to favor a digitally-based, social network-centric world, it’s critical that Marketers become more expert at viral marketing. Key to this will be identifying amplifiers, focusing on congregation points, leveraging social media opportunities—all without overdoing it. As importantly, Marketers must discover new approaches to spread and scale viral marketing just as effectively as the flu seems to proliferate every flu season.  

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