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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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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Watson Calling: Can Cognitive Computing Improve Ad Effectiveness?

May 28, 2013

The following post first appeared in the IBM “Building a Smarter Planet” Blog on May 21, 2013.

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It’s often said that marketers are drowning in data, but here at Nielsen, we have an idea for turning that harrowing experience into an insightful deep sea exploration.

For decades, Nielsen has been in the business of empowering brands and agencies with the information they need to understand and build connections with consumers.  We do this by measuring the advertising and media content people watch, the goods and services people buy – and very importantly, by spotting connections between the two. Why are these connections important? If you know what ads people are exposed to, and you know what those same people buy, you can get a lot smarter about how well your advertising is working and how to make it work better.

IBM Watson Calling - Can Cognitive Computing Improve Ad Effectiveness?

IBM Watson Calling – Can Cognitive Computing Improve Ad Effectiveness?

However, despite vast amount of data at their fingertips—and often because of the complexity of the data at hand—our clients’ ability to form these vital connections is oftentimes hindered. In fact, our advertiser clients tell us that despite the ever increasing amounts of data they have access to, they still have problems answering basic questions such as: How much should I spend on advertising? How should I allocate my spending across media platforms and within them? And, how do I measure my advertising performance “in-flight,” and make course corrections to improve results?

To help answer these questions, Nielsen created a simple “end-to-end” framework for measuring advertising and media effectiveness: the 3R’s. The 3R’s try to answer three simple questions: First, is my advertising reaching my intended audience (Reach)? Second, is it breaking through, being remembered and changing consumer opinion about my brand (Resonance)? And third, is it driving a behavioral reaction – e.g. sales (Reaction)?

We’ve been working hard to create the data sets and tools to help brand marketers answer these questions. We’ve gotten much better at answering the fundamental questions about advertising effectiveness, but we still have work to do.

Like never before, we and our clients face a continuous and, sometimes overwhelming stream of data generated by consumers and our digitally enabled measurement tools.  Just envision terabytes of structured and unstructured data pouring into our offices – trends, metrics, sentiments and perspectives – that express who consumers are, which programs and ads they’ve seen, how those ads perform by TV program, genre, web site, placement, number of times they’ve seen the ad, exposure to social media, where they’ve shopped, what they’ve bought, etc.

Within this data, there exists a range of opportunities to better understand consumers. But the challenge is clear, and for many, overwhelming – due to the data’s volume, scope and growing complexity, it’s almost too much to decipher.

A new form of technology is needed to dive deep into this sea of data, and come up for air with actionable advertising and media insights that can help brands understand their campaigns’ reach, resonance and reaction, and in turn, improve their advertising campaigns.

That’s why we were so intrigued when we began discussions with IBM about an entirely new and unique category of technology known as cognitive computing.

Cognitive computing systems can understand the nuances of human language, process questions akin to the way people think, and quickly cull through vast amounts of data for relevant, evidence-based answers to their human users’ needs. And very importantly, they learn from each interaction, to improve their performance and value to users over time.

Seems like a custom fit for the data-driven challenges today’s advertisers face.

Building on this excitement, we’re embarking on a new collaboration between the Nielsen Innovation Lab, which we founded in 2012 to advance research in advertising effectiveness, and IBM to harness the power of Watson, the sole player in this exciting new era of cognitive computing.

IBM Watson

IBM Watson

As part of our own brand’s continuous effort to advance understanding around advertising effectiveness, we’ll be exploring ways to use Watson for helping our agencies and their client brands engage more effectively with consumers across all devices – from TV to tablet to smartphone – while improving the impact of their advertising and media plans.

We believe this collaboration will open up a realm of possibilities for our clients, so they too can uncover value from new and exciting data. It’s time to stop drowning, and start exploring.

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Revisiting Reach — The Promise of Cross-Platform Planning

February 18, 2013

Watching TV the other night, I saw an ad for Brand X. And another. And another and another. After the fourth viewing, I thought “Enough! How many times do I need to see the same ad during the same program?”

Maximizing the audience reached at 1+ frequency—meaning that as many consumers as possible see your ad at least one time—has been gospel truth for many years now. The prevalence of media platforms and the ability to create integrated campaigns present additional challenges to achieving frequency control and unduplicated reach.

But they also bring great opportunity. The best media plan uses each platform to reach a different audience, rather than running the campaign as separate, independent plans for each platform.

Reaching Everyone in Your Intended Audience – the Impossible Dream?

Even in the broad world of TV, I’ve seen over the years that it’s really difficult to reach much more than 80 percent of your intended audience, no matter how much you spend.

A standard media plan typically bombards the heaviest 20 percent of TV viewers with ads, yet directs little or no advertising toward the lightest 20 percent. This isn’t the fault of TV—it’s still the broadest reach media vehicle we have, and virtually all households still watch TV. It’s just that current media planning tools leave something to be desired: more reach.

Light Viewers – Where are They?

So what’s the issue? Well, light viewers tend to be younger, more affluent, better educated and working outside the home—just the type of people who don’t have the time to watch much TV. So they watch more cable, watch programming at different hours, use DVRs, stream content online, etc.

They’re just harder to reach on traditional TV—and current media planning tools don’t do a very good job of constructing plans to reach these people. That’s why TV media plans often end up with approximately 80 percent reach—no matter how much they spend.

Multi-Platform – a Potential Solution?

Focusing on reaching these light viewers online allows you to extend your overall campaign reach against your intended audience. When done strategically, campaigns have achieved nearly 90 percent reach, as measured by Nielsen Campaign Ratings. Without proper insight, however, you may experience high levels of overlap in reach between TV and online, as many heavy TV viewers are also heavy online consumers, leaving you back at square one.

Nielsen Online Audience Segments—TV Viewing provides the insight you need to augment your TV media plan with online ads that reach audiences based on their TV viewing habits, so you can focus on reaching those hard-to-find light TV viewers online.

So instead of a traditional TV plan, which maxes out reach at 80 percent and bombards top quintile viewers with ads, this approach has a broader effect: it extends reach by serving ads to consumers who wouldn’t have otherwise been reached through traditional TV. By more strategically placing ads, it can also cap frequency among the online viewers and reduce frequency among the heaviest TV viewers.

Key Takeaways – Things to Remember

  • Maximizing reach at 1+ frequency is the gold standard
  • Traditional TV media plans typically don’t achieve more than 80 percent reach
  • Heavy viewers are overloaded with ads, while light viewers are exposed to few or none at all
  • Extending a campaign across platforms can increase reach and reduce frequency

To me, this looks like a good recipe for improving the effectiveness and efficiency of your media plans. Further, it might even benefit your brand by not upsetting heavy viewers in your intended audience who are currently overexposed and probably sick of seeing your ads and brand.

I like more reach per campaign—and at lower cost per thousand (CPM)—especially because I don’t like to be bombarded with the same ad over and over. And I’d be willing to bet that your intended audience would agree with me.

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MediaPost TVBlog Interview — The 3R’s of Advertising Effectiveness

December 11, 2012

The following is a repost of David Goetzl’s November 27, TVBlog post:

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There’s no sense for advertisers to ever be fully satisfied with the effectiveness of their messaging and tactics. So, they’ll always be in search of more data and the finish line will keep moving.

But here’s at least one enticing landing spot: a gauge of how many consumers saw an ad on one of four screens (TV, PC, tablet, smartphone) and what it prompted them to do (or not) in real time — with the data coming in an easily digestible form, ripe for swift action.

David Goetzl Interview on the 3R's of Ad Effectiveness

David Goetzl Interview on the 3R’s of Ad Effectiveness

Randall Beard says Nielsen’s on that path with its “3R framework,” an umbrella term for its efforts to measure how reach and resonance lead to reaction. (It could be called 4Rs with an equation where reach + resonance + reaction = revenue.)

Helping in the kitchen are the 3Vs of Big Data, where there’s more volume and variety of information coming at greater velocity.

“There’s way more data, way faster that’s coming at advertisers and agencies,” said Beard, Nielsen’s global head of advertiser solutions. “And one of the big challenges is to have a simplified (platform) that brings it all together in a way that they can easily operationalize it.”

Beard will lead a webinar next week with details on how Nielsen envisions opportunities in a 3R playing field. In advance, he took some time to offer some thoughts:

–In the “reaction” area, the Nielsen Catalina Solutions services look to connect media consumption with purchase behavior. There are multiple research providers looking in that direction with TV advertising. What makes the offering different?

“The audience data is from the Nielsen people meter data set — supplemented by set-top-box data,” he said. “Most of the other players in the space are just simply using set-top-box data … The second thing is that we’re cross-platform, so we have this service not only with TV, but with online, with mobile, with print. So you can identify the most responsive buyer behavior group and then execute that across platforms.”

–If the same ad runs on live TV and online, which is more effective?

The data is not for the exact same ad on both platforms, but 2011 research found the “breakthrough” — percentage of consumers remembering an ad — for 15- and 30-second spots was about 50% higher in an online platform than TV. Hypotheses Beard offered include online platforms offering more of a lean-forward experience and usually a lesser ad load.

–Nielsen, of course, doesn’t determine what the currency is in a particular market. But can any of its “reaction” tools – Nielsen Catalina, Buyer Insights – offer the basis for one should advertisers want to trade on the data?

Beard indicated Nielsen believes it plays more of an advisory role, but there are opportunities for sort of one-off deals.

“We’re trying to bring data to the advertisers, agencies and media companies that they can use to be smarter about the way people plan buy, execute and ultimately optimize the advertising,” he said.

He said working with NBC, Nielsen has found the same ads in its Olympic programming have more “resonance” than when they run elsewhere and NBC has used that to demonstrate effectiveness in a sales process.

–One argument networks make is there is value in ads viewed as they zip by in fast-forward mode via DVRs. Logos might be seen or there may be some reinforcement if a viewer has seen the ad before in full. Has Nielsen developed any insight here through its research?

Not discretely. But it has found that ad recall is 30% lower for time-shifted viewing — whether an ad is skipped or not with a DVR — versus live TV.

“If you know that there’s a difference there, you can certainly assume that at least some part of a lower score in a DVR’d program is because of fast-forwarding,” Beard said. “How much? Couldn’t say.”

— One coveted metric in the “reaction” area would be: did an ad prompt a purchase the next day? (Helpful to consumer package goods and telecom marketers, among others.) Can a viewing-purchase link be available in a sort of overnight fashion a la the cornerstone Nielsen TV ratings?

Not yet. It takes time to connect the dots.

But in a “resonance” sphere – both with TV and digital ads – results come in much faster.

–But clearly the quicker the better – especially if there’s an emphasis on providing real-time insight to allow adjustments.

That’s a “big opportunity,” Beard said, across all platforms. That would give an advertiser with, say, three ads running a chance to determine certain effectiveness gauges for each and do some editing mid-flight.

That not only can improve “resonance,” but save money.

If a 15-second spot is doing just as well as a 30-second one, why stick with it?

“Why spend money on 30s,” Beard said. “Move all your spending to 15s … there’s lots of opportunities for advertisers, in particular, to measure “reach” and “resonance” in as close to real-time as possible and then make smart choices about how they allocate their spending, or improve their advertising  to get a better reaction outcome.”

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Digital Innovation – A Conversation with Group M’s Chief Digital Officer Rob Norman

November 20, 2012

Last week, the Paley Center for Media hosted their Innovation without Borders conference. I had the pleasure of leading a discussion with the inimitable Rob Norman, the Chief Digital Officer of Group M.

Paley Center for Media Innovation without Borders

In our discussion, Rob and I debated the fragmentation of the media landscape, the increasingly simultaneous consumption of media,  the need for end-to-end advertising measurement, the importance of standard metrics, and the role of real-time optimization, among other things.

Rob Norman — Chief Digital Officer, Group M

To see Rob’s take on these and other media and advertising topics, click here.

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Why Marketers Are Still Struggling with Social Media (and what to do about it)

November 5, 2012

As the one-time CMO of a large global wealth management business with severe reputational issues during the 2007 financial crisis, I struggled mightily with how to engage with and use social media to help my brand.

Why Marketers Are Struggling with Social Media

Five years later, you’d think things would be better. But almost all of the CMO’s and Marketing leaders I talk with are still struggling with Social. Everyone knows it’s important, they know they need to engage with it, yet they are still trying to answer fundamental questions that are relevant to any Marketing activity:

1)      How do I engage and use social media to benefit my brand and drive sales ?

2)      How do I measure social media and the impact it’s having on my brand—positive or otherwise?

These are challenging questions that almost all Marketers, no matter their sophistication, are struggling with. The question is, why?

Social Media as a Business Driver

In most Marketing activities, Marketers design marketing programs that they believe will increase basic Marketing measures like awareness, trial and consideration, and ultimately result in higher sales.

To do so, Marketers have created predictive tools that increase their confidence that these programs will ultimately work. Examples include:

  • Copy testing to predict likely advertising success in building sales
  • Purchase intent scores, which measure the likelihood of consumers buying your product
  • Market mix modeling norms, which indicate how much sales $1 of investment will yield
  • Etc.

A key issue with social marketing programs is that there are few of these measures, and even where they exist, they are highly suspect. Here’s why.

The Impact of Social – An Experiment

In his book “Everything is Obvious Once You Know the Answer,” Duncan J. Watts describes a web-based experiment designed to emulate a “market” for music, as a means of measuring the impact of social media. He designed the experiment for consumers to listen to, rate, and potentially download songs.

First, he created two groups. Both groups were given the same set of songs to listen to and rate. Each group was further divided into sub-groups so it would be possible to see how multiple groups responded to the same environmental conditions.

But, there was one key difference between the two groups. Group A consumers were not able to see how many of their compatriots were downloading the songs they were listening to. Group B, in contrast, was able to see the downloads and rank order popularity of the music based on other participants behavior. Said differently, group B had a “social layer” of potential influence while Group A did not. The experiment was “repeated” multiple times given that each of the sub-groups had different participants.

Group A results with different participant groups were remarkably consistent–the rank order of songs was similar across groups. If song A was number one in the first group, it was also number 1 in the 2nd group, 3rd group, etc.

This tells us not only that consumer music popularity without a “social layer” is consistent and relatively unchanged across groups, but that it is highly predictable.

Group B results were quite different. The most popular songs, and the less popular ones, were typically  even more popular or less popular in Group B than Group A—e.g. the “social layer” of seeing how other participants downloaded songs sharply accentuated the way the degree to which consumers in Group B rated and downloaded songs.

But, equally important, results across different participant groups showed large variations in popularity. So, if song A was most popular in the first group, it might only have middle popularity in the 2nd group, and so forth.

Social Makes Results More Extreme and Unpredictable

Duncan Watts had this to say about the results:

“In all the ‘social influence’ worlds…popular songs were more popular (and unpopular songs were less popular) than in the independent condition. At the same time, however, which particular songs turned out to be the most popular—the “hits”—were different in different worlds. Introducing social influence…increased not just inequality but unpredictability as well.”

Said differently, the “social layer” not only caused the ratings to be different, but also made the results much less predictable. This is the challenge that Marketers face with social media:  social interaction and the impact it has on your brand is highly unpredictable.

In a world where CMO’s want to be sure that every dollar they are investing—in time, people and resources—is money that delivers a good return, a fundamental challenge with social is that it’s much less predictable than traditional Marketing programs in how it impacts your brand.

What to Do?  Measure & React

What’s a CMO to do? Well, I believe that real time measurement of social—how well its reaching your consumers, how its changing their attitudes toward your brand (for better or worse), and what impact its having on your sales—is the right way to mitigate and take advantage of the unpredictable nature of social.

Watt addresses unpredictability as follows:

“Rather than predicting how people will behave and attempting to design ways to make consumers respond in a particular way…we can instead measure directly how they respond to a whole range of possibilities, and react accordingly.”

Real time “measure and react” is the best way that you can engage and respond to consumers in a social world when it’s so difficult to predict in advance how social engagement will play out.

That’s why CMO’s need to focus less on creating highly compelling (and perfect) social content and programs, and invest more in quickly understanding how consumers are responding to the various elements of their plan and then adjusting accordingly.

It’s obvious, CMO’s just need to continuously “measure and react,” because when they do so, they already know the answer–and how to respond.

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