The “Death of Marketing” Has Been Announced Prematurely

Has there been a fundamental change in how people think about and buy goods and services? Is old-school marketing dead?
According to the recently-minted orthodoxy of social media, marketing is being transformed, and we are moving from the Age of Push to the Era of the Conversation. The Don Drapers of the world, they say, will now have to play the new way, find new jobs or become hobos. Participation in a conversation is voluntary, per the new theory, meaning marketers can’t unilaterally control conversations and so now must learn to communicate differently with the people in the marketplace.

WHAT HASN’T CHANGED

Marketing Has Always Been A Conversation – Marketers Just Haven’t Recognized It Until Now

There is an important truth here – much of the conversation about brands and products is intra-customer, and doesn’t involve the marketer at all. This has always been the case, but it just has not been as observable until it started happening online.

Audiences Have Always Been Able to Walk Away

Audiences have always asserted more control over the “conversation” than marketing models have admitted. People have been fast-forwarding and channel-surfing through television ads since they figured out which remote control buttons to use. Since the very birth of mass media, admen and their clients have been solving and re-solving the problem of how to entice an audience to listen to their stories instead of wandering off to grab something from the refrigerator.

Propaganda Still Works

Working against this is has always been the fact that (as psychological experiments have shown) repeated messages have an influence on peoples’ perceptions and behavior even if they are skeptical or not paying full attention, and even if they are aware they are being ‘sold’.

WHAT HAS CHANGED

The Emergence of Social Media

Thanks to social media lowering the bar for what constitutes a relationship, people are regularly engaging in communication with a wider circle of casual or low-involvement contacts.

Conversations are Observable and Trackable

We can find out what people are saying about brands and our products (at least when they happen in online social media). These conversations can assert a great deal of influence on buying behavior.

Advertisers and Marketers can Participate in the Conversation

Marketers can, when they decide it is to their advantage, participate in these conversations and assert some influence on the the agenda and the messages

Advertisers and Marketers can START the Conversation

Marketers can initiate conversations, and they can provide the platform or venue for these conversations to take place. However, the the attempt can backfire. Conversations can and will change locations if a community gets the sense that there is excessive censoring or propagandizing.

SO?

So, things have changed, but not that much. People still need to buy things, they still need to decide what to buy and where to buy it. It’s just that now, people increasingly use social media (among other channels) to get information about products and services they are considering. Social networks have always been influential, but now they are pervasive, instantaneous, and measureable. So you shouldn’t ignore social media, you should listen to and participate in it. That’s all.

The Digital Nervous System

The web can function like a giant extension of the human nervous system. Like a spider at the center of a giant global web, you can collect and observe streams of data coming from all over the digital expanse: searches, tweets, forums, blogs, newspaper and magazine sites, press releases, Facebook and LinkedIn. Each time someone looks for or mentions your company or your product you are alerted, and you can choose in that moment to respond to it, ignore it or wait until you have more information.

Does this sound like anything you are doing now? Someone should be doing this for your company, because marketing has increasingly become an ongoing series of conversations (whether you participate in the conversation or not).

EXPERIMENT: DETECTING INSTANT RESPONSE TO MEDIA WITH THE INTERNET

There are several national TV shows that frequently have book authors as guests (the Daily Show, The Colbert Report, The Today Show, Good Morning America). The next time you find yourself in front of one of these shows when an author is on plugging their book, try the following experiment (this will work best with a show with a national audience):

1. Fire up your laptop and go to amazon.com
2. Search in the Books category for the title of the book the author is plugging on the show you are watching
3. Click to the Amazon page for that book.
4. Scroll down past the synopsis and the reviews to the section labelled Product Details. It should look something like this:

The number I have circled is the book’s current sales rank on Amazon.

5. Every few minutes while the author is on the show and for a while after that (until you bore of this experiment), hit function key f5 to refresh the page and watch what happens to the book’s sales ranking.

The rank should get better – in real time – as you are sitting there. I have done this several times when my brother-in-law has done TV appearances to promote his books, and it is amazing. Once he was on Oprah Winfrey and we saw the sales rank improve precipitously from 20-something into the top 10 while he was being interviewed.

Now imagine all the other analogous information streams there are available on the internet. If you could get the monitoring automated, just think of how quickly you will know exactly what the world thinks of your new site, your new ad campaign, your new product. Just think of what you’d be missing by NOT knowing.

EXTRA CREDIT EXPERIMENT #1 – THE TWITTER BUMP

In between rank checks you should do check in on Twitter searches for the author’s name and the book’s name. These should also pop during the author’s TV appearance.

EXTRA CREDIT EXPERIMENT #2 – THE GOOGLE BUMP

After a day or so you should go to Google Trends and see what happened to searches for the author’s name and the book’s name. These should’ve spiked on the day the author did the TV appearance. Google Trends doesn’t provide much flexibility about getting more granular (in time) data in a more real-time way, and it looks like the beta for Google Insights for Search has a latency of a couple of days.

GOOGLE EPIDEMIOLOGY – WHO KNEW THEY COULD DO THAT?

Take a look at the Google Flutrends project (http://www.google.org/flutrends) and you can see what an amazingly useful datasource this would be with access to the full detail in realtime. It turns out that counting Google searches for flu information is a quicker detector of flu epidemics than CDC reports are.

I believe it would be just as accurate in detecting other kinds of contagion sweeping through the world: fads, emerging trends, scares, rumors, accidents, disasters – this is the kind of information that businesses need to know when it involves their products, their brands, or their markets.

Math Marketing: Excellent White Paper by Dimitri Maex

Dimitri Maex is the Managing Director Marketing Effectiveness at Ogilvy & Mather, and the author of a fantastic white paper that is posted HERE on the WPP website . What is so great about it is that it presents exactly what most companies need to know in order to get started in harnessing the full power of quantitative marketing methods, in a package that only takes about 15 minutes to read.

He starts with the history of quantitative marketing, gives a sense of the place of “math marketing” in the current business landscape, describes the types vendors with which a company can ally, and the wraps up with how a company should organize and hire to around the new skills and challenges peculiar to the coming era of quantitatively-driven marketing.

Some nits:
I don’t like the sound of the name “math marketing”. It’s just that the math doesn’t do any marketing – people still make the decisions and integrate the insights into their work, they just use data-based metrics and statistical techniques to assist them in getting a coherent picture of what is working and what isn’t, and formulating what might work in the future. It is probably also a terrible way to brand something you are selling to execs who mostly sucked at and avoided math in school. It’s like calling it “eat your vegetables marketing”.

The section on vendors is far from exhaustive. He leaves out SEM/SEO agencies in particular, and provides only the massive brand names in most of the categories he is describing. I guess Maex works for an ad agency – so he’s not responsible for selling you on his competition – but I’d look elsewhere for a buyer’s guide.

Whatever, he is right on the money about the current state of affairs and where most companies need to go.

He wraps with a couple of lists: Seven Steps to Increased Accountability, and Seven Steps to Increased Accountability to Transformational Consumer Insights.

This is a great document for business folk who want to understand the big picture of marketing analytics and quantitative marketing techniques, and want to understand how to manage them to best effect.

Alan Wurtzel’s Editorial in the Q3 Issue of the Journal of Advertising Research

More good metrics reading from the JAR: After my prior posting on metrics articles in the Q4 Issue of the Journal of Advertising Research, it occurred to me that I did not mention the editorial that NBC’s Alan Wurtzel wrote in the Q3 issue…

Now. Or Never – An Urgent Call to Action for Consensus on New Media Metrics” by Alan Wurtzel, President of Research and Media Development at NBC Universal
In this editorial, Alan Wurtzel lays out what he believes is a critical juncture for measurement of new media. He sums it up this way: “You can’t sell what you can’t measure, and, unfortunately, our measurement systems are not keeping up with either technology or consumer behavior.” The problem isn’t a lack of data – the samples are getting bigger and the precision is getting greater. The problem is that technical challenges exist that make it hard to assess the validity of measurements. Without precise and transparent definition for how data are gathered and metrics are being calculated from data, Wurtzel says programmers cannot depend on the numbers as a basis for decision-making. Proprietary considerations are holding vendors back providing this level of visibility into their processes.

Wurtzel cites a case – quoted by many sources last fall – where NBCU purchased and compared viewership data for the “Heroes” finale from several different set-top box (STB) vendors. The difference between the highest and lowest measurement of the show’s ratings was 6% – which translates into $400,000 of difference in revenue. While 6% sounds low, the “Heroes” example had high enough ratings that they should have had relatively low variation in measurement, meaning that the variation in ratings for lower-rated shows would be much worse. And this is variation in purportedly directly-measured STB data, which should have had little variation at all.

According to Wurtzel, there are serious differences between different vendors that cause this variation. For example, there is no standard way to determine whether or not an STB-attached TV is on or off from the STB data stream, so every data vendor has come up with their own algorithm for deciding when the TV is on or off, and they aren’t sharing these algorithms. There are other similar “edit rules” that each vendor carefully guards. This creates differences in the measurements generated. Now, when you think of the task as not just measuring TV, but an integrated understanding of how a program works across three screens (TV, Mobile, and Internet), now you are looking at huge gaps in comparability and meaning of metrics from screen to screen.

This was written last Fall. What grew out of this thinking was the CIMM, which I have discussed in prior posts. What is likely to happen in the long run is anyone’s guess, but Alan’s article reads like a set of product requirements for the ultimate three-screen audience metrics platform, so the best outcome would be for some smart entrepreneur were to develop just such an offering. Hmmm… I’d say keep your eyes on the marketplace.

The December Issue of the Journal of Advertising Research (JAR) has Great Metrics Articles!

There are a couple of useful articles this month in the Journal of Advertising Research. They are on a roll over at the JAR, driving some great discussion in the last few months about measurement of marketing, digital and otherwise. Recommended reading in this month’s issue:

Commentary: Who Owns Metrics? Building a Bill of Rights for Online Advertisers”, by Benjamin Edelman, Harvard Business School Assistant Professor in Negotiation, Organizations & Markets
Ben Edelman, who has written on the role of deception and overcharging in online media (among other topics) is right on target here – he argues that advertisers have a right to know where and when their ads are being shown, delivered in the form of meaningful, itemized billing. He also asserts the advertisers’ ownership of the data that comes from their campaigns, and says they should (for example) be able to use data collected from their Google PPC campaigns to target campaigns on MS AdCenter or Yahoo! This is definitely a controversial area – certainly Google, along with cable and satellite TV operators, would disagree – read it and let me know what you think.

It’s Personal: Extracting Lifestyle Indicators in Digital Television Advertising, by George Lekakos, Assistant Professor in e-Business at the University of the Aegean, Greece.
In case you think my comment about TV distributors wanting to own audience data is irrelevant in the context of digital marketing, Lekakos lays out a scheme for using set-top box data to discover and target lifestyle segments that are then used as part of a targeting algorithm. The author lays out an approach by which TV set-top box data can be used to drive very accurate personalization and targeting of ads, but the question of whether the data belongs to the distributors, the programmers, or the advertisers is quite critical to whether this can be implemented. I’d have to say that the question is far from settled.

Measuring Advertising Quality on Television: Deriving Meaningful Metrics from Audience Retention Data<by Dan Zigmond, Sundar Dorai-Raj, Yannet Interian, and Igor Naverniouk
The authors explore the use of audience retention metrics captured via TV set-top boxes as a measure of ad quality. They use a “retention score” that purports to isolate the effect of ad creative on audience retention, and link it with future audience response and qualitative measures of ad quality. They assert its usefulness as a relevance measure that could be used to optimize TV ad targeting and placement. Again, we should note that the issue of data ownership needs to be dealt with if this approach is going to be applied widely.

The Foundations of Quality (FoQ) Initiative: A Five-Part Immersion into the Quality of Online Research, by Robert Walker, Raymond Petit, and Joel Rubinson
To address both the increasing importance of online research and questions about its validity, the FoQ Initiative has been undertaken to measure the quality of online research. The Online Research Quality Council included large advertisers, ad agencies, academic researchers, and research suppliers in the process. Among the issues they addressed: accuracy, representativeness, and replicability of results, identification and handling of questionable survey-taking behaviors, and the suspicion that small number of “heavy” online respondents are taking most online surveys.

Some of the interesting findings:

  • There is significant overlap in membership of various online research panels, but no evidence this causes data quality issues
  • Multiple panel membership actually lowers the odds of “bad” survey-taking behavior by 32%
  • You should keep surveys short – longer surveys increase the occurrence of “bad” survey-taking behavior by 6X
  • Age matters – younger respondents had 2X the occurrence of “bad” survey-taking behavior than older ones
  • Search Volume for Analytics Ramping Up Steadily – (More Fun With Google Trends)

    Just for fun, I did another Google Trends search, this time on “analytics” – adding “CRM” and “ERP” as reference points. The result seems to suggest that if you are in the business software market, that you should have an analytics offering. We’ll see, but I predict that the hot growth area in business software in 2010 will be Analytics. Searches for analytics have been steadily ramping up for the last several years, and are now at a higher level than searches for the above-mentioned enterprise business software categories.

    I find it very interesting that searches for “ERP” and “CRM” have been flat for so long, but REALLY interesting that the volume of “analytics” searches surpassed them in 2009.

    Strong Seasonal Pattern Found in Search Data for Marketing Mix

    I guess it makes a kind of sense, but a search I did in Google Trends on the phrase “Marketing Mix” indicates that marketers are only interested in the topic during the colder months of the year. I guess once plans are submitted and budgets are approved, they have bigger fish to fry. Or maybe they are in the Hamptons. Take a look at the graph in the screenshot below – classic annual seasonality, right?

    One of the changes I would expect to happen in the next few years, is that focus on marketing mix will become more continuous, and this graph will look more linear.

    New Partnership Measuring Online Ad Impact on CPG Sales: IRI, Comscore, AOL, [x+1], and Dynamic Logic

    A recent spate of press releases (HERE, HERE, and HERE, among others.) announced a partnership that will offer measurement of online advertising’s sales impact for consumer packaged goods companies. What does this mean to online content providers, agencies and ad networks? If there is a credible way of measuring the impact of online advertising on the sales of snacks, beverages, health and beauty aids, OTC pharmaceuticals and household products, this will unlock huge CPG money that has been held back from full adoption of online advertising because of uncertainty about its relative effectiveness compared to channels CPG companies have used for decades. Did I say “huge money”? I meant to say HUGE MONEY.

    This will ultimately have a secondary effect that is good for the analytics business – it will raise the bar. CPG companies have long used analytics to plan and measure impact for their media spending, and as a result, they are data and modeling savvy. They will not blindly accept whatever someone pulls from Atlas, DoubleClick, Google Analytics, Omniture or WebTrends. The CPG paradigm is one where the cross-effects and tradeoffs between different media channels are measured and modeled, and nothing gets the big spend unless the numbers support it. This goes way beyond just throwing some tags in some ads and counting impressions, clicks and conversions. This entails starting with capture of how marketing dollars are spent, and then modeling how the spending does or does not move total sales (not just the sales from online). Things are about to get even more interesting.

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