Less is known about advertising than we think

It strikes me as very odd when people say things like “we have much to learn about [insert new media], it’s not like TV that we know so well”.

Know so well?!?  How many marketers have heard of the ‘Duplication of Viewing Law’ (Goodhardt, 1966*) ?  How many can predict a repeat-viewing rate for a program, time-slot, or channel?  Even what is known isn’t well known (nor used).

There are so many unanswered questions.  Even simple questions like is an ad spot on the left hand side of a page is worth less or more than one on the right?  And how much?

Not enough is known about how we should best use media to expose category buyers to our advertising.  Let alone how these exposures reach brains.  And this is true for even ‘old media’ like TV and print.  So much that needs to be researched.  It’s extraordinary how ignorant many marketers (and marketing academics) are about our discipline’s fundamental ignorance.

Byron Sharp, July 2015.

* Published in the most cited journal in the world, Nature (and yes the date is correct, 1966).  Yet try to find a marketing textbook that covers it (not counting this one).

What’s Not to “Like”? Can a Facebook Fan Base Give a Brand the Advertising Reach it Needs?

Our earned media research article has now been published in the Journal of Advertising Research:

What’s Not to “Like?” Can a Facebook Fan Base Give a Brand the Advertising Reach it Needs?
Karen Nelson-Field, Erica Riebe, and Byron Sharp

Journal of Advertising Research, 2012, June, Volume 52, No.2
A marketer with a Facebook Fan base has at least some ability to advertise to that audience. What quality of reach, however, does this sort of “earned media” deliver? The landmark discovery by Andrew Ehrenberg of the negative binomial distribution (NBD) implies that the most effective advertising requires media that reach across both heavy and light buyers of the brand. This article investigates the buying concentration of the Facebook Fan base of two different brands (both Fast Moving Consumer Goods (FMCG) categories) and compares it to the brands’ actual buying bases. The buyer base of each of
the brands is distributed in the typical NBD, whereas the Fan base delivered by Facebook is skewed in an opposite pattern—skewed toward the heaviest of the brands’ buyers— making the quality of Facebook’s reach appear rather unappealing.

Can you use facebook to stimulate your fans to talk about you?

Since the Advertising Age covered the Ehrenberg-Bass Institute’s analysis of facebook’s ‘talking about’ metric there has been a flurry of internet coverage.

The findings got reduced to a sound bite of “only 1% of facebook fans engage with brands”. Which could easily be misinterpreted. Dr Karen Nelson-Field’s result is actually that around 0.4% (ie less than one percent) of the fans of a brand actually interact with it on facebook in a typical wek.

The interaction is what facebook report as “Talking about’, and includes activity such as to like, comment on or share a Brand Page post (or other content on a page, like photos, videos or albums), post to a Page’s Wall, answer a posted question, liking or sharing a check-in deal, RSVP to an event, mention a Page in a post, phototag a Brand Page…all the activity that facebook measure.

Now 0.4% in a week doesn’t sound so bad. It sounds like it might cumulate to near 25% in a year, but this would be a heroic assumption. In these sorts of social phenomenon we usually see highly skewed distributions. There will be a small percent of fans who do most of the talking every week. So this probably cumulates to something much less than 10% in a year. Karen is investigating.

Even facebook’s own fans don’t talk much about facebook (on facebook)

One of the questions asked of Dr Karen Nelson-Field’s analysis of facebook fans engagement with their brands on facebook is whether the result is simply due to slack social marketing by the brands in question.

Given that Karen analysed the 200 brands with the most facebook fans it seems a bit of a stretch to say that these brands “don’t understand facebook”.

Some have speculated that brands that understand passionate loyalty probably do much better.  But Karen’s analysis included brands such as Old Spice, Harley-Davidson, Ferrari, and Tiffany & co.

Finally, Karen’s analysis included facebook’s own facebook fans.  In a typical week only 0.28% ‘talk about’ facebook on facebook.  Maybe facebook itself doesn’t care much about fan engagement, after all they are clever marketers.

Digital Age Branding – You are spending your money in all the wrong places – or maybe not

I’ve written before about the army of consultants crying
“consumer behaviour has changed radically”
“marketing doesn’t work anymore”

Who then present nothing more than a repackaging of the orthodoxy. e.g. see my comment on Seth Godin’s “Purple Cow”.

There are many marketing assumptions that need to be changed. Yes, practice can be improved. So by all means let’s talk about this, but anyone advocating specific changes should offer supporting evidence, from serious research.

Harvard Business Review recently published a fairly shameless advertorial for McKinsey’s which makes the mundane observation that the digital age has meant some changes in how consumers learn about and buy brands. The article is all hype and assertion, based apparently on McKinsey ‘research’ that has produced results like “60% of consumer facial skin care products now conduct online research on the products after purchase”. Does anyone believe this ? I’d love to see an independent replication.

They boldly announce that advertisers are spending their money in all the wrong places. Gasp, how terrible. Where’s the evidence ?

They write things like “up to 90% of spend goes to advertising and retail promotions. Yet the most powerful impetus to buy is often someone else’s advocacy”. So what is the implication ? That we should spend more money on stimulating word-of-mouth, fine but research shows that advertising is the major stimulus for brand word-of-mouth (1), so that gets us back where we started.

They present a “NEW” model of the consumer decision making process, that starts with consideration, then evaluation, buying, then hopefully enjoying, advocating, bonding and repeat-buying. It’s a terrible rational, highly involved model, just as Howard & Sheth’s original one was back in 1969 (2). Yes with an audacious straight face they present this as new thinking. Their main thesis is that marketers need to consider all these stages and gain touch-points at each. 20 years ago my colleagues Caroline Rowe and David Corkindale presented a near identical idea, they considered it a useful teaching tool, nothing more.

McKinsey go much further to claim that marketers’ advertising spends are commonly hitting people at the wrong times. But they give no evidence. They seem to assume that advertising has no memory effect. There is an in-built assumption that hitting someone at the moment when they are thinking about the brand/category is the only advertising that works.

And they write as if search advertising doesn’t exist. As if marketers don’t already offer ways for consumers to access their brands during active search.

As I said, a fairly shameless advertorial for McKinsey’s services in social media advertising, which could be excused if only they offered some new insight.

References:

(1) Keller, E., & Fay, B. (2009) “The role of advertising in word of mouth”, Journal of Advertising Research, 49(2), 154-158.

(2) Howard, J. A., & Sheth, J. N. (1969) “The Theory of Buyer Behavior”, New York: John & Wiley Sons, Inc.

Other reading:
Jamhouri, O., & Winiarz, M. (2009) “The enduring influence of TV advertising and communications clout patterns in the global marketplace”, Journal of Advertising Research, 49(2), 227-235.

Rubinson, J. (2009) “Empirical evidence of TV advertising effectiveness”, Journal of Advertising Research, 49(2), 220-226.

Don’t limit your advertising to the heavy swing purchaser segment – all category buyers matter

Jack Wakshlag (Chief Research Officer of Turner Broadcasting) asked me to comment on a finding from TRA that the largest advertising sales response comes from a group of consumers TRA call “Heavy Swing Purchasers” – who are defined as “category heavy purchasers who have bought the brand previously, but not loyally”.

My comment is in light of what is known about how brands grow, and how advertising affects sales (thanks to 40+ years of single source based research).

Promotional literature from TRA reports a repeated finding that “Heavy Swing Purchasers” buy the brand more in response to advertising And even more importantly it is a large segment, so 80% of incremental sales come from this group – after all, ROI is a dumb marketing metric, it’s total response that matters.

The TRA finding fits with a known empirical generalisation that the largest sales uplift come from the brand’s lightest buyers, who are by far the brand’s largest group of customers. By the way, the same happens when TV shows increase their ratings, it’s largely because the program’s most infrequent viewers watch slightly more often.

The only twist here is that TRA don’t just say “light buyers of the brand” but “light buyers of the brand who are also heavy category buyers”. I suspect, however, that they merely mean people/households who buy the category more often than the average person. I hope so because category buying rates follow a skewed (Gamma) distribution with most buyers buying less often than the category average. This means that any brand’s lightest buyers are made up of two groups:

1) there are people who buy the category often but that particular brand is small within their repertoire – these are the easiest to nudge (and gain sales from), i.e. high ROI.
2) there are people who don’t buy the category very often, so even if the brand is quite large within their repertoire they don’t buy it often.

This second group matters too. Especially in the long term.

They matter a lot for market share growth. One of the things that distinguishes large brands from small is that a greater proportion of their customer base is made up of light category buyers (see ‘Natural Monopoly Law’ page 97). Ignoring these people might boost your advertising ROI, but will prevent you from moving to a higher market share position.

Professor Byron Sharp, June 2011.

American marketers can now see the real sales effect of their advertising

Single source (longitudinal, individual level) data is now available in the USA, showing buying and TV advertising exposure.

This is terribly exciting, because this data can, with careful analysis, provide a high quality quasi experiment. That is, without the effort and expense of devising a controlled experiment you can use this live market data to give you the same experimental outcome. You do it by sorting category purchases into those that were preceded by no recent exposures to your advertising and those that were (and further divide these into 1-exposure, 2-exposures etc). Then you simply compare your brand’s share of these different groups of purchase occasions to see the real sales strength of your advertising. Your brand’s share, of course, should be higher amongst purchase occasions that were preceded by your advertising!

This is vastly more trustworthy than trying to achieve the near impossible and quantifying the sales effects of a particular ad using a statistical analysis of aggregate time series data. It’s also much faster, you don’t have to wait a year before finding out what the effect of last year’s advertising was supposed to have been.

TRA and Nielsen Catalina Solutions are two companies that currently offer single-source data by overlapping data from buying panels and TV viewing panels (i.e some households are in both). NCS also monitors on-line and mobile media exposure.

These data let you identify which ads work better so you can drop non-performing ads and drastically improve the effectiveness of your advertising. And you can use this sales effectiveness data to learn how to make better ads.

And you can measure how much incremental effect is gained by additional recent exposures, i.e. is bunching exposures worth it ?

And whether ads work better in different contexts, on different channels, in different pod positions. There is so much valuable information that can be learned once the true sales effect of advertising is known. Much R&D needs to be done.  The potential to improve the sales effectiveness of TV advertising is immense.