Do consumers really understand “native advertising” labeling?

There’s no question that “native advertising” – paid editorial content – has become a popular “go-to” marketing tactic. After all, it’s based on the time-tested notion that people don’t like advertising, and they’re more likely to pay attention to information that looks more like a news article than an ad.

Back in the days of print-only media, paid editorial placements were often labeled as “advertorials.” But these days we’re seeing a plethora of ways to label them – whether identified as “sponsored content,” “paid posts,” or using some kind of lead-in descriptor such as “presented by …”

Behind all of the verbal gymnastics is the notion that people may not easily distinguish native advertising from true editorial if the identification can be kept somewhat euphemistic. At the same time, the verbal “sleight of hand” raises concerns about the obfuscation that seems to be going on.

These dynamics have been tested. One such test, conducted several years ago by ad tech company TripleLift, used biometric eye-tracking to see how people would view the same piece of native advertising, that carries different disclosure labeling.

The results were revealing. Here are the percentages of participants who saw each ad, based on how the content was labeled:

  • Presented by” labeling: ~39% saw the content
  • “Sponsored by” labeling: ~29%
  • “Promoted by” labeling: ~26%
  • “Brought to you by” labeling: ~24%
  • “Advertisement” labeling: ~23%

Notice that the content that was labeled “advertisement” was noticed the least often. This provides yet more confirmation that people ignore ads.  When advertisers used softer/fuzzier terms like “presented by” and “sponsored by,” they achieved a bigger lift in the content being noticed.

It comes as little surprise that those same “presented by” and “sponsored by” labels are also the most potentially confusing to people regarding whether the item is paid content. And when people find out the truth, they tend to feel deceived.

Members of the Association of National Advertisers look at it the same way. In an ANA survey of its members conducted several years ago, two-thirds of the respondents agreed that there should be “clear disclosure” of native ads – even if there’s a lack of consensus regarding who should be responsible for the labeling or what constitutes “clear” disclosure.

Asked which labeling describes native ad disclosure “very well,” here’s what the ANA survey found:

  • “Advertisement”: 62% say this labeling describes native ad placements “very well”
  • “Paid content”: 37%
  • “Paid posts”: 34%
  • “Sponsored by”: 31%
  • “Native advertising”: 12%
  • “Presented by”: 11%
  • “Promoted by”: 11%
  • “Branded content”: 8%
  • “Featured partner”: 8%

Considering that the findings are all over the map, it would be nice if a universal method of disclosure could be devised. But the language that’s agreed upon shouldn’t scare away readers, since in so many cases native advertising isn’t directly pitching a product or service.  Labeling such content “advertising” would be as much of a misnomer as failing to divulge the company paying for the placement.

My personal preference for adopting consistent labeling language among the options above would be “Sponsored by …”  What’s yours?

Good news: Online advertising “bot” fraud is down 10%. Bad news: It still amounts to $6.5 billion annually.

Ad spending continues with quite-healthy growth, being forecast to increase by about 10% in 2017 according to a studied released this month by the Association of National Advertisers.

At the same time, there’s similarly positive news from digital advertising security firm White Ops on the ad fraud front. Its Bot Baseline Report, which analyzes the digital advertising activities of ANA members, is forecasting that economic losses due to bot fraud will decline by approximately 10% this year.

And yet … even with the expected decline, bot fraud is still expected to amount to a whopping $6.5 billion in economic losses.

The White Ops report found that traffic sourcing — that is, purchasing traffic from inorganic sources — remains the single biggest risk factor for fraud.

On the other hand, mobile fraud was considerably lower than expected.  Moreover, fraud in programmatic media buys is no longer particularly riskier than general market buys, thanks to improved filtration controls and procedures at media agencies.

Meanwhile, a new study conducted by Fraudlogix, and fraud detection company which monitors ad traffic for sell-side companies, finds that the majority of ad fraud is concentrated within a very small percentage of sources within the real-time bidding programmatic market.

The Fraudlogix study analyzed ~1.3 billion impressions from nearly 60,000 sources over a month-long period earlier this year. Interestingly, sites with more than 90% fraudulent impressions represented only about 1% of publishers, even while they contributed ~11% of the market’s impressions.

While Fraudlogix found nearly 19% of all impressions overall to be “fake,” its fraudulent behavior does not represent the industry as a whole. According to its analysis, just 3% of sources are causing more than two-thirds of the ad fraud.  [Fraudlogix defines a fake impression as one which generates ad traffic through means such as bots, scripts, click-farms or hijacked devices.]

As Fraudlogix CEO Hagai Schechter has remarked, “Our industry has a 3% fraud problem, and if we can clamp down on that, everyone but the criminals will be much better for it.”

That’s probably easier said than done, however. Many of the culprits are “ghost” newsfeed sites.  These sites are often used for nefarious purposes because they’re programmed to update automatically, making the sites seem “content-fresh” without publishers having to maintain them via human labor.

Characteristics of these “ghost sites” include cookie-cutter design templates … private domain registrations … and Alexa rankings way down in the doldrums. And yet they generate millions of impressions each day.

The bottom line is that the fraud problem remains huge.  Three percent of sources might be a small percentage figure, but that still means thousands of sources causing a ton of ad fraud.

What would be interesting to consider is having traffic providers submit to periodic random tests to determine the authenticity of their traffic. Such testing could then establish ratings – some sort of real/faux ranking.

And just like in the old print publications world, traffic providers that won’t consent to be audited would immediately become suspect in the eyes of those paying for the advertising.  Wouldn’t that development be a nice one …