Internet has a major role on our society.
Advertising has a major role on the Internet
In other words, Advertisers money fuels web sites that have a major role on our Society. We already know the impact on elections, but is it limited to it?
Advertisers to publicly list where they advertise.
In France, to fight hate speech, Senators passed an amendment in mid-December 2019 on a law named “Avia law” requiring brands to know where their online advertising campaigns are running and to keep a public list of those sites.
Programmatic advertising could be impacted.
Discussions were held on how to make online advertising actors, in particular brands and their agencies, responsible for the financing of illegal content. An amendment by MP Eric Bothorel (withdrawn for now), provided for penalty of up to one year’s imprisonment and a fine of up to EUR 250 000 against advertising brands, their agency representatives and advertising service providers if their advertisements are purchased on sites whose hateful nature has been determined as such by a court decision.
According to The Guardian this French law “could be copied across Europe.”
Helping publishers and advertisers.
On Tuesday, December 17th 2019, the French Senate did adopt a modified version of the original bill:
The new text stipulates in particular that “advertisers shall publish online and keep up to date at least monthly the information relating to the places where their advertisements are placed which are communicated to them by sellers of advertising space on the Internet, pursuant to Article 23 of Law No. 93 122 of 29 January 1993″ (known as the Sapin Law, editor’s note).
Using an AI-powered media profiling 3rd party.
To be efficient, media profiles cannot be self-declared by media themselves. The profiling process must be transparent, unbiased, universal and always up-to-date with the current context.
TrustedOut provides those informations on Media, Sources and/or Articles:
1. To the buyers of ad space.
Say ACME wants to run an ad campaign on media covering the Aerospace and Defense Industry in France.
The corpus will look like this:
Profiling, reporting and updating every month those 90 media, 171 sources, 2+k articles a day, can be cumbersome and open to mistakes.
Instead, TrustedOut produces those reports on a media, say here “Lignes de Defense”, showing toxic profiling, such as Hate news, but also Political orientations and the sources qualifying for the campaign.
In this report, and over the past 30 days, the media and all its sources have covered the following classifications:
ACME, the advertiser, combines the white list of its campaign and the reporting desired by the coming laws.
2. To the sellers of ad space.
Lignes de defense can produce a report solely focused on its media with all combined sources, or a report per source.
In addition, Lignes de defense can dig into each article it publishes and view how the article is profiled.
We do encourage to (re)read the 2 posts on article classifications sensing Editorial Orientations
The need for a new source of intelligence in targeting
Advertisers want a perfect targeting for their campaigns. With the end of 3rd party cookies, Advertisers will have to rely on other sources of intelligence to target the perfect page for ad insertions.
No self-declaration. No bias.
TrustedOut is totally independent from any preset lists and is entirely powered by AI using countrywide published content. This guarantees our content profiling to be unbiased, universally able on any matter and always up-to-date. We do NOT use any self-declared data coming from anyone. We listen, profile. All the time.
Dialect detection means no dependence on keywords.
How can you, for example, target the Healthcare Industry? With a list of keywords? Who did it? Is it up-to-date?… Hard to manage. Instead TrustedOut listens and profiles everything published and keeps on learning the words and expressions, the “dialects” (or “bags of words”), for each and every classification. This way, the definition of “Healthcare, in our example, always captures the words and expressions used for this targeting. No worries. No lists, potentially biased and out-dated. You are covered. Always.
Profiling Intelligence must be at insertion time.
Content perception varies upon time. A page/an article can be perceived primarily in one classification and, over time, in another one. In this example, we see first “Employment” at publishing time and 3 weeks later, “Seniors”. Same with the dialect words and expressions, it all evolves over time which is key for a perfect targeting.
For the Publisher:
The need for a precise, external and unbiased product pulse.
Like any business, publishers need a trustworthy, unsolicited, unbiased look at what they publish. This goes for articles, feeds/sources and the whole media (distinct domain). Not only this is critical to pilot a business but also to compare with others.
The end of self-declarations for special ops.
TrustedOut provides always-up-to-date profiling of a section or the whole of a media. It also provides trends which can be compared. The end of self-evaluations, self-declarations for a more trusted relationship with your sponsors and commercial partners.
Editorial trends and KPI measurement.
TrustedOut profiles published and exposed content. All of it and at all time. This means measuring editorial trends and positioning. Amongst a media and across a market, a region or a country. Mapping Editorial trends pictures how one reacts to a matter in depth and in time. Finally, it also measures performances and the balance of demand/delivery.
For the Brand Manager:
Brand Consistency Builds Brand Awareness
Marketers know Brand Consistency is key to build and keep awareness and credibility. To keep brands consistency, brands must be totally safe and not appear in an environment not consistent with its values. TrustedOut allows Marketers to define the content appropriate for their brands and get corresponding Whitelists where to deliver the right communication.
Consistency, inside and outside.
Branding is not reserved to marketers. Everyone within an organization, employees, board members, partners and, of course, customers and prospects should all have access to a curated list of sources related to the brand.
Consistency in PR goals and measurements.
Direct your PR efforts to where you want your brand to be and use our instant profiling to measure evolutions and progresses. Define KPIs with your PR departments and measure your ROI on a classification, a perception, a competition.
For the Analyst:
Must trust the Content in to trust the decisions out.
The mandatory first step in any analytics is to trust the content/data you are going to analyze. If you do not, results will be unreliable and worst, decisions you are going to make might be dangerous and disastrous to your business and brand. Bottom line: if no trust in, then no Trust Out.
Who reacts to what, and how.
Analyze how an event, product launch or local news, are classified and where. A great source of insights on how to prepare for a new launch or positioning.
Watching the future.
Industries keep on evolving. Be on alert about what technology is popping up, how it is received amongst content oriented, political or else, and where it is happening.
For content selection: AI-powered classifications can sense Editorial Orientations AND Evolution over time. Keywords cannot.
For years, access to knowledge was all about the presence or absence of keywords to trigger the selection of content: A 1-dimensional access, keywords based, to knowledge. Linear. Limited to 0 (absent) or 1 (present).
Last week, we covered the first advantage of AI-Powered Classifications vs keywords based selection, Editorial Orientations, and showed how the same event, on 3 different publications can have different Editorial Orientations.
This is an additional dimension to access knowledge.
Let’s now have a look at a 3rd dimension: Sensitivity over time.
Perception of an event evolves with time, so do our AI-Powered classifications.
France has been through a lot of social movements with the pension reform the French government is pushing for.
From the beginning of the protests until now, the perception has evolved.
Let’s look at the same article and how AI classifies it at two different times.
We are at the beginning of the movement, Employment and Unemployment is the top classification.
On Dec 31st, top classifications are now:
3 weeks later, the very same article with the very same content is classified as Senior first, then Social Assistance and, now in 3rd, Employment and Unemployment
Clearly, after 3 weeks of protests, Aging and Social are topping the Employment dimension.
How can AI-Powered Classification do this?
In a previous post, we explained how our AI worked:
Which means the day the article is published, we use Classifications Datasets (aka bags of words) on that very day.
Classification Datasets are also updated to sync with every single classification and sense the depth of expertise over time. This means some words can be in and out and with a different weight over time. This means classifications are set, by default, for the day an article is published but can be re-run on a different day and produce a different classification. Like in real life, your perception of something evolves with time.
Why it matters.
Simply because time is a vital dimension of perception.
Simply relying on the presence of keywords to select content for analytics, expose your brand via advertising etc… is dangerous.
What’s true at publication time might not be at analytics time, or advertising time…
In the example above, you may or may not want articles about “Seniors”. At publication time, the article was under the radar, 3 weeks later it is classified as “Seniors”. Is it still where your brand wants to be exposed? are those content the one you want to analyze today? do those articles matter for the education of your teams?
Relying on keywords that are present in content forever, not only does not give you the orientation of the content but is not sensitive to the evolution of perception. And as we know, in Marketing:
For years, access to knowledge has been ruled by keywords presence. Search engines, corpus selection for business intelligence, DSPs for online advertising, Brand Safety, Watch alerts…
All is about the presence or absence of keywords to trigger the selection of content: A 1-dimensional access, keywords based, to knowledge. Linear. Limited to 0 (absent) or 1 (present).
Keywords presence does not sense angles, subtlety and orientations taken by the author (nor the sensitivity over time. Today’s meanings are the same any other day).
For example, the presence of “Christmas gift” might be “ok” but is it in a context of “Military defense” and “Weapon”? Can you maintain queries excluding all related, always evolving dictionaries of synonyms and be sure your brand won’t be exposed?
After all, a word can have several meanings depending on its context and the time it is read. AI-Powered Classifications are the solution:
AI-Powered Classifications are adding 2 more dimensions: Editorial orientations and timing context.
Today, we will focus on editorial orientations detection.
Next week, we will explain the sensitivity to the time of publication.
Both, AI-Powered Classifications and keywords based selections are unbiased, universal and up-to-date. Because TrustedOut is AI-Powered, our machine learning guarantees the same non-humain, machine powered benefits.
1 General › Politics › Diplomacy
2 General › Politics › International
3 Industries › Aerospace And Defense › Weapon
4 General › Politics › Military Defense
5 General › Politics › Civil Defense
6 Industries › Energy › Nuclear Power
7 Industries › Aerospace And Defense › Naval System
8 General › Politics › Administration
9 Industries › Aerospace And Defense › Aerospace Systems
10 General › Politics › Government
1 General › Politics › Diplomacy
2 Industries › Aerospace And Defense › Weapon
3 Industries › Aerospace And Defense › Aerospace Systems
4 Industries › Aerospace And Defense › Missiles And Rockets
5 General › Politics › International
6 General › Politics › Military Defense
7 People › Society › Opinion And Idea
8 Industries › Aerospace And Defense › Satellite
9 General › Law › International
10 Industries › Aerospace And Defense › Aircraft
Editorial Angles
Here’s a summary of the classifications for the 3 articles:
A few remarks:
USAToday and Le Figaro top classification is Diplomacy. CBSNews is Military Defense
The 2 US articles have the same top 4. (in a different order)
Le Figaro does not have Nuclear Power in its Top 10
All have Military Defense. Only USAToday has Civil Defense
All have Aerospace and Defense > Weapon in their top 3
Only Le Figaro has Society > Opinion and Idea and Law > International in its top 10
For Industry > Aerospace and Defense, USAToday has 3, CBSNews has 4, Le Figaro has 5 out of their Top 10.
Here’s how TrustedOut saw the Aerospace and Defense Industry, back in October:
How AI-Powered Classifications are sensitive to the time of publication: Meaning, Classifications evolve with the time as our “bag of words” are permanently updated and why it matters… Continue to part 2/2
“…every time a person loads a page on a website that uses real-time bidding advertising, personal data about them are broadcast to tens – or hundreds – of companies. Here is a sample of the personal data broadcast.
● What you are reading or watching
● Your location (OpenRTB also includes full IP address)
● Description of your device
● Unique tracking ID or a “cookie match” to allow advertising technology companies to try to identify you the next time you are seen, so that a long-term profile can be built or consolidated with offline data about you
● Your IP address (depending on the version of “RTB” system)
● Data broker segment ID, if available. This could denote things like your income bracket, age and gender, habits, social media influence, ethnicity, sexual orientation, religion, political leaning, etc. (depending on the version of “RTB” system)”
“We used to read the newspaper, now the news reads us.”
This quote from the Global Editors Network. We strongly encourage you to read the article using the quote as a title and try the section “What happens when you read an article online”. Below is a screenshot for Spiegel.de
1 out of 5 happy for their data to be shared (UK, 2017)
In 2017, GFK was commissioned by IAB Europe (the AdTech industry’s own trade body) to survey 11,000 people across the EU about their attitudes to online media and advertising. GFK reported that only “20% would be happy for their data to be shared with third parties for advertising purposes”. [source]
Finding#1: Removing 3rd party tracking/AdTech and investing in Context increases revenue!
NPO and its sales house, Ster, invested in contextual targeting and testing, and produced vast sales increases even with sites that do not appear to dominate their categories.
The Covid-19 market shock shifted the market from video to display
Finding#2: “legitimate publishers of all size can increase revenue”. The New York Times example…
On their site, Open.nytimes.com, they wrote: “As of April 2019, we [The New York Times] removed all third-party data controllers from our homepage, section fronts and articles. … This reduced the amount of data we shared with third-party data controllers by over 90 percent. We are working on ways to improve this number…”
Finding#3. “Context is powerful.”
“NPO properties now provide no geotagging, no frequency capping, and no cross device measurement. Despite the absence of these features, extensive testing with advertisers has proven that the ads are effective, and advertisers are spending more with NPO than before.”
“Contextual relevance is preferred across all verticals
When shown articles representing different verticals, consumers were consistent: they always preferred contextual relevance. Across the board, consumers paired the advertisements they prefer with articles categorized in the same content vertical.”
The picture above shows the majority of consumers prefers to have ads relevant to the content where they are inserted.
It does make sense to avoid any opposition or distraction from the content.
Profiling makes content relevant.
TrustedOut’s Holistic Profiling works like this:
Which means, not only the content where the ads will be inserted is classified and gauged in expertise but the Perception and the Orientation of the Media of insertion are also gauged.
Ex: How it applies to Entertainment:
No more unmanageable, biased, irrelevant over time keywords
With TrustedOut, Classifications in our taxonomy define a Vertical.
For Entertainment, for example, brand classification “Entertainment & Leisure” comes to mind. But then, why not Information and Communication with its Motion pictures, Online Media, etc… and then why not Culture and Arts with its Arts, Comics, Dance… and then what about content about Eating and Drinking?…
Geo: USA, As of 2020/08/28
Why it matters?
No dependance of unmanageable, irrelevant over time lists of keywords.
TrustedOut qualifies every piece of content at the moment of use. Expressions and their weight are permanently updated.
An amazing opportunity for greater context relevancy.
In our example above, adjust ad messages to the type of Entertainment. Greater context relevancy, greater approval from the customer!
Relevant… and safe!
Now that context is relevant, but…
… is the publisher of this content spotted as Fake News, Junk Science, Conspiracy Theory, Revisionism or Hate News?
… is the publisher politically oriented? Religiously oriented? Humorous/Satirical?
Say you are looking for Entertainment in the largest sense as shown above but you don’t want publishers spotted with toxic content, not far right or far left and not humorous/satirical. No filter on Religion.
We are delighted to introduce within our Customer User Interface, a new feature coming from the feedback we’ve collected:
“How to get a daily report on the Corpus I’m using for an ad campaign or analytics on a product launch?”, “I want to share this report with my management, so no learning curve, must be straight forward”
Well, here it is. In the Customer UI, there is a new “Report” button. At any time you can get a PDF of what your Corpus is made of and share it amongst your team or/and client for review or approval.
Brand Safety Surveillance.
Let’s take an example: You are running an ad campaign to get traffic to a page. TrustedOut analyzes the destination page and build the following Corpus for this campaign:
Content must be French for France
Media must have covered “Society” AND talk about “Digital Life” over the past quarter to get stable classifications
Corpus looks like this:
A click on the “Report” button will give you this PDF:
Click on the button to get the report
Fine tuning your Corpus to get the desired Report
At all time you can tweak your Corpus to correct things you don’t like in the Report.
For example, page 29 shows:
… and you don’t want:
Toxic content
You can tolerate Politics but don’t want Far Right, nor Far Left
You’re ok with Religions and Humorous/Satirical
Then, change your Corpus definition to:
Next: Connect your Corpus to your DSP. (Spoiler alert: Blog post coming soon :))
Analytics Perimeters Watch
Controlling and sharing the Corpus you use for your analytics is critical.
After all, trusting decisions you are going to make impose to share the content you use to make your analytics and thus the decisions from those.
(reminder: the name TrustedOut comes from “If it’s not Trusted In, it cannot be Trusted Out”)
To pursue with our example above, the Report shows on page 9 the trends of your Corpus over time:
Now, say you don’t want to use, for any reason, media talking about Preschool and Primary Schools:
Simply change your Corpus definition with the addition line:
And now, Trends look like this:
Get management and clients involved by sharing Corpuses!
How to avoid some context?
Keywords vs Classifications bans.
Both methods are compatible and serve different purposes.
Keywords bans avoid specific words presence at the page level.
Pros: Very targeted and at the page level. Avoid a competitor brand, a named reference like a city or someone…
Cons: Got to be very specific on those keywords as they do not handle nicknames or synonyms, just to name those two. This generates very long lists to ensure safety and those long lists may be biased, outdated and prevent you from context you might indeed desire.
Classifications bans avoid specific associations to your brand at the Media/Source level.
Pros: No need to worry about new terms as bag of words for a classification are permanently updated. Words/expressions get in and out. Automatically. This is critical if you don’t want some risky associations to your brand.
Cons: This will not work to avoid specific words or brands where keywords ban is a better option.
An example? Want to be associated with Wellness, but not with Disease?
Your brand wants to be exposed in Wellness publication but not those associated with Diseases (like Covid).
For demonstration purposes here, we’ll focus on a small list of publications to easily identify differences.
Corpus will be made of:
Media in America and in English
Media Taxonomy is Wellness > Specialized > over the past week
This gives us 11 Media.
Now, you want to avoid Media with those 11 that do Cover Diseases. Your corpus becomes:
10 Media left. One is gone which you can look at by changing IS NOT to IS in the Disease condition and find:
Let’s double check with TrustedOut’s profile over the past week:
