“Why customer trust is more vital to [media] brand survival than it’s ever been”

We recently wrote in the post below:

“Your Trust is based on the publisher brands you value.”

TrustedOut’s market

Because Trust and brands are so linked, including for Media, we wanted to share our takeaways from this CMO (Chief Marketing Officer) article “Why customer trust is more vital to brand survival than it’s ever been” [article applies beyond Australia].

Authenticity is key to trust, so how do [media] brands build this in a world of digital and social upheaval?

“Simply saying a brand is going to do something, without backing it up with actions, is a consumer disaster waiting to happen.”

“It’s about being transparent, doing what is expected and shared values. Key to this is the internal culture of the brand becoming more evident,” she [Qualtrics customer experience subject matter expert and principal consultant, Vicky Katsabaris] says. “The expectation is you deliver to those values with more purpose-driven activities so you are living and breathing the values.

Gaining trust: demonstrate [media] brand clarity of purpose and core values and be transparent with all policies and procedures.

“Board and staff members need to adhere to these ethical standards as, in effect, they are the brand and only they can elicit consumer trust,” he [Director of brand agency Hulsbosch, Jaid Hulsbosch] says.

To do this, a corporation and its brand needs to be determined to demonstrate brand clarity of purpose and core values and be transparent with all policies and procedures”

2019 predictions.

This confirms our predictions for 2019…

Top 2019 predictions: Privacy and Transparency

…  and confirms the uptrend in trust in media lately.

 

 

 

The decline of local newspapers impact on democracy.

 

A recent study published in Oxford’s Journal of Communication (and available here) shows some very interesting links between the impact of losing a local newspaper and the increase of bipartisan (left or right) votes. Here are our takeaways:

Newspaper Closures Polarize Voting Behavior

Missing local news has a negative impact on political outcomes

“Local news sources are not merely suffering in this new marketplace—many are disappearing for good (Hindman, 2009; Shaker, 2014). As newspapers close, other local media are not emerging to fill the information gaps, with negative impacts on important political outcomes”

Less local news, less regard on local politics.

“Another emerging literature details negative consequences of declining local news. Where local newspapers are weaker, people know less about their representatives and subnational governments and turn out at lower rates (Hayes and Lawless, 2015, 2018; Kübler & Goodman, 2018; Shaker, 2014), and municipal governments spend less and borrow at higher rates (Gao et al., 2018; Yazaki, 2017). ”

The Nationalizing Media Environment and Political Polarization

Less news opinions creates more, national-based, bipartisan decisions

“Declining access to quality local news is harmful to voter behavior and responsive governance, leading to more corruption (Arnold, 2004; Besley, Burgess, & Prat, 2002; Campante & Do, 2014; Strömberg, 2004) and lower voter turnout (Schulhofer-Wohl & Garrido, 2013). In the absence of quality local news options, Americans may rely on partisanship and national news to inform their political decisions (Hopkins, 2018; Trussler, 2018).” A relative reduction of local news in the media marketplace may result in less exposure to local news and more regular exposure to national media, with significant effects on engagement and partisan voting (Clinton & Enamorado, 2014; Hopkins & Ladd, 2014; Hopkins, 2018).

When a local newspaper closes, split-ticket voting decreases by 1.9%.

[Split-ticket voting refers to when a voter in an election votes for candidates from different political parties when multiple offices are being decided by a single election, as opposed to straight-ticket voting, where a voter chooses candidates from the same political party for every office up for election. – Wikipedia]

Less local news mix local and national matters.

“Our findings connect the literature on the polarizing effects of the changing news environment to scholarship on the negative democratic consequences of the decline of local news: just as adding the internet or partisan cable news to the media environment can influence voting behavior, removing a local news source from the marketplace may polarize the choices citizens make”

So, now, what?

We wrote on Jan 17th, the post below announcing Google, Facebook, and now the Knight Foundation have reach a whooping $1B financial support quality journalism and for local news…

Saving journalism. [updated 2/19/19]

Also, on Feb 11th, we published this:

Trust, Media and Democracy

Why it matters to us

Quality journalism is mandatory for democracy and vital to Media brand values. The foundation of TrustedOut Media profiling  to provide sources Analysts will define as their need and trust in Business Intelligence, Advertising and PR.

Questions? Shoot!

Presentation to the GESTE (major online editors in France)

We were very proud to be invited to present at the latest GESTE (major online editors in France) event about “Trust and labelization“.

The presentation.

Click to run presentation

 

The Table of Content.

The problem:
Distrust in media.

The consequence:
In decision-making, only what is trusted in can be trusted out.

The point:
Distrust is general, trust is personal. No universal list.

The logic:
Trust is about reputation. Media Brands are about reputation.

The solution:
Industrial Profiling Media Brands.

The application:
Easy querying, live feeding.

The technology:
Machine learning, Web crawling, big data and microservices to self-feed, self-grow and daily validations

Our live taxonomy:
Permanent machine learning, customizable sensitiveness & specialty depth,
enterprise mapping.

The opportunity:
BI, Ads & PR

Question? shoot!

 

Get information from Traditional Media, have conversation on Social Media. Not the other way around.

Misinformation and biases infect social media, both intentionally and accidentally

This highly recommended article from The Conversation exposes 3 types of bias identified by Indiana University. Hereafter are our takeaways.

1/ Bias in the brain

More information means less quality content shared

“Cognitive biases originate in the way the brain processes the information that every person encounters every day. The brain can deal with only a finite amount of information, and too many incoming stimuli can cause information overload. That in itself has serious implications for the quality of information on social media. We have found that steep competition for users’ limited attention means that some ideas go viral despite their low qualityeven when people prefer to share high-quality content.”

Beware emotions in headline trap

“One cognitive shortcut happens when a person is deciding whether to share a story that appears on their social media feed. People are very affected by the emotional connotations of a headline, even though that’s not a good indicator of an article’s accuracy.”

What matters is where it’s coming from.

“Much more important is who wrote the piece.”

TrustedOut foundation: profile who’s behind to evaluate your trustworthiness appreciation and the path to greater trust in media:

Optimism and method for greater trust in media.

2/ Bias in society

Like seeks like (“Birds of a feather flock together”)

“When people connect directly with their peers, the social biases that guide their selection of friends come to influence the information they see. …social networks are particularly efficient at disseminating information – accurate or not – when they are closely tied together and disconnected from other parts of society.”

“Us vs Them”

“The tendency to evaluate information more favorably if it comes from within their own social circles creates echo chambers that are ripe for manipulation, either consciously or unintentionally. This helps explain why so many online conversations devolve into “us versus them” confrontations.”

We are right. Distrust in fact-checking

“…during the 2016 U.S. presidential elections [analysis] shows that Twitter accounts that shared misinformation were almost completely cut off from the corrections made by the fact-checkers. When we drilled down on the misinformation-spreading accounts, we found a very dense core group of accounts retweeting each other almost exclusively – including several bots. The only times that fact-checking organizations were ever quoted or mentioned by the users in the misinformed group were when questioning their legitimacy or claiming the opposite of what they wrote.

3/ Bias in the machine

Getting more of the same. Accurate. Or not.

“The third group of biases arises directly from the algorithms used to determine what people see online. Both social media platforms and search engines employ them. These personalization technologies are designed to select only the most engaging and relevant content for each individual user. But in doing so, it may end up reinforcing the cognitive and social biases of users, thus making them even more vulnerable to manipulation.”

Illusory truth effect. Repeat until it feels true.

“For instance, the detailed advertising tools built into many social media platforms let disinformation campaigners exploit confirmation bias by tailoring messages to people who are already inclined to believe them. Also, if a user often clicks on Facebook links from a particular news source, Facebook will tend to show that person more of that site’s content. This so-called “filter bubble” effect may isolate people from diverse perspectives, strengthening confirmation bias.”

Popularity bias. More clicks makes it feel more true.

“Another important ingredient of social media is information that is trending on the platform, according to what is getting the most clicks. We call this popularity bias, because we have found that an algorithm designed to promote popular content may negatively affect the overall quality of information on the platform. This also feeds into existing cognitive bias, reinforcing what appears to be popular irrespective of its quality.”

Get information from Traditional Media, have conversation on Social Media. Not the other way around.

Unsurprisingly, and somewhat reassuring, numbers from Reuters/Oxford (hereafter for the US) show trust in social media are the lowest with 13% vs 34% for news overall and the highest at 50% with News/Media I use. (we developed this with this post “While distrust is general, trust definition is personal.“)

Related posts:

Saving journalism. [updated 2/19/19]

Top 2019 predictions: Privacy and Transparency

TrustedOut’s market

Questions? Comments? Contact us!

 

 

Older people share more fake news.

Age predicts behavior better than any other characteristics (even party affiliation )

Researchers at New York and Princeton Universities, through their recent surveys, are saying older users shared more fake news than younger ones regardless of education, sex, race, income, or how many links they shared. [source: The Verge]

7 times more fake news sharing

“But older users skewed the findings: 11 percent of users older than 65 shared a hoax, while just 3 percent of users 18 to 29 did. Facebook users ages 65 and older shared more than twice as many fake news articles than the next-oldest age group of 45 to 65, and nearly seven times as many fake news articles as the youngest age group (18 to 29).”

Profiling media sources…

“It won’t be easy: how to determine whether a person is digitally literate remains an open question. But at least some of the issue is likely to come down to design: fake news spreads quickly on Facebook in part because news articles generally look identical in the News Feed, whether they are posted by The New York Times or a clickbait farm.”

… to build trust.

Profiling sources so limit fake news spreading is similar, in logic, to profiling sources to limit misleading intelligence. We call it “Corpus Intelligence” and will focus on B2B solutions. In production end Q1 2019.

Trust, Media and Democracy

click here to read report

The Aspen Institute and the Knight Foundation recently released a report on a commission they organized about Trust, Media and Democracy. While coming from America, we believe most can apply wider.

If you don’t have the time for the length report, this medium page is very interesting. Here are our takeaways in the light of our previous posts, regrouped in 3 main categories:

10 ways to rebuild trust in media and democracy

Before starting up, we can not resist to simply cut and paste the introduction paragraph: “Our nation is experiencing a crisis of trust. We believe that reliable news is vital to our democracy, but many of us can’t name an objective news source. Concern about “fake news” is high, but we can’t agree on what that means. We can’t even assume every American is operating under the same set of facts. We retreat to polarized political tribes and don’t want to listen to anyone outside them.” – Superbly written and so much in alignment with what we believe and the motivation to create TrustedOut.

Of course, the purpose here is not a posture of “we know better” but rather than copycatting what the article says, simply note we wrote about most of those points and thus, are in agreement with them.

a/ Privacy and Transparency (#1, 5 & 6)

Top 2019 predictions: Privacy and Transparency

b/ Financial support (#2, 3, 4 & 7)

Saving journalism.

c/ Education (#8, 9 & 10)

Media trust over education stages

Feedback welcome. Go the bottom of any TrustedOut.com page…

Consumer trust is a vital and a key differentiator for publishers

Image taken from article in reference

Can’t resist just cutting and pasting the very first sentence here “Consumer trust is a vital and a key differentiator for publishers in a competitive environment. Fostering trust, prioritizing consumer rights and offering transparency of data practices is more important than ever before for premium publishers.” from this article from Digital Content Next

Sounds like our previous post on TrustedOut Market, doesn’t it?

So, unsurprisingly, we loved this article. Here are our takeaways:

Gap between trust in traditional and social media is now at an all-time high.

  • The US and Canada and European markets also registered significant trust in traditional media and search compared to social media. Trust in traditional media is at its highest-ever historical level at 65% in US and Canada and 60% in Europe, trust in search at 61% and 59%, respectively. However, rust in social media in both markets is at 34%.
  • The percentage gap between trust in traditional and social media is now at an all-time high of 31-points in US and Canada and a 26-point gap in Europe.
  • In terms of political differences, consumers who identify as Republican voters show only 33% trust in media compared to 69% of Democrats voters.

#MeToo shift from the “mass population” to the “informed public

Further, more women, think that the #metoo movement, (plus 23 percentage points year-over-year) than men (plus 18 percentage points) shift from the “mass population” to the “informed public” segment.

CEO to take the lead. Don’t wait for government!

People are also looking to leaders to take charge and initiate change. More than three-quarters (76%) of respondents report that CEOs should take the lead on change rather than waiting for government to impose it.

First priority: equal pay. Last: fake news

Specific needs for positive change include: equal pay (65%), prejudice and discrimination (64%), training for jobs of tomorrow (64%), environment (56%), personal data (55%), sexual harassment (47%) and fake news (37%). 

TrustedOut’s market

In its latest report on Social Intelligence, Forrester writes, straight right from the beginning:

Enterprises Are Still Not Using Social Intelligence To Its Full Potential” 

“Social Listening Platforms’ Current Offerings All Look Alike

Each social listening platform provider emphasizes its unique applicability and use across the enterprise. But each vendor also parades a roster of features and functionalities that largely look the same from one to the next. Buyers will struggle to distinguish major differences between each vendor’s current offering because social listening platforms all rely on the same data sources as the foundation of their platforms. … most vendors in this evaluation tap into the same third-party aggregators such as webhose.io for web content, LexisNexis or Factiva for news, … Social listening platform shoppers may find the breadth of data sources an important selection factor, but the discernment of data differentiation becomes increasingly difficult when all vendors source from the same well. ”  – Forrester, Q3’18

We couldn’t agree more.

Even more if you add the current crisis of distrust in content. Magnified but far, far more complex than just some fact checking to feel better with fake news being fixed. No, fake news are just the tip of the iceberg. The issue of trust in news and information in general is to, first understand who is talking before listening to anything they say, and then, ultimately taking any action.

The immense problem today is to not profile who is talking and thus, the trust you can put in the publisher, before spreading and commenting which means adding your intrinsic support.

Intelligence needs data.

Nothing new here. AI with its deep and machine learning, needs data. Analysts need data… any kind of intelligence needs data.

Social Intelligence needs data.

Forrester makes a point by saying there is no differentiation of the offer because there is no differentiation of the data used for the Social Intelligence. Of course, we agree and that’s the foundation of TrustedOut: providing profiled media sources. Let’s have a look at the 3 references mentioned by Forrester:

Webhose.io, Factiva and LexisNexis are all about articles. We believe Media is what matters.

Webhose.io claims to be “Data As A Service”, provides articles. Factiva (Dow Jones) does the same but claims to be curated by (lots of) humans. LexisNexis does the same but focused on legal.

We totally respect those three and in no way, are we judging them. We are just saying they, all three, take an “article” approach. You could also get your articles by the author name but none is scoring them.

None of them is focusing on the media itself. TrustedOut does. Here is why:

Trust is based on a reputation. An article does not have a reputation.

An author may have a reputation but is temporary and linked to a matter.

A publisher brand definitely has a reputation and its values guarantee stability.

Bottom line: Your Trust is based on the publisher brands you value.

This is why TrustedOut is an AI-Operated profiling media database offering our clients to define their trust via sophisticated queries (65+ fields and 400+ categories) because ONLY you can define your own trust. No-one can tell you what you trust.

The distrust fix is in giving you the tools to define what you trust.

Update: Digital Content Next wrote recentlyConsumer trust is a vital and a key differentiator for publishers in a competitive environment. Fostering trust, prioritizing consumer rights and offering transparency of data practices is more important than ever before for premium publishers.”. This could be from us.

Company sizes.

LexisNexis has 10,000+ employees and $2.8 Billions in revenue, 5M users and is available in 175 countries.

Factiva was bought by Dow Jones in 2006 for $160 Millions when their revenue was $290 Millions, used by 1.8M users and 80% of the Fortune Global 500.

Webhose.io is a younger independent company out of Tel Aviv claiming 35,000 registered users, $5.5M in revenue and 115 languages.

Market is growing fast.

$4B in 2018 and according to BusinessWire: “The Global Social Media Analytics Market size is expected to reach $11.6 billion by 2023, rising at a market growth of 28.6% CAGR during the forecast period.”

Various Sector Demands is growing fast.

“Asset managers double spending on new data in hunt for edge” – Financial Times

“Investment groups have more than doubled their spending on new digital information sets and data scientists in the past two years… Asset managers last year spent a total of $373m on data sets and hiring new employees to parse them, up 60 per cent on 2016, and will probably spend a total of $616m this year, according to a survey of investors by AlternativeData.org, a trade body for the industry. It forecasts that overall expenditures will climb to over $1bn by 2020″

So, demand is fast growing…. better use content you trust.

Taxonomy fun facts (as of today!)

Taxonomy DNA for The New York Times – Tech section

In these 2 recent posts, we announced our AI-operated Taxonomy…

Introducing Taxonomy DNA

Taxonomy DNA (cont.) – comparing a specialist vs a generalist

… time now to share some fun facts about it:

10,000,000 words

is the dictionary of words used for the qualification of our taxonomy classifications. Those words were precisely selected to be meaningful for each of our taxonomy classifications (leaves).

100,000 new article abstracts collected daily.

Every day, 100k article abstracts are collected. This number should grow to 1 million a day within 3 months.

75,000 operations per article

… to classify within our taxonomy every single article for every single day for every single feed for every single media.

8 Billions classification operations daily

This is growing daily and should reach 50 to 70B shortly.

Allowing for sophisticated Taxonomy classifications filters.

Thereafter is an example of how to filter classifications and depth of specialization per classification (we’ll dig into this more in a coming post) for your corpus:

Corpus creation and maintenance (may change)

Of course, should you have questions, let us know!

The incredible story of a 10 year long fake, success story.

For 10 years. Fake pharmaceutical, fake CEO, real top-notch business school.

It’s the real story of the fake story of Berden and its CEO. Both are the result of a top notch curriculum at HEC in France. [HBR story here]. The course is to control Enterprise reputation and the challenge was to create a Co., Berden, and its CEO, Eric Dumontpierre. And the success was incredible. For 10 years, the CEO was beloved, the company was super visible, to the point a real competitor sent a cease and decease for a… fake product of fake Berden.

The trick: Do not talk to medias

“The students had only one constraint to respect: not to communicate directly with the media. They had to build their reputation organically, by building an online ecosystem of websites and social network accounts where they would publish press releases and other information about the company, its history and activities.”

The method: Spread false…

Recent studies show that false information is easier to peddle than true information

… bold…

Research on the dissemination of “fake news” shows that students have used communication techniques identified decades ago by researchers as drivers of this phenomenon. Readers are more likely to circulate strong stories that evoke emotions such as fear (river pollution), disgust (child labour) and surprise or joy (32-hour work week) than smooth stories.

… repeat, until it sounds true.

Researchers have shown that repetition increases perceived veracity. In other words, familiarity induces credibility.

The fix: Trust profiled medias.

As previously written here, the solution to avoid this chaos is for medias to have clear values delivered and defended by professional journalists. THE weak point, the trick used here is the absence of contact with medias.

Absence of media opens the door to total chaos in education, opinions and decision-making. TrustedOut Corpus Intelligence is here to profile a totally unbiased, AI-Operated, Media database so Intelligence tools are fed with the content business analysts trust.