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Dutch MPs call for transparency on Facebook political advertising

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Sourced from DutchNews.nl

Dutch MPs have almost unanimously backed a motion calling on the government to pressure Facebook to come clean about political advertising ahead of the provincial elections in March.
Only the right-wing VVD and anti-Islam PVV opposed the motion which urged ministers to call for more transparency in political advertising. This transparency is necessary, MPs say, because ‘social media, including Facebook, offer a platform to political fake adverts’ at both election time and on other occasions.
Facebook said at the end of January that it would bring new political advertising rules and tools introduced in the US and UK last year into countries which are holding significant elections this year.
These measures will not, however, come into effect in the Netherlands before the end of March, after the provincial elections.
MPs say Facebook should come clean about the origins of political advertising three weeks ahead of the provincial vote on March 20.
Facebook has said its new rules will be in effect in Europe ahead of the EU parliamentary elections which take place between May 23 and May 26.
Feature Image Credit: Depositphotos.com

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Sourced from DutchNews.nl

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Good News – AAI add another 50 seats for their April #AAIToolkit seminar

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Free to AAI Members – please register your attendance

€35 + booking fee for non-members


 Join us for a once off conversation with Paul Hughes, Patrick Ronaldson, Richard Carr and Patrick Hickey, the original Rothco Founders and Partners

 

 

on Tuesday 2nd April 2019 8.30 a.m. – 10.00 a.m.
at Core, One Windmill Lane, Dublin 2

The discussion “Rothco: The Highs and Lows” will illustrate experience and work from across the years, and will be facilitated by Tom Kinsella Managing Director – Homes, AIB Group


  

  

 

 Hear the story of how great people and great clients helped Rothco to reach the point it is at today.  This is a conversation not to be missed.

As always at #AAIToolkit, there’ll be plenty of opportunity for questions from the audience, so make sure there is a chair with your name on it:

Be inspired and join the interaction, click below to register 

Free to AAI Members – please register your attendance

€35 + booking fee for non-members
Book now  

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Content groups in Google Analytics

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f there is an unsung hero in Google Analytics, it is definitely something called content groups (or content grouping). Never heard of it? It is hiding in plain sight, in your Google Analytics view settings, and can be set up in a couple of clicks. Once content groupings are set up, you will always want to use them.

Ready? Get some coffee, snacks, and let’s go build some content groups.

What are content groupings in Google Analytics and what do they do?

Simply put, content grouping allow you to create… wait for it… groups of content. Many times you will want to see consolidated reports on multiple elements and dimensions without having the possibility to see them grouped together as one entity.

Imagine you run a bilingual site like this blog but don’t necessarily have the URL structure to distinguish between languages. Imagine you run a news site made up of content sections such as politics, finance, sports, culture, etc. Imagine you run an e-commerce site with departments and product categories.

In the case of the multilingual blog, I want to see an overall view of my content’s consumption in terms of language.

In the case of the news site, I want to see which sections were read the most and which were read next.

In the case of the eCommerce website, I want to see whether my users are browsing within the same product category or exploring other products.

Creating content grouping

First things first, go to your Google Analytics admin panel and locate your view, as shown below:

You should be seeing an empty table, but I’ll show you how mine looks in the test view we’ll be playing with:

List of content groupings in Google Analytics

As you can see in the example above, I’m using up all 5 content groups allowed per Google Analytics view. I can create more groupings in another view if needed.

In your case, you should have a big red button called New Content Grouping . Click it. CLICK IT NOW.

The first thing we’ll do is give the new content grouping a name. If we use the eCommerce website example, let’s imagine it’s a clothing store – with 3 major sections: women’s clothing, men’s clothing and children’s clothing. With that in mind, let’s name the new content grouping Product section.

Next, I have to choose from three options in order to give my content grouping a value:

  1. Group by tracking code: relies on what information is sent to the Google Analytics tracking call, using Google Tag Manager for instance. This implies your tracking code / data layer includes the information required, with a productSection dataLayer entry for instance. Probably the safest option, assuming you can handle the related development.
  2. Group using extraction: here we’ll be looking at patterns in URLs and capture the strings in the URLs that match the pattern. Expect to use regular expressions.
  3. Group using rule definitions: with this option we can specify a value that applies when conditions are met, based on URL, page title or screen name. Basic but powerful, assuming you’re ready to handle lots of unique cases.

Actually, let’s tackle them in reverse order!

Group using rule definitions

This is going to be the most common way you use content groupings. Why? Because accessing your site’s URLs is the easiest way to find patterns and use them to create logical groups.

For instance, If we want to give our Product section content grouping a value based on URL rules, we can create a new rule. As shown below, we are creating a value of “Kid’s clothing” for pages where the URL contains /kids or /children. Yes, you can use regular expression as well as AND and OR conditions, which make rule creation a breeze.

Creating content grouping in Google Analytics based on rule definition

Another example is what I use to measure how much content on my site is served as AMP.

The above definition means I can now look into my Behavior > Site Content > All Pages report and use my content grouping as the main dimension:

Using a content grouping as main report dimension

Then once you select your content grouping (AMP in this case), your report shows you that consolidated view you’ve been waiting for:

Neat, right?

Group using extraction

We got the fun part done with the previous grouping method but the extraction method can be interesting too! In the example below, we use a regular expression to capture part of the URL folder structure that immediately follows the /products/ folder. In our case we assume URLs in the form of /products/mens/shirts.html. As with regular expressions, whatever sits inside the parentheses is captured to be used later. If the regexp is set to /products/(.*)/.*.html and using the above test URL, we’re going to captures mens and store it as the value for our content grouping.

Sounds straightforward, yes? Good – now for the best bit.

Group by tracking code

Grouping by tracking code is a lot more elegant, especially if you work with a tag management system such as Google Tag Manager. Essentially, you need to select your content grouping’s number (index) from 1 to 5 and pass a value to it.

Let’s examine the Google Tag Manager methodology. Assume you can generate the following data layer for any given page:

var dataLayer = window.dataLayer || [];
dataLayer.push({
  "productSection": "Men's clothing"
});

In Google Tag Manager, create a variable based on your productSection data layer variable:

Next, in your Google Analytics page view and event tags (or even in your Google Analytics configuration variable), setup your content group to use your new variable:

Using Google Tag Manager variables to populate content groupings in Google Analytics tag

Publish your GTM container and voilà! You have an elegant solution for content grouping that does not rely on URL-based rules and can easily integrate with your content management system.

But wait, don’t we have custom dimensions for that?

Ah, an astute remark! Custom dimensions are indeed available for a similar purpose, with the addition of specific scopes (user, session or hit), whereas content groupings are hit-based. Furthermore, custom dimensions are pretty much expected to be set in the tracking call, whereas content groupings can be set using URL rules, extraction, or tracking code, making them a bit more flexible than custom dimensions.

As mentioned before, the main advantage of content grouping over custom dimensions is pathing. You can see how content grouping can be included in a flow-type report:

If I use my content publication year content grouping, I can see if users navigate from older to newer posts or the other way around:

Using content groupings as high level navigational elements

Of course this method works great with the news site or ecommerce site examples I mentioned earlier.

In closing

If you hadn’t heard about content grouping in Google Analytics before this post, something tells me you’ll be using them very soon.

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Sourced from https://juliencoquet.com

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How Quitting Facebook Could Change Your Life

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By Erin Corbett

Quitting Facebook can affect your life, according to a new study.

In some ways, the report, The Welfare Effects of Social Media, recalls life before the internet. That is, without Facebook, the study’s author’s found, you have more free time and spend some of it directly connecting with friends and family.

Additionally, the study learned that being unplugged from Facebook made people less knowledgeable about politics. Some were also less affected by extremes of political discourse.

The study was headed by Hunt Allcott, an associate professor of economics at New York University, and Matthew Gentzkow, a Stanford economist, and was mostly financed by the Alfred P. Sloan Foundation.

Researchers led by Alcott and Gentzkow recruited participants using Facebook ads. They were ages 18 and older and spent at least 15 minutes on the social networking platform everyday. More than 3,000 people were in the study, based on their filling out questionnaires about their daily routines, mental wellbeing, and political leanings.

Participants stopped using Facebook, except for the social media’s Messenger app.

Results of the one-month experiment showed that people scored lower on tests of their political knowledge, while political polarization dropped between 5% and 10% for some users.

“This is not a trivial finding,” David Lazer, a professor at Northeastern University, who teaches political science and computer and information science told the New York Times. “It could have gone either way. You could imagine that the other chatter and information on Facebook was crowding out news consumption.”

Participants also reported having an extra hour each day — and sometimes more for heavier Facebook users — which they spent offline with loved ones, or watching TV.

The study also found that deactivating Facebook had a positive, yet minor impact on mood. While the study did provide evidence to support the addictive nature of social media, it remained unclear whether heavy Facebook use worsened a person’s mental wellbeing, or if people with mental health disorders were heavier users.

“This is one study of many on this topic, and it should be considered that way,” a Facebook spokesperson said in a statement to the Times. The statement, quoting from the study, added that Facebook can be highly beneficial to its users, and “any discussion of social media’s downsides should not obscure the fact that it fulfils deep and widespread needs.”

Feature Image Credit: Jaap Arriens—NurPhoto via Getty Images

By Erin Corbett

Sourced from Fortune

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When it comes to agencies, brands care more about cost than transparency

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By Seb Joseph

Price, not transparency or partnerships, remains the priority for clients when it comes to their agencies.

Last year, agencies pitching for the $1.7 billion global ad account for GlaxoSmithKline were asked to make upfront guarantees on the cost of media, despite it being widely acknowledged that those guarantees can’t be made for digital media, according to an executive who was on one of the pitch teams. Most, of course, complied.

The pitch had gone on for six months and was managed and audited by ID Comms and Ebiquity. It gradually morphed into negotiations over cost savings once the procurement team took over. Before that happened, GSK’s marketers had scrutinized each agency’s operating model and probed how they would provide full transparency into the money made on the media bought.

But the longer those discussions went on, fewer business KPIs and strategic relationships came up. Finally, agency executives found themselves in a corporate box overlooking a rugby pitch, giving GSK procurement team an overview of the savings they could make, said the agency executive.

Following those talks, Publicis won the account. “GSK reviews our media agency arrangements based on a number of criteria including strategic thinking and differentiation, understanding of our business, systems and reporting, quality of talent, the cost of media and contractual terms,” said a spokesperson from GSK, when asked for comment.

Savings often trumps all else if there is no clear winner on other criteria, and even then the numbers need to be highly competitive. It can create a race to fulfill those guarantees with cheap impressions that may not be safe, viewable or real.

Consultant education
Sources said that lack of education by pitch consultants –and agencies refusing to push back on invalid processes or decisions — makes matters worse.

“Running a tender for an agency or technology partner is not the same as procuring steel or glass,” said Ruben Schreurs, managing partner at digital media consulting firm Digital Decisions. “There is so much in-depth nuance in cost structures, and even more so when you go into operating models and strategic fit, that it is simply insane to apply too much weight to the bottom-line pricing in the decision process.”

It’s the standard trajectory of how many big media accounts are handled now. Transparency issues are the reason many advertisers go to pitch, but cost pressures are often what decides the outcome. According to data from Ebiquity, out of the 100 pitches it conducted last year, 54 percent said the top criterion used was cost improvement, and 34 percent said it was “strategic vision and expertise.”

At Adidas, which had a pitch for its $300 million media budget last year, the brand spent six months planning an operating model that went to agencies in the pitch document. The pitch, which was managed by MediaSense, was won by Mediacom. Sources said it was because the agency offered good price guarantees, although the company says the decision was more layered than that.

Progressive advertisers want fair remuneration, but there is still a disconnect between the marketing and procurement teams.

“The dynamic is changing, but I don’t think we are where are we should be,” said Laetitia Zinetti, managing principal for media management at media analytics specialist Ebiquity. “It can be difficult for an advertiser to differentiate between agencies on their strategic capabilities, so they look at how efficient they’re going to be — not just on the media costs but on the remuneration and technology costs too.”

The problem is advertisers are struggling to know what they don’t know about online media, and the pitch consultants are scrambling to fill in the blanks.

“The field of pitch consultants is growing fast, and levels of expertise are not everywhere,” said the media director at a luxury advertiser on condition of anonymity. “For remuneration, we use full-time equivalent payments and an incentive element. We want our partners to be profitable, but ideally at the same rate as we are. We do, however, see a shift in the market toward outcome or performance-based remuneration.”

Clients may even respect when agencies push back: “I worked on a pitch recently where a major agency declined to pitch in a major market because they felt they couldn’t compete on price,” said the marketing procurement director for a global CPG advertiser. “I was surprised, and it was a bit inconvenient for us, but ultimately I respected their honesty — and they saved their people a lot of work for likely little reward.”

This marketer said price guarantees are still useful criteria to judge an agency’s ability to buy digital but insisted the primary focus should be on the effectiveness of that media. “Pitch consultants continue to struggle in this area,” said the marketing procurement director, who is part of a broader push at the advertiser to take both pitch management and media management in-house.

“The KPIs on which we judge agency performance in online clearly need to include price, but should be much broader and encompass how well that agency fits with our strategic priorities such as reach versus quality, viewability or value chain transparency,” said the marketing procurement director. “I have yet to see a structured approach to this from pitch consultants that doesn’t ignore pricing but enables comparison on these broader ‘softer’ metrics.”

New models
Advertisers continue to use price guarantees to award media agencies because the cost of media is easier to determine than its effectiveness. Absolut, BT and L’Oreal have all tried to adopt newer ways of paying agencies in recent years. Whether it’s driving sales, customer loyalty or selling a car, measuring the effectiveness of these outputs is still subjective, which makes it hard to see the value. Few advertisers and agencies can get to the balance of risk and reward.

When Volkswagen ran its media pitch in 2016, one agency on the account proposed a cost-per-car remuneration model, according to one executive on the pitch. The carmaker declined. It’s hard for an advertiser to commit to outcome-based models like a cost per car when advertising is one of several factors that could impact sales, and subsequently hard to attribute a value to it. Scrapping the more traditional commission-based remuneration models like price guarantees is not a simple process.

“There is often a tension in media agency reviews between strategic marketing objectives and the need to demonstrate efficiencies,” said Nick Manning, svp at consulting business MediaLink. “Bluntly put, marketing wants innovation, and procurement wants lower costs for the same media. Digital has to be handled differently. It’s about effectiveness and value, not price, and performance has to be tracked differently. You can’t benchmark digital in the same way as TV.”

By Seb Joseph

Sourced from DIGIDAY UK

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96% of top level marketers believe that tech is driving in-house. Why?

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Sourced from Banner Flow

In our recent State of In-housing report, 96% of top-level marketers believed that tech was driving the in-house movement.

Yet what is it about advertising technology that has enabled the in-house revolution in marketing?

Well, we have it figured out.

Here are our top 3 reasons:

1. Efficiency is fuelling change

Greater efficiency is a top 5 reason for brands moving their marketing in-house.

In fact, efficiency is the ‘it’ word of ad tech. All providers promise streamlined workflows, efficient processes, and enhanced productivity – something that not all agencies can deliver.

With improved workflows, brands are questioning why they should pay an external agency to do the same work they can do in-house, often a lower cost. For top-level decision makers, the adoption of ad tech is a natural choice for marketers looking to move their processes in-house.

This is not a feeling exclusive to Europe either. In a 2018 survey by the Association of National Advertisers (ANA) 12% of US respondents claimed greater speed as a key reason for moving operation in-house.

For Ville Heijari, CMO at Rovio (an early-adopter to the in-house movement) ad tech has been an essential addition: ‘We use workflow automation tools, campaign automation, and various tools that enable us to increase the speed of delivering more versions, variation and experiments with digital campaigns.’

How do you select ad tech for efficiency?

With so many solutions out there to choose from, it’s important you select the right product. A product that will not only solve existing inefficiencies but present opportunities for future growth.

Take Shutterstock for example. Their existing online production was too slow, taking weeks instead of days. Now, they not only produce advertising quickly, but they have also created some truly exceptional ads. Thanks to added analytics and optimisation features from the Bannerflow CMP.

Whatever aspect of your digital marketing you choose to make more efficient, it’s important you pick a product that will create efficiency throughout your campaign processes. Otherwise, why bother?

scaling-bannerflow-efficiency

Scaling into different versions is easy with Bannerflow’s intuitive tool.

2. Creativity is driven by effective ad tech

For 51% of respondents, lack of time is ranked as the main blocker to creativity.

Therefore, it must follow that with increased efficiency there is greater creativity?

Nowhere is ad tech’s influence more obvious than with the introduction of Dynamic Creative Optimisation (DCO) into the online advertising space. This technology, when combined with a CMP, is the perfect combination of efficiency and creativity. Allowing you to produce the right ads, at the right time, for the right person.

Be warned though, for 22% of brands from the in-housing report believed technology to be a barrier to creativity. For Lara Izlan, Director of Programmatic Trading and Innovation at AutoTrader, the pressure to adopt ad tech too fast can lead to: ‘an ad tech infrastructure that is overly complex’.

How to choose the right ad tech for creativity?

With the right product, beautiful and eye-catching designs don’t have to take weeks off your designer’s life.

In fact, if you choose a platform with a workable interface, a comprehensive onboarding programme, and an engaged customer success team your ad tech will aid, not hinder your design team.

Indeed, for Icelandic telecommunications company NOVA, increased in-house efficiency has led to some truly innovative online advertising. With the widgets provided in the Bannerflow platform making their designers want to be creative.

3. Transparency comes as standard

9 out of 10 marketers are concerned with the transparency level of media agencies.

Problems surrounding transparency have been plaguing agencies for a number of years, on a number of issues – particularly in regards to media buying. Programmatic media buying has frequently been labelled as the ‘black box’ of digital marketing. Agencies have been taking advantage of clients ignorance to take full control of clients budgets – with little or no accountability.

Ad tech has emerged as a solution to this problem. Allowing brands such as Electrolux, Philips, and Lucozade to take full control of their media buying strategy, in-house.

The right technology can provide accountability over budgets, analytics, and optimisation. As well as help tackle issues surrounding fraud, viewability, header bidding, and yield optimisation.

Although Raluca Efford, Head of Digital and Social Media Marketing at Direct Line, has her own opinion: ‘When trading desks were first set up in 2008/09 they were there to enhance transparency for clients. Since then, they have become more and more complex and have become the ‘black box’ technology that they wanted to mitigate against.’

What does transparency mean for ad tech?

In terms of media buying, it is important to choose a tool that doesn’t over complicate the process. Having your analytics in one place, and the ability to optimise in real-time will vastly improve your campaign performance.

What is more, with the Bannerflow media buyer, you have full accountability over where your money is being spent – even on third-party integrations.

bannerflow-analyse-optimise

The Bannerflow analyse and optimise feature.

Conclusion

Ad tech presents a great opportunity for brands looking to take control and bring marketing in-house.

Efficiency, creativity, and transparency are all clear benefits of an age where technology holds sway. Yet, in this oversaturated market it is important to choose a solution that will clearly deliver on these objections.

Bannerflow’s easy to use creative management platform (CMP) allows you to build, scale, publish, analyse and optimise in one. To discover more about our product get in touch with us.

Or, if you want discover more findings from our State of In-housing report you can read the full report here.

 

Sourced from Banner Flow

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The Cost of Apple News

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By Ben Thompson

Apple is, according to the Wall Street Journal, driving a hard bargain with publishers ahead of the launch of its rumored News subscription service:

Apple Inc.’s plan to create a subscription service for news is running into resistance from major publishers over the tech giant’s proposed financial terms, according to people familiar with the situation, complicating an initiative that is part of the company’s efforts to offset slowing iPhone sales. In its pitch to some news organizations, the Cupertino, Calif., company has said it would keep about half of the subscription revenue from the service, the people said. The service, described by industry executives as a “Netflix for news,” would allow users to read an unlimited amount of content from participating publishers for a monthly fee. It is expected to launch later this year as a paid tier of the Apple News app, the people said.

The rest of the revenue would go into a pool that would be divided among publishers according to the amount of time users spend engaged with their articles, the people said. Representatives from Apple have told publishers that the subscription service could be priced at about $10 a month, similar to Apple’s streaming music service, but the final price could change, some of the people said…

Another concern for some publishers is that they likely wouldn’t get access to subscriber data, including credit-card information and email addresses, the people said. Credit-card information and email addresses are crucial for news organizations that seek to build their own customer databases and market their products to readers.

Probably the most obvious way to understand this story is that it, along with the report that Apple would have a launch event on March 25, appear to be attempts to negotiate through the media. I’m reminded of the January 2010 report in the Wall Street Journal that Apple’s impending tablet would cost $1,000; when Steve Jobs announced the iPad three weeks later, the $499 starting price seemed like a bargain. Perhaps leaking a 50/50 revenue share, along with an impending deadline for negotiations, is a way to make a 60/40 or 70/30 revenue share seem like a reasonable compromise?

The Growth of Apple News

Let’s back up for a moment: Apple News has grown to be a major force in publishing, at least in terms of traffic. According to a New York Times story that Apple cooperated with, the service “is read regularly by roughly 90 million people.” That has translated into traffic for news publishers that, according to Slate, often outpaces Facebook post-last January’s algorithm change.

The problem, as Digiday explained, is that traffic — which is almost completely realized within the Apple News app, not on publisher’s web pages — comes with minuscule amounts of revenue. Yes, Apple News allows for advertising, but that advertising is either sold (poorly) by Apple or sold directly by the publisher with no allowance for either programmatic ads nor data about users.

So why do publishers bother?

Apple News and Aggregation

There are a number of factors that should ring familiar to anyone familiar with the travails of publishers on the Internet.

To start, Apple News readers visit Apple News and, for the most part, read what Apple News presents to them; the front-page may be human-selected, as Apple sought to make clear in that New York Times article, but just as is the case with algorithmic selection (which is what determines what users see for the rest of Apple News, it just happens to be called “Suggested by Siri”), no one publication is favored:


Apple News Today view

On one hand, this is obviously not good for publishers: there is limited wherewithal to build brand affinity, there is no customer data shared (for purposes of follow-up, much less ads), and as noted above, there really isn’t much money to be made.

On the other hand, what are publishers really giving up? Readers going to the Apple News app have already made the decision to not visit a particular publisher’s website directly, and, given that digital content has zero marginal cost, why not support Apple News on the off chance some article hits it big?

It should be noted that publisher pages within Apple News complicate this narrative a bit: on one hand, they are a place to build brand affinity; on the other hand, they are more likely to cannibalize direct visits to the publisher’s website. But how many Apple News users are likely to switch to a browser for a particular publisher should they leave Apple News?

What is happening is Aggregation: Apple News attracts the users, which means publishers are coming onto Apple’s platform on Apple’s terms, which makes Apple News more attractive to users, making publishers ever more reticent to leave even though they aren’t getting much out of the deal.

Apple News and Publisher Subscriptions

For suppliers, the antidote for Aggregation is to go direct to consumers; the key is to embrace the same forces that drive Aggregation. First, the addressable market should be the entire world, not just a limited geographic area. Second, the same sort of automated payment tools available to advertisers on Aggregators can be leveraged for consumers; indeed, the tools for consumers, particularly given the lower dollar amounts and decreased need for paperwork, can be as simple as Apple Pay, and they can scale indefinitely. Third, a freemium approach to content means that social networks can be used for user-generated marketing.

Apple News as currently construed is actually somewhat helpful in this regard: publishers can push subscription-only content (as well as free content) into Apple News, and give users the option to subscribe using the App Store. For example, the Wall Street Journal elected to make the piece that triggered this Article free:

Free Wall Street Journal article in Apple News

However, the next story over, about Google Cloud, requires a subscription:

Subscription story in Apple News

It’s not perfect: clicking on that subscription link means the publisher has to pay Apple 30% the first year and 15% after that, and they don’t get any customer data (unless the customer creates an account in order to use their subscription on other platforms). Still, to my mind it is somewhat less egregious than Apple’s restrictions on in-app purchase; Apple News is driving the customer to a publisher’s content and charging accordingly (as opposed to taking a tax simply because there is no alternative to the App Store), but at the end of the day the publisher is still establishing a direct paying relationship with a subscriber.

The Spotify of News

What Apple is reportedly building now, though, is decidedly different. The so-called “Netflix of News” — although, given that Apple will pay out on a marginal basis as opposed to buying content, a better descriptor would be the Spotify of News — would entail customers paying one monthly fee to Apple which Apple distributes to publishers based on what subscribers read.

Publishers should be very clear about the implications of this model: it is not a direct-to-consumer model. Rather, it is an Aggregation model that happens to monetize via subscriptions instead of ads. That means it has all of the same problems for publishers that are posed by Aggregators:

  • Publishers do not form a direct connection with users; that connection is with Apple News
  • Publishers get no meaningful data (including no email addresses); there is no means to increase engagement or monetization down the road
  • Publishers must compete with every other publisher for attention

That last point is the most important, and should weigh heavily on publishers that have committed to the subscription model. What makes subscriptions work is an alignment between editorial and business model: the former is incentivized by quality and differentiation because the payoff is a customer with a high lifetime value; the New York Times put this succinctly in their 2020 Report:

We are, in the simplest terms, a subscription-first business. Our focus on subscribers sets us apart in crucial ways from many other media organizations. We are not trying to maximize clicks and sell low-margin advertising against them. We are not trying to win a pageviews arms race. We believe that the more sound business strategy for The Times is to provide journalism so strong that several million people around the world are willing to pay for it. Of course, this strategy is also deeply in tune with our longtime values. Our incentives point us toward journalistic excellence.

The proposed Apple News model, on the other hand, which pays out according to reader engagement, pushes in the opposite direction — the Facebook direction. The motivation is “to maximize clicks” and “win a pageviews arms race”, with some “time-spent” variables mixed in; sure, the driver isn’t low-margin advertising, but shifting the means of monetization doesn’t change the ends as far as incentives go.

The Cost of Apple News

It is absolutely worth noting what a great deal for consumers an Apple News subscription bundle would be: I totally get the idea of subscription fatigue, and having one place to get all of the best journalism would be amazing. That, though, doesn’t mean that Apple News wouldn’t be an Aggregator: that confirms it! Aggregators win because consumers prefer them, leaving publishers no choice but to go where the consumers are.

To that end, I am sure that a significant number of publications will sign up for Apple’s offering; clearly the company is confident enough to leak a date. And, frankly, many publications should: most publishers are already locked into the volume game when it comes to their editorial direction, and Apple News subscription payouts will be additive to the bottom line.

Publishers that have truly committed to subscriptions, though, should say no: not only will it be difficult to make up revenue that will be cannibalized lower per-customer payouts from Apple News, but more importantly a reversion to a model predicated on page views will hurt their business in the long run. This is especially the case if Apple News becomes a major revenue driver; yes, digital content can be distributed with zero marginal cost, but the incentive cost should not be discounted — it works directly against the quality imperative that is the critical factor in making the Aggregator-avoiding direct-to-consumer business model work.

I wrote a follow-up to this article in this Daily Update.

 

By Ben Thompson

Sourced from Stratechery

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Study Finds Tech is Number One Industry for Workplace Drinking

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By Adam Rowe

Workplaces and alcohol have a long and tipsy history together, from 60s-era Mad Men culture to a co-working space hot-button topic today. It’s no secret that the tech industry is pretty drink-friendly, with a beer fridge often nestled between the ping-pong table and a snack bar on the list of attractive workplace perks.

But, in recent years, we’ve started side-eyeing tech’s drinking habits. The #MeToo movement has impacted drinking policies at major companies – most prominently, WeWork dropped its unlimited beer tap option last October following sexual assault allegations at WeWork events.

Now, a new study has pulled tech drinking culture back into the spotlight. The tech world, the study found, is the single industry most likely to allow or sponsor alcohol consumption in the workplace.

Tech’s Drinking Culture

In a survey with more than 1,000 respondents, Niznik Behavioral Health found that the tech industry took home the prize for the most drinking-friendly workplaces. The marketing and advertising industry came in third, and the construction industry came in second

Specifically, a little over half (53%) of the tech industry was found by the study to include alcohol at the team bonding events. A further 35% of tech firms offer company-sponsored happy hours.

Moreover, about half (49%) of the employees across all industries (not just tech) thought that drinking with a coworker or their boss would improve their relationship. However, moderation is still in order – most said that two drinks was the right amount.

The Downsides

Granted, it makes sense that a little light drinking can improve team bonding. But, there are plenty of potential downsides, and the negative impact of too much drinking was highlighted by the study:

“Heavy drinking can lead to regrettable disclosures, and work events were no exception to this trend. Respondents were most likely to report revealing secrets to colleagues after drinking at a work event or complaining about work issues in a way they later regretted. Another 9 percent simply said they embarrassed themselves by becoming clearly intoxicated. In such cases, some would propose a proactive approach: Rather than waiting for others to broach the subject, express your mortification and move on.”

Over-indulgence is an issue likely to crop up at any drinking event. However, it’s an expected downside, rather than an existential threat to the concept of workplace drinking itself.

A larger issue is the cultural pressure on those who won’t drink at all.

Abstainers Will Self-Exclude

Of the 35% of respondents who prefer not to drink at a work event, 22.3% said they would give an excuse just to avoid the work event entirely. That was the most common response, followed by drinking anyway (15.8%). A remarkable 11.5% of respondents said they would pretend to drink at such an event.

In other words, even moderate workplace drinking can have a concerning effect on the one thing it’s supposed to encourage: employee bonding.

Workplace drinking in tech

There are plenty of anecdotes to back this up online, from one tech employee’s account of the variety of experiences being “the sober one” (hey, at least hearing secrets beats dealing with vomit), to tech startups alleged to have excluded non-drinkers because they weren’t a “culture fit.”

Needless to say, you don’t want a full third of your workplace to feel uncomfortable at your party. If you’re committed to drinking, make sure that alcohol-free options are easily available and try to fight any stigma or pressure as best you can.

Some recommend including an equal amount of non-alcoholic to alcoholic drinks at every tech event (and advertising as much beforehand). This actually might be easier than you think. Plenty of alcohol producers have been adding an increasing amount of non-alcoholic options over the past few years.

According to a recent CB Insights report, the world’s largest brewer, AB InBev, has made seven acquisitions or investments in the space, and believes “low-alcohol and non-alcoholic business [will] represent 20% of global sales by 2025, up from 8% today.”

Workplace drinkingAre Dry Events the Answer?

Dropping the alcohol at a workplace event isn’t likely to upset too many people, with almost a third of the survey’s respondents saying that they’d even prefer a healthy alternative such as massages or exercise.

“Dry activities also appealed to a significant portion of people who liked to drink at work events,” the study found. “At least 30 percent of this group would trade drinking events for sponsored lunches, massages, fitness training, and permission to bring pets to work.”

Dry events may not quite replace drinking ones in the tech industry. But, there’s a sliding scale for how inappropriate workplace drinking can be.

Sponsored happy hours may feel fine, but team bonding exercises will make abstaining team members a little more uncomfortable if non-alcoholic beverages aren’t included. Drinking at after-work events can feel better than bringing beers directly into the nine-to-five itself, but the pressure to conform to a tech work culture can remain.

The bottom line: moderation is a must. And the tech industry’s status as the number one top drinking industry indicates that it might need a tad more moderation yet.

By Adam Rowe

Adam is a writer with an interest in a variety of mediums, from podcasts to comic books to video essays to novels to blogging — too many, basically. He’s based out of Seattle, and remains a staunch defender of his state’s slogan: “sayWA.” In his spare time, he recommends articles about science fiction on Twitter, @AdamRRowe

Sourced from TECH.CO

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Predictive Analytics For Retail: What Lies Ahead?

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By Dave Wendland

Although I’m not certain that they all were “Robert Wendland originals,” my late father had many witticisms to which I credit him. With impeccable timing, a simple, pithy phrase would be spoken that was not only appropriate for the moment but also stuck with me for a lifetime. One in particular that I reference often suggests that “You can’t drive forward if you spend your time only looking in the rear-view mirror.”

The rate of change occurring in our lives and across virtually every industry is unprecedented. Oddly, the smartphone was first introduced less than a decade-and-a-half ago, and yet its ubiquity makes it unfathomable to think of going through life without one. The same could be said of self-check-in at airports. (Remember the days of paper tickets, travel agents and full-service?) And, in retail, where our company Hamacher Resource Group works across the retail supply chain, everything I remember from my childhood seems like ancient history.

I am personally fascinated by predictive analytics and the ability to combine data elements to create an approximate idea of what the future may hold. Although data modeling has been used quite extensively in certain industries (e.g., weather predictions based on specific historic models and key indicators, insurance estimates and actuarial tables, etc.), the concept of applying similar science to retail holds unrealized potential. Given technology advancements and data-mining tools, potential future predictions — in other words, answering the question “What lies ahead?” — seems far more attainable than ever before. Considering big data already captured within the retail sector, it becomes mind-boggling.

Virtually all industries have pools of information that could be used for predictive purposes. This reminds me of a presentation I sat through nearly three decades ago by a then-IBM executive who suggested that the future will be owned by those who have the keys to data and the intelligence that it generates. And, as recently as this month’s National Retail Federation event, the power of data was repeatedly emphasized.

According to a recent blog post from McKinsey, “winning decisions are increasingly driven by analytics more than instinct, experience, or merchant ‘art’; what succeeded in the past is now a poor predictor of the future, and analytics is helping to inform and unlock new pockets of growth.”

So, what types of data do we have available in the retail class of trade? Here’s a partial list:

• Point-of-sale transaction-level data

• Retail pricing strategies

• Consumer-based loyalty information (shopper insights)

• Physical store size and demographic characteristics

• Department sizes and product assortment (planogram data)

• Store navigation intelligence (traffic flow)

• Social media metrics

• Competitive intelligence

• Seasonality and other external trends (e.g., weather)

If one takes the time to imagine connecting discrete data elements and begins creatively combining them in unique ways, amazing predictions can be formed. Whether informing promotional campaigns, personalizing customer offers, improving employee training, building customer retention or simply forecasting demand and optimizing assortment and stocking levels, using big data and some gut instinct can conjure up interesting insights. Here are a couple on my mind.

Imagine aligning store navigation intelligence, shopper loyalty data and neighborhood demographics to consider how to attract others within the area by enhancing navigation and department placement to match their needs. Once again, continuing to do the same thing time and time again may not be positioning the retailer to best capture additional sales.

As an example, say a grocery store was initially designed to attract stay-at-home moms with two kids. The store was arranged to cater to her needs, but the neighborhood was now comprised of older adults with limited mobility and fixed incomes. How could the data predict their navigation pattern, category preferences and better cater to their overall shopping occasion? The hypothesis I would look to prove is whether shelves should be lower and aisles wider, whether certain categories (e.g., sugary cereals and baby diapers) should be downsized and how to rearrange the checkout to be less confined and more staff-centric. Predictive analytics could be used to model the potential result of such changes and allow the retailer to assess whether such an investment would be justified by the return.

Another scenario fueled by predictive analytics could look at the success ratio of certain product launches within a retail operation. Examining planogram and assortment data alongside point-of-sale transaction details and customer loyalty intelligence, future predictions can be created to fuel decisions about placement, promotion and timing.

Today a delicate balance exists between staid and proven stock keeping units (SKUs) and potential innovators and disrupters. Developing analytic modeling that can better predict performance could greatly improve buying decisions and bolster the performance of the category. This would certainly help in honing the process of new item evaluation and potentially reduce the number of new products shelved that do not perform to the expectations of the retailer.

In essence, only looking in the rear-view mirror and continually employing the same process will merely produce the same results. On the other hand, using learnings from the past and combining new, enriched data elements could generate a true breakthrough that drives new results.

Feature Image Credit: Getty

By Dave Wendland

Vice President, Strategic Relations at Hamacher Resource Group, Inc., passionate about optimizing results across the retail supply chain.

Sourced from Forbes

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How Tableau aims to make data analytics more accessible

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Sourced from IT Brief

Tableau Software announced the general availability of Ask Data, which leverages the power of natural language processing to enable people to ask data questions in plain language and instantly get a visual response right in Tableau.

This patent-pending capability makes it easier for people, regardless of skill set, to engage with data and produce analytical insights they can share with others without having to do any setup or programming. Ask Data is available as part Tableau’s newest release, Tableau 2019.1.

Customers can simply type a question such as, “What were my sales this month?,” and Tableau will return an interactive visualisation that they can continue to explore without limits, either with iterations, new questions, or drag and drop gestures.

There is no need to have a deep understanding of the data structure, no setup required and no programming skills necessary. Ask Data uses sophisticated algorithms that are driven by an understanding of the person’s intent, not keywords, which helps Tableau return more relevant results.

Ask Data technology translates simple questions into analytical queries

Ask Data supposedly uses sophisticated algorithms that are driven by an understanding of the person’s intent, not keywords, which helps to understand a person’s question, anticipate needs, and allow for smart visualisation selection.

For example, when someone types in “APAC furniture” for their sales data, they want to filter “Product Name” to “Furniture,” and “Region” to “Asia Pacific.” Ask Data combines statistical knowledge about a data source with contextual knowledge about real-world concepts: “Furniture” is a common value for the “Product Name” field and “APAC” is an acronym of “Asia Pacific.”

Additionally, Ask Data’s parser automatically cuts through ambiguous language, making it easy for people to ask questions in a natural, colloquial way. This means, if a question could be interpreted multiple ways, Ask Data will combine knowledge about the data source with past user activity and present a number of valid options to choose from, with the ability to refine the results if needed.

Tableau expands platform with prep conductor in new data management package

Tableau also announced today the general availability of Prep Conductor, a new product that enables organisations to schedule and manage self-service data preparation at scale with no programming or complicated setup. Tableau Prep Conductor is part of a new subscription package called Tableau Data Management.

Prep Conductor supposedly automates flows created in Prep Builder (the renamed Tableau data prep product).  Prep Builder is already in use by more than 11,000 customer accounts, and Prep Conductor will help organisations use it more broadly to ensure that clean and analysis-ready data is always available.

It also gives people greater confidence in their data by providing added visibility and detail behind cleaning history and data connections, as well as alerts when processes are not operating as scheduled.

Tableau Prep Conductor gives IT the ability to monitor and set up automatic cleaning processes (flows) for their data across the entire server. It also allows customers to build permissions specifically around data flows and data sources in order to maintain control and meet data compliance standards and policies.

Feature Image Credit: Getty

Sourced from IT Brief

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