The aftermath of the February 28th retail boycott

February 2025

The title here is a type of pun on math   and how reporters spin the numbers to fit their agenda. It's a kind of nod to the idea lies, damn lies, and statistics.

Trying to make a boycott take off

On February 26, 2025, Betty Lin-Fisher, a consumer reporter at USA Today plugged the article she wrote for the outlet on LinkedIn thus:

This Friday, Feb. 28 is the one-day, 24-hour consumer economic blackout.

Consumers are encouraged not to spend money during the 24-hour period and if you need something, to buy local.
The Feb. 28 event is one of several boycotts planned by groups of consumers or activists to protest what they call corporate greed, companies that have rolled back their diversity, equity and inclusion efforts and President Donald Trump's efforts to eliminate federal DEI programs since taking office.

 The Boomerang Effect Shown on Social Media

The comments showed that not everyone agreed with this approach, with many declaring that they'd make a point of shopping that Friday. Some added additional commentary on why they thought this was wrong. 

For example, Kimberly wrote this: 

I will go to Target and look for products by black businesses and purchase some. I disagree with this whole thing as it could affect those that have nothing to do with it. Treat people on merit and qualifications not race. Last I saw we've had a black President, VP, police chiefs, mayor's, governors I could go on and on into infinity. You can be anything you want to
be. Only one standing in your way is yourself.And Jan wrote:We should agree to disagree and give the current administration 2 full years to show American just what they will do for us. I may not have liked prior Presidents but I never wished harm on our working people. After 2 years, THEN speak up and change things with the Mid-Terms. However, I believe we will see our economy turn around over the next 6 months and no one will want to change anything! It's only been 5-6 weeks...... Wish for the BEST for our Country! We the People have spoken with our votes

What does the data show?

Now that we're in early March, the numbers should be in to let us know if the boycott had any significant impact. So let's see what Betsy Lin-Fisher had to say in her follow-up  on the first day of what  was intended to be a one week "fast" from Amazon purchases and a full 40 day "fast" (the correspondence with Ramadan has to be deliberate, as Lent only began today -- Ash Wednesday) intended to harm Target and Walmart in USA Today. 

She was forced to admit that rather than dent Amazon sales, as compared to the previous eight Fridays, sales were actually up 1%, as per Momentum Commerce. It doesn't appear she's getting this information first-hand but relying on Forbes reports, and the headline it used about Amazon on March 2 was Amazon Defies ‘Economic Blackout’ As Sales Climb During Boycott.

Lin-Fisher was willing to concede Amazon so long as she could claim Target. Again, that's based on a Forbes report: Target Loses Web Traffic As Costco Gains On Feb. 28 Economic Blackout Day The implication her is supposed to be that Costco, which did not yet make a statement about dropping DEI, is being rewarded -- as per an increase of 22% in web traffic and 3% in app visits [not sales but visits] --while the other evil retailers are being duly punished by a drop in traffic.

Let's now set aside the question of whether or not Costco benefitted from the boycotters' position, which actually contradicts their stance of avoiding all big retailers and buying locally instead -- and take a closer look at Forbes' figures for Target and Walmart., and I want you to notice something. Hint: it's in the calendar page that I used as the illustration for this blog.   

• On blackout day, Target website visitors dropped 9% compared to Friday, Feb. 14, from 5.2 million to 4.7 million.
• Target app user traffic, representing the most loyal Target customers, was off even more, down 14%, from 4.2 million to 3.5 million.
• On blackout day, the nation’s number one retailer, Walmart, experienced a 5% slump in web traffic, down from 11.7 million on Feb. 14 to 11.2 million and number two Amazon dropped by 2%, from 67.1 million to 65.9 million.

Did you pick up on my hint? Why are we comparing the 28th to the 14th? Wouldn't it make much more sense to compare the 28th to the 21st -- the closest Friday to it and one in which there was no special occasion that prompted people to spend billions of dollars on gifts? 

The NRF predicted a record-breaking $27.5 billion in spending for Valentine's Day 2025

SEe the illustration above of the level fs spending  about the sales predicted for this year's Valentine's Day that would include spending on February 14th itself -- given the last minute habits of many consumers. They would have been able to shop online at retailers like Walmart and Target and still pick up in store to make sure they'd have the expected token of love ready. In fact, a good chunk of Valentine's Day shoppers do make their purchases online as you can see from the graphic below:

 

Deliberately taking February 14th as the baseline to "prove" a significant drop in shopping traffic at Target and Walmart on an ordinary Friday is the equivalent of weighing yourself just after a Thanksgiving dinner and then weighing yourself a few days later first thing in the morning before breakfast and claiming you lost five pounds. Anyone who tracks weight accurately would always tell you to weigh yourself at the same time of day each time for the sake of consistency with your baseline. 

This tactic is known as stacking the deck, one of the logical fallacies you should have learned about it in a rhetoric course. 

Related: 

Everybody lies with visualizations

The Value of Zero: Accuracy and Trust

Data-driven marketing has always focused on getting as much information on your customers as possible through various channels. As privacy grows increasingly important and tracking becomes increasingly limited, zero-party data (ZPD) is on the rise.

Conventional marketing wisdom has always been that the more you know about your customer, the more effectively you can target them. For that reason, marketers have always been trying to get their hand on as much data as possible, relying not just on their own first-party data but even paying for second-party and third-party data. 

To clarify terms, here’s a rundown on the differences in data sources.
First-party data

First-party data is what a business receives directly from a customer typically as a result of purchases, subscriptions, or points of contact. It can be the result of what a customer actively fills in on a form or passively shares as a result of cookies that the customer accepts by using the brand’s site or the tracking that comes through use of an app.

While a complete record of information given by a customer is valuable, for businesses that haven’t had much time to gain a complete history, it may not suffice to inform truly tailored experiences. That’s why businesses will pay for access to additional information through second and even third parties.
Second-party data

Second-party data is first-party data acquired by another company that is then sold to a business that wants more information about its customer base. Drawing on the more thorough information can fill in more of the customer picture, but it’s still limited to what a single business has been able to gather on the customers, which is why some will pay a broker for data.


Third-party data

Third-party data is different from first and second party in that it draws on multiple sources of data that a separate company puts together into a single dataset to be sold to those in the market for that kind of customer information. Typically, the company in the business of delivering data will purchase first party data from a number of companies to create these data packages for others to buy through the data exchange marketplace.
Data drawbacks

While going from one to three increases your data resources, it’s not without its drawbacks. As anyone can buy third party data, what a business buys is not unique to it. As a result, it is very likely that all businesses competing for the same customers are working off the same data set.

Also since the establishment of GDPR in Europe and CCPA in California, marketers have had to respect consumer-set boundaries for the collection, use, and sale of their data.

The rise of such legislation has shed more light on privacy issues that has created pressure for platforms to stop enabling data collection without users’ knowledge. That is the story behind Google’s resolution to phase out third-party cookies and Apple’s new iOS setup for informed consent on apps.

The new frameworks don’t only curtail marketers from using data obtained from outside sources. They can even limit some first-party data that businesses have obtained without informed consent by tracking consumer behavior with cookies, pixels, or cross-device identification (XDID).

That is why a couple of years ago, we started hearing about zero-party data or ZPD. The term has been credited to Forrester, which presented it in Predictions 2019: B2C Marketing Report.

This approach has gained momentum over the past couple of years. AW360 predicts that a quarter of CMOs will be looking to implement ZPD in 2021.
The zero-party solution

As both zero-party data and first-party data take in information directly from the customer, there is some overlap between the two. The crucial difference between them is that zero-party data only includes what a customer knowingly and willingly shares.

That means that customers are in full control of the information they share with the business. They are willing to give their data if they feel they can trust the brand and are getting something of value in return.

Read more in  Zero to Hero: Providing Personalization & Privacy

Today's targeted marketing is powered by data and automation

 Marketing is always more effective when it is more targeted. As a result of integrating data and algorithms, marketers are able to now deliver a personalized customer experience at scale. 

There are various ways to target specific customers, and approaches range from lumping customers into very broadly defined categories to getting a lot more fine-tuned about the segments and responsive to individual customer behavior .In collaboration with Google, Deloitte put out a Digital transformation through data: a guide for retailers to drive value with data that took a closer look at these gradations. 

It ranked them as follows:

• Limited segmentation: All users are analyzed in broad segments. 

• Basic segmentation: Uses standard characteristics (e.g., gender, geography) for segmentation.

• Detailed segmentation: Segments are based on personal and behavior

• Dynamic segmentation: The UX / UI can respond to a customer’s in-session behavior as he or she exhibits different segment characteristics.

Achieving the detailed level depends on much more data than the static kind that is used for basic segmentation, and advancing to the dynamic level requires a level of automation that will enable recommendations and responses to go out in real-time. 

 The coming AI revolution in retail and consumer products invoked the women’s clothing store,  Avenue Stores LLC as an example of dynamic segmentation. It explained that  it brings together “data across multiple touchpoints, including in-store activities and market trend analysis, to learn and reason about what customers want and when they want it.” On that basis it can reach out to customers with communication tailored to their situation in real-time, which makes it possible to capture their attention while in “‘shopping mode.” 

Marketing for loyalty

Being in touch with your customers to let them know you’re there for them without pressuring them to buy can pay off in winning their loyalty and business later. In this case, your automated messaging doesn’t have to respond to segment your audience, as you would be working off a general form of communication.

When you don’t have history

But what if you do need to sell your products now? Marketing recommendations can work even on the more basic level, not just for new customers for whom you have no history to flesh out a profile but for the type of marketing communication that depends on general trends. For example, a very broad segment of all people in the United States can work for promotions tied to events shared by all due to the calendar, whether it’s Mother’s Day, Memorial Day, July 4th, etc. 

You don’t need to know much about your customer other than that they’ll know what these days are because they are on their calendars due to living in the United States for the trending algorithm to work well. That makes using this approach ideal for customers for whom you don’t have first-party data.

It doesn’t matter so much what they are normally interested in or what they’ve bought before when you’re sending out a marketing message about buying their mother something before May 10. However, if you do have information about the customer, say you know they’ve ordered flowers for their mother last year, then you can combine the trending recommendation with what you know about their behavior.

Read more in

Advanced Segmentation and Automation Are Changing the Marketing Game

Pick a Pumpkin for Perfectly Personalized October Marketing

  Pick a Pumpkin for Perfectly Personalized October Marketing

by Ariella Brown

We in the 2020s, and it's time for marketers to take a more inclusive approach for their messaging this season. Not everyone celebrates Halloween, and even those who do are likely to be scaling it back  this year.

Halloween is a major occasion for sales in a normal year as close to 70% of Americans, according to Statista,  celebrate. Ever think about the 30% that don’t? 

This is a good year to take them into consideration.

A combination of outright restrictions and individual choices are  taking parades, traditional trick-or-treating and big bashes  off the table for October 31. Consequently, even people who normally do shell out the NRF’s estimated average of  $86 and change  for the day are expected to spend less this year, reports Market Watch.

But that doesn’t mean that October is a bust for marketing. On the contrary, there are opportunities to effectively target customers by understanding what this point in the calendar means to them. 

That means identifying what kind of pumpkin resonates with your customer: Is it  a jack-o’-lantern, an ordinary gourd, or pumpkin spice flavor? 

Jack-o’-lantern marketing

https://p0.pikrepo.com/preview/471/304/jack-o-lantern-on-brown-surface-thumbnail.jpg

These customers are the prime target for straight-up, over-the-top Halloween marketing. Even among them, though, there are still distinct segments, and marketing should be targeted accordingly. 

You have your customers who think of it as a celebration centered around children and who want the products and imagery to reflect that. Think cartoon-style ghosts and witches to go with your classic or plastic jack-o’-lantern.

For those at a different stage of life, Halloween may be about adult parties where alcohol is served and where the spookiness rating goes from G to R. Imagery for that is more realistic and possibly more risque. 

How to know which witch to go with for your messaging? Segment your communication.

Plain pumpkin marketing

The picture above is from the Bed Bath & Beyond site. The classic harvest setup is the one that was chosen for the cover of the catalogue it sent me with the “let’s get this fall rolling” emblazoned on it.

The decor is about celebrating Fall rather than Halloween, though even that can come with different vibes, according to one’s particular taste. It makes sense for Bed Bath & Beyond to target the plain pumpkin type of customers because they make up the general Fall market.

That market is far-reaching, extending from food to fashion, cosmetics to decor, even blankets needed for cooler nights. Bed Bath & Beyond carries items from all of those categories.

For those who want a particular date to which to tie their purchases, this year there is 10/10. As Bloomberg reported, the designated shopping day is inspired by China’s Singles’ Day, which sparks record levels of shopping every year on 11/11.

This new October shopping event is the brainchild of Deborah Weinswig, a retail consultant. She told Bloomberg that she has been pressing for it for years, though this year retailers finally embraced it in the hopes of starting December shopping earlier to make sure inventory and delivery can keep up with demand.

Pumpkin spice marketing mystique

For some, ordinary pumpkins just don’t cut it. But pumpkin spice is another matter, particularly the latte associated with the flavor that owns the acronym, PSL.

The pumpkin spice mystique is not just about the flavor; it’s about building a connection with customers based on anticipation and engagement. Starbucks does it brilliantly.

Beginning in August, Starbucks kicks up the buzz as speculation about when the first one of the new season will be poured builds. Starbucks deliberately switches the date of release each year to maintain the mystery and increase anticipation.

Even brands that don’t sell anything associated with pumpkin spice directly can apply this marketing approach. When you want to build up to the launch of a new product, a special event, or even a return of a seasonal item, you can let your customers know to look out for it and build their excitement.

A similar approach can work for just about any retailer who can deliver the right message to connect with customers. It’s all about finding what they will find relevant to them and segmenting accordingly.

This season, the marketers that show they really know their customers are the ones who will deliver the inclusive and on target communication. They know that one pumpkin does not fit all.

 

For a literary connection for pumpkin spice marketing, see 

From Shakespeare to Starbucks: Pumpkin spice marketing mystique  

Why you need a little Christmas in your marketing earlier this year

From key search terms to AR-powered ads, this holiday season is a boon to brands that capitalize on digital opportunity and get in the game early.

Among the many shifts in shopper behavior thriggered by the global pandemic is that of thinking about the December holidays as early as April. Marketing insights from Pinterest and Facebook were already published in June, so businesses can start to gear up earlier than usual.
Dreaming of the holidays under lockdown

In June, Pinterest put out its guide to marketing with the apt title, Earlier Than Ever Holiday 2020. While pinners always show earlier holiday activity than the public at large, this year, they were thinking of Christmas as early as April.

Pinterest reports that its search volume on terms like “Christmas gift ideas,” “holiday recipes,” “Christmas,” “holidays,” and “Christmas decor” were 70% higher in April 2020 than for April 2019. Clearly this past April was different from those of other years.

By then a fair amount of us were told to stay home to stay safe under lockdown conditions with no clear end in sight. Feeling both bleak and bored at home, it’s no wonder that people felt they could use a little Christmas right this very minute.

Cue up the song from Mame:

at were t

“As the coronavirus pandemic grips us with anxiety and fear, we should all follow Mame's lead and light up the night with holiday lights and lighthearted music.” That’s the comment from April 2020 on the video.

From dreaming to planning and shopping

One major difference to note between the two guides, though is this: While Facebook does draw on some data from 2020 to account for the pandemic’s impact, it primarily draws its holiday trends from 2019, in contrast to Pinterest’s focus on 2020 for holiday searches.

Read more in
Holiday Season Arrives Early for Data-Driven Marketing

Data quality check

You may have heard the expression, quality doesn’t cost -- it pays. A more precise formulation applies to business in the form of the 1-10-100 rule of data quality. The idea is that while it could cost you $1 to corroborate the data upon entry, it costs $10 to clean it later and $100 to leave it uncorrected due to the various losses that will result from it. How to prevent that happening? Adopt a CDP solution.

Losses due to poor data quality cost the US economy $3.1 trillion annually, according to IBM’s 2016 estimate, and concern about data quality has risen since then. According to Dunn & Bradstreet’s 6th Annual B2B Marketing Data Report, it grew from 75 percent in 2016 to 89 percent this year. It also found that only half of those surveyed express confidence in their own data.

Read more in 

3 Tips for Achieving Customer Data Quality

Banking on Data

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Very few people seem to express warm, fuzzy feelings about banks. In fact, they are more  20 point drop in public trust in 2018. 

likely to have cold, prickly feelings about them. Financial services institutions suffered a

So what can banks do to try to attract and retain loyalty? Aside from asking banking customers directly, how would banks find out what people really think of what they’re doing? They could tap into social data. That’s what Crimson Hexagon did with in a report that compares two bank brands: BNP Paribas and Santander. 

The report is based on an exploration of five years’ worth of online conversations related to these two large bank brands.  Data was culled from “Twitter, Facebook, Reddit, blogs and forums – a wide range of locations where consumers gather to discuss various topics.” 

Read more in 

Data You Can Bank On

Wearables Pose Security Risks

Takeaway: Thanks to the advance of IoT, the market for wearables keeps expanding to the point that it should hit 50 billion devices by 2020. While these devices offer hands-free convenience for specific functions, they also introduce new points of vulnerability that can be opportunities for hackers.

Cisco predicted that by the year 2020, 50 billion new wearable devices will be connected through the IoT. This increases points of connection exponentially, and that translates into a huge opportunity for hackers.

Demonstrated Hacks

That wearable devices like Fitbits can be be manipulated through acoustic interference was demonstrated by a number of research experiments. It’s true that there are no immediate ramifications of a nefarious nature other than possibly gaming the count of one’s steps, but the researchers do warn of this: “For instance, should one trust the step count from a Fitbit as evidence for an alibi?” How can it be relied upon if it’s possible to inflate the number of steps through a hack?

This is a question of reliable accuracy, but sometimes it is the accuracy itself that poses a problem. Wearables might be picking up accurate information that is traced directly to the individual and so reveal quite a lot.

Read more in Hacking Wearable Tech: The Potential Danger of Advancing Wearable Technology

Extracting marketing value from data

As businesses strive to become more data-driven, the challenge lies not amassing data for
data's sale, but in getting the right data.

According to research from Harvard Business Review, data records are so prone to critical errors that less than three percent of data meets basic quality standards. Accuracy matters, and banking on the wrong data can translate into serious business losses. In 2016 IBM estimated that losses due to poor data quality cost the US economy $3.1 trillion annually

Gary Read, CEO of Import.io, a web data integration solution provider, spoke about how his business gathers data from publicly available websites and puts it into a common format to enable organizations to gain insights that can inform their marketing strategy.  What Import.io does is take care of the data so that businesses can focus on the insights.

Read more in 

Tapping Data for Marketing Insights

A different lookalike strategy to fit GDPR

Privacy concerns, and the need for GDPR compliance for any company that is globally connected has made it necessary for brands to find ad targeting alternatives.

The question is: are marketers going to step back, or take a step forward, with a new paradigm of lookalike data?

The trend in programmatic advertising has been to tap into more -- and more -- data about individuals, to deliver more personalized approaches. But with the rise of GDPR, not all data is fair play in the EU, and that changes the rules of the game.

Some companies are rolling back personalization and reverting to more traditional forms of contextual advertising. Others are looking forward by leveraging data in new ways.  

Earlier this week, Cedato officially released its Contextual Lookalike Targeting technology for programmatic video. 

Read more in 

Redefining Lookalike Strategies For GDPR Compliance

The Personal Touch in Marketing

Digital platforms open up new opportunities to reach people wherever they are on multiple devices and to pick up reams of data to feed into marketing campaigns. But with thousands of forgettable, repetitive ads coming at people every day, the challenge is not merely to blend into the background noise, but to offer relevant and personalized communication.

The second Adweek Executive Lab, which took place on Tuesday in New York and was sponsored by Tapad, included several discussions about using data to achieve personalization.

Read more in The Challenges of Drawing on Digital Data for Customized Communication

Everybody lies with visualizations

Photo by Ashkan Forouzani on Unsplash

As I wrote here, before it became trendy to point out the problem of fake news, I explored how data visualizations can mislead people. I’ve noticed that in the last couple of years, data visualization has become a major focal point.  The old maxim of “Seeing is believing” is the real driving force behind visualizations of data.  While not all of us relate to spreadsheets, we tend to respond well to graphs, charts, and other visually appealing renderings of those numbers.  

While we can all fall for it, we can immunize ourselves to some extent with vitamin C. 

Back in 2016, I identified three key C's in a Baseline article, Data Visualization: You Must 'C' It to Believe It: Context, Correlatin, and Causation. 

Context: This includes contextual information for the graphs, which sometimes indicates that the results visualized represent outliers rather than typical results. Getting the context also requires getting the baseline for the survey, including timelines, locations, and the population size and type used to get the numbers.
As data visualization tools include ways to slice and dice your data, it is not all that difficult to zero in on just the segment that yields the results you want. So you need to know the larger context, as well as any added-in points that are outside that particular context.
Correlation: This is the supposed strongpoint of visualizations: showing up correlations. But they are easily manipulated and misleading, as there are many correlations of time that are not necessarily causally connected—though visualizations can make them appear that they are.
Causation: This is what real insight is all about: finding out what causes what. There is no substitute for thinking this through, no matter how seductive it may be to simply go with the correlations presented by the visualization.

In revisiting an argument offering data visualization as proof, I've come to add some additional C tests:

• Correspondence to reality. Just because someone claims expertise doesn't mean they are completely correct about their assertions. For example, when I was in labor with my first baby, the doctors and nurses at the hospital just dismissed my pains, claiming the contractions were "mild" and that the birth was far from imminent. I was not the expert; they were, but I knew that I felt the baby coming. As it turned out, the resident barely got to me in time. I learned from that experience that you should not be gaslighted by expert views that directly contradict not what you just think you know but what you do know and directly experience. 
• Convenience: This pertains to both means and ends. Convenience of means refers to using the data that is on hand or easily measured even if it's not necessarily the data that is the most relevant. It's rather like measuring how much snow fell on your windowsill because it's easy to reach rather than going out to get the measure on the street and in drifts to get a more accurate measurement. Convenience for ends is about selecting data that you can easily fit into the conclusion you wish to draw AKA cherry picking. 
• Confirmation Bias:In general, when you look for data on something, you have to bear in mind that absolute objectivity is rare. Many of us have deeply-seated values and beliefs that will not allow us to entertain the possibility that we are on the wrong track,which would skew our results because of what we allow and disallow in the data set. It is the equivalent to painting a bull's eye around where your arrow went. So ask yourself, does the person have some personal agenda that could be coloring the outcome? If so you should treat them with the same healthy skepticism you would treat cigarette tobacco studies sponsored by tobacco companies. 
• Certainty Camouflaging Contingencies: Few things are absolutes, so if someone states something without qualifiers, likely something is being hidden or glossed over -- like the fact that the data is out of date or taking searches of racist terms and jokes as proxies for the person being a racist and then shifting labels from what actually is measured to what the person says is signified by the measurement. This leads to a triple F: Fudging Figures and Facts.

All of these were inspired by an argument made in Seth Stephens-Davidowitz's book Everybody Lies. Read more about it in Sex, Lies, and Data Profiles

Related post: 

DATA VISUALIZATION: YOU HAVE TO C IT TO BELIEVE IT

Marketing for Mom's Day

Vintage mom image from
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Vintage-Apron-Mom-GraphicsFairy-463x1024.jpg

A mother's love may be priceless, but there is definitely a price tag on Mother's Day. 

While Mother's Day does not have the status of a federal holiday like Easter, in fact, it occasions significantly more spending. The National Retail Foundation (NRF) forecasts that this year's Mother's Day spending will reach $23.1 billion.  For comparison, this year’s Easter spending was estimated to be $18.2 billion.  

Obviously, marketers have to seize the day for their brands, particularly if their brands feature jewelry. That's the top choice of gift for the day. According to the NRF's survey, 34% of shoppers intend to buy something in that category, bringing that total spend to an impressive $4.6 billion.

While many jewelry brands are, no doubt, sticking to the standard sentimental messages, some are breaking out of the box in their depictions of different types of mothers with strengths that go beyond the stereotyped image of a woman in an apron. Crimson Hexagon's data on what people are talking about the most and what garnered the most positive conversations. It uncovered some fresh takes in mother images in some jewelry campaigns, as well as some surprises.

Read more in Mother's Day Marketing

See some of the ads featured below:

Alex and Ani's “Symbolize Your Love” campaign includes the outtakes of commercials filmed with real people (which fits very well with increasing demands for authenticity in marketing)

Can Facebook Prevent Suicide? Ethical Questions Arising from AI

In today’s hyperconnected world, we are generating and collecting so much data that it is beyond human capability to sift through it all. Indeed, one application of artificial intelligence is identifying patterns and deviations that signal intent on posts. Facebook is using AI in this way to extract value from its own Big Data trove. While that may be applied to a good purpose, it also raises ethical concerns.

Where might one get insight into this issue? In my own search, I found an organization called PERVADE (Pervasive Data Ethics for Computational Research). With the cooperation of six universities and the funding it received this September, it is working to frame the questions and move toward the answers.

I reached out to the organization for some expert views on the ethical questions related to Facebook’s announcement that it was incorporating AI in its expanded suicide-signal detection effort. That led to a call with one of the group’s members, Matthew Bietz.

Bietz told me the people involved in PERVADE are researching the ramifications of pervasive data, which encompasses continuous data collection — not just from what we post to social media, but also from the “digital traces that we leave behind anytime we’re online,” such as when we Google or email. New connections from the Internet of Things (IoT) and wearables further contribute to the growing body of “data about spaces we’re in,” he said. As this phenomenon is “relatively new,” it opens up new questions to explore with respect to “data ethics.”

Read more in 

The Ethics of AI for Suicide Prevention

AI for Customized Consumer Communication

As AI advances, it's reshaping marketing with new ways of pulling in data and insights to reshape and customize consumer communication. Its impact on marketing was explored in a recent NYC Media Lab white paper, "How AI Is Changing Media Economics."

 Now it's possible to apply real time analytics to a campaign that is tested, tweaked, and tailored to an audience. 
Read more in 

AI: The Ultimate Game-Changer for Media