Location connecting social and marketing

Location-Based Social Marketing

For extreme introverts the great thing about social media is that you never have to see your connections in real life. But for people who like to actually interact with people face-to-face, as well as the businesses that seek to get people in a physical door, that can actually be a shortcoming. Location-aware social media can bridge that gap between the virtual and physical.

Location awareness is what distinguishes the Locye social media platform. It allows users to “observe social activity at real-time hotspots and places of interest worldwide” and to post content that those nearby can see. For those who don't want to give too much away, there is an option to post anonymously. Users can also select whether they want their posts kept up for just a day or for a virtual eternity. 

Locye's Founder and CEO, Sajjad Mustehsan, discussed the platform's potential for marketing with me. He said that it “will soon be offering business-to-consumer marketing capabilities” with three defining characteristics:

Read more in Location-Based Social Marketing

The problem of visibility in today's complex supply chains

Supply chains today are integral to building a competitive advantage. As they grow in complexity, those who manage them acknowledge that they do not have as full visibility as they should. Technological solutions can point the way to more visible, better managed, and more efficient supply chains that deliver better value for companies and their customers.

While there is wide variation in the supply chains of various businesses, there are still some identifiable trends. The 2017 GEODIS Supply Chain Worldwide survey (PDF) delves into some of them. The report draws on the responses of 623 professionals in 17 countries from various functions related to the supply chain, including finance, operations, marketing, strategy, IT, and management.

The majority (67%) of people surveyed in a position of supply chain leadership rank as C-Level or top management. This does appear to play some role in successfully strategies because businesses in which that position is help by “a middle manager seem less profitable.”

The top concerns for those who responded to the survey were, not surprisingly, “containment of their costs (32%).” That fits with their awareness of dealing with “global competition (28%).”  However, more than half (57%) reported that they see “Supply Chain as a competitive advantage, enabling the development of the company and not” merely an area in which to reduce expenses.   

Read more in 

Today’s Complex Supply Chains Demand Visibility Solutions

Data Scientist Interview

Domingos Lopes is about to begin a new job involving machine learning at Google after having completed the NYC Data Science Academy 12-Week Data Science Bootcamp. He came in with a strong math background, having earned a PhD in that field from NYU in 2016. After deciding that he did not want his job prospects to be limited to academic settings, Lopes decided that the best course of action was to acquire data science skills. In addition to the technical skills like Python fluency, he expects to draw on the ability to communicate data insight and work effectively in a team setting as he embarks on his career at Google.

Read more in https://www.switchup.org/blog/alumni-spotlight-domingos-lopes-hired-at-google

Wait, what?

This is not a post on the popular book that bears that title. (I did write about that here:  uncommoncontent.blogspot.com.) This is my reaction to the number a billion that sounds impressive but is really completely meaningless without context.*

When I shared a link today on LI, it offered me three other links to read. Among them was a FastCompany article, "Six Ways YouTube Is Primed For The Future (And Four Areas That Need Work)" Now read what it says for the fifth and see if you have the same reaction I do:

5. YouTube’s rebuilt algorithms have led viewers to watch 1 billion hours of video a day. YouTube is optimized for what it calls “watch time,” which encompasses what users view, how long they tune in, the length of their overall YouTube session, and so forth. Together, these signals help YouTube algorithms decide which videos a user is most likely to watch shortly after they’re posted and which will lead to the longest overall viewing period.

Do you get what's missing here? How many viewers are there? How many hours did they watch before the algorithms were rebuilt?

Without those two pieces of information, we really have no way of knowing how much of an advance one billion hours of video a day represents. Sure, it sounds like a lot, but we don't know if it represents the two billion people watching an average of a half an hour a day or one billion watching an average of an hour, or half a million watching two hours.

 We also don't know if the actual goal was to bring in more viewers or to keep the ones already watching on the channel for longer. That's a pretty important piece of context, as well, if one is to judge if the algorithms are accomplishing what the company intended for them. The article does refer to 800 million YouTube consumers of music but doesn't clarify whether or not that represents the viewers in total and if that number represents an increase over the number before the adjustment to the algorithms.

The bottom line is this: Don't be dazzled by numbers, no matter how large, that are presented without the relevant context.


*Related post http://writewaypro.blogspot.com/2016/10/data-visualization-you-have-to-c-it-to.html
http://uncommoncontent.blogspot.com/2017/09/missingness-at-museum.html

Expanding comments with AI

The problem with human moderators is that they have human limitations that cannot keep up with a

pic from https://d1avok0lzls2w.cloudfront.net/img_uploads/Blog-Comments.jpg

huge influx of comments. That was the problem the New York Times faced in balancing reader comments demand with an editorial standard of civility for all published comments. Its solution was a partnership with , an incubator owned by Google's parent company, Alphabet.

Back in September, the Times announced the partnership in an article that set out the challenge faced by its 14 moderators tasked with reviewing the comments on the 10% of articles that do allow them. That alone amounted to 11,000 comments a day. As the article invited readers to try their hand at moderating, it was entitled Approve or Reject: Can You Moderate Five New York Times Comments?

I took the test. The official summary of my results were: "You moderated 4 out of 5 comments as the Community desk would have, and it took you 81 seconds. Moderating the 11,000 comments posted to nytimes.com each day would take you 49.5 hours."

That summation was followed by this: "Don't feel too bad; reviewing all of these comments takes us a long time, too." According to my calculations, however, the Times actually allows more time for their moderators. Given 14 people working 8 hours a day, the number of working hours each day would be 112, or more than twice the number of hours they said would be required for my rate of moderation.

That investment of so many hours is not something they regret, as they regard it as a requisite part of building up "one of the best communities on the web." However, they recognize that needs must dictate a new approach. That's where the machine assistance enters into the picture, enabling the same number of humans to effectively moderate a much larger number of comments and reduce the delay for reviewing time.

Flash forward to June 13, 2017, and the Gray Lady herself announces: The Times Sharply Increases Articles Open for Comments, Using Google's Technolog

Read more in How AI Can Moderate Comments, Eliminate Trolls

Personalized video marketing

“What's in a name?” Possibly quite a lot when it comes to personalized marketing.

Several months back I received a marketing email from Sprinklr that was rather ironic given its message about effective use of data. It opened like this: “ Hi {lead.First Name:default=}.”  Obviously, something went wrong, and I saw the code rather than my name.

Of course, personalized emails are not all that unusual any more, so some marketers have upped their game with personalized video. After receiving the “A Dog's Purpose” video (above) — in a correctly personalized email — I contacted Adgreetz's co-founder and CEO Eric Frankel about what data is used for this kind of personalized video marketing, and how the video was delivered to people who are 1) dog owners, and 2) have a dog of that particular name? 

read more in A Marketer's Best Friend

Define "good"

I don't mean that in an abstract way or with the kind of depths of thought about what we mean by "qulity" that drove the author of Zen and the Art of Motorcycle Maintenance toward madness. I just mean it in the context of "good pay."  The question arises from this job posting:

We pay really well because we want really good content.
“Really good content” means well-constructed, well-reasoned arguments that are also extremely engaging.
Articles need to be a minimum of 500 words, though analysis pieces need to be a minimum of 1,000 words
We provide you with the headlines and an initial source
We’re looking for both weekday AND weekend writers. There’s a bonus for weekend writers.
We often promote writers to management positions

Ah, I think, they say they have high standards but compensate accordingly, so I was picturing a minimum of three figures and not just with a one or two at the beginning of the number. But my illusions about some shared view on what constitutes "good" pay was shattered an instant later as I read on:

What We’ll PayPay will start at $15/article during the test period. Afterward, we’ll bump it to $20/article for weekday news articles, and $30/article for weekday analysis articles. Weekend news articles are $25/article and weekend analysis pieces are $35/article. 

So, basically, they'll pay you what teen babysitters get per hour for an article that should take you several hours to write.  Certainly, any beginning writer -- and that's the only kind who likely would apply for this job -- would likely need more than hour to crank out an article of that length that is not merely recycled platitudes.

Related: http://writewaypro.blogspot.com/2017/05/on-working-almost-for-free.html
http://writewaypro.blogspot.com/2016/05/writing-for-free-is-not-deductible.html
http://writewaypro.blogspot.com/2016/05/an-idiots-guide-for-writers.html

AI gets a boost from curiosity

As data analytics become increasingly driven by artificial intelligence (AI),

photo credit: https://c1.staticflickr.com/3/2332/2083892100_3e015d810a_b.jpg

researchers search for a way to drive machine learning. The key ingredient its future development may be a dash of curiosity.

There are all kinds of AI systems currently used by various businesses with different names like Alexa and Albert to personalize then. Perhaps it's time for an AI system named George after the monkey whose curiosity propels him into various adventures.

That would be an apt choice for the Intrinsic Curiosity Module (ICM) developed by a group of four researchers at University of California, Berkeley. The attempt to inject curiosity to achieve self-motivated advances in machine learning was the subject of their paper, Curiosity-driven Exploration by Self-supervised Prediction, that was just submitted to the 34th International Conference on Machine Learning (ICML 2017).

Their premise is that external rewards for learning are of necessity limited and actually rather rare in real life. That doesn't mean that people stop exploring or seeking out answers even when there are no prizes for doing. They are motivated by their own human curiosity. Infusing that kind of motivation in a virtual agent gets it to test things out for itself even when not directed to do so. The test of the effect was done in monitoring how far it would proceed in two video games, VizDoom and Super Mario Bros. as you see in the demo video here:

Read more in Machine Learning Taps Power of Curiosity

Getting insight on all the channels with AI

Marketers have access to more data on their customers than ever before. The challenge is getting rapid insights from all the channels used, in time to act effectively. One solution is an  AI-powered customer retargeting platform for omni-channel marketing operations. Abhi Yadav, ZyloTech's  co-founder and CEO, spoke to me about the function of AI in omni-channel marketing.

ZyloTech, formerly DataXylo, launched in 2014 as an MIT spin off. Its advisory teams includes PhDs in AI, data scientists, and other marketing experts from the university. The platform uses machine learning to analyze all customer data continuously, and in near real time, for actionable insights on omnichannel marketing.

In the current environment, marketers really have “no way of knowing whether the individual” targeted by the ad “is a new, lost, inactive, loyal or brand-conscious customer,”  says Yadav.

Read more in An AI Approach to Omnichannel

On working almost for free

Someone I did some freelance work for a few years back contacted me to inquire about writing for his current company. The exchange on LinkedIn messaging went like this:

Hi Ariella, Not sure if you remember me from my ___ days but I am looking for a freelancer to help out with blog posts across two products here at ____. I don't remember what your pricing was but I do remember that you made my life a whole lot easier. Can you send me what you were asking?

 I assured him that I did remember him and asked what kind of articles he had in mind. His response:

• product focused
• and a bit of thought leadership
• Just so I can make sure, does $50 for an 800 word article work?

I wrote back:

I'm assuming you dropped a zero there.

Surprisingly enough, he said:

I did not. Our content director informed me that is what we normally pay for an 800 word article. Understood if that is way too cheap. 

That was far below my rate even when I first started freelancing (and he knows it's a tiny fraction of what was paid by his previous company, which is why I had assumed he dropped a zero).  But I am not one to throw away opportunities in a snit. I said my daughter may do it for that rate. After all, she is willing to work for free for college internships. So I'll let her take a crack at it. At least, it will be a learning experience and resume builder for her.

Related posts http://writewaypro.blogspot.com/2016/05/writing-for-free-is-not-deductible.html

 http://writewaypro.blogspot.com/2016/05/an-idiots-guide-for-writers.html
https://www.linkedin.com/pulse/college-internships-real-story-ariella-brown-phd-1

AI for customer service

AI is changing our everyday interactions. What once required a human rep can now be handled by a

(Image: panuwat phimpha/Shutterstock)

virtual assistant whose programming allows customer problems to be solved more quickly.

A recent Venturebeat article declared, "AI chatbots are the next big shift in customer service." Those of us of a certain generation expect to wait on a line or on the phone for a person to take care of our customer service issues. But the generation that favors texts to calls has come to have different expectations.

Read more in  Why Machine Learning Can Improve Customer Service

The eyes have it with AI

The camera is already starting to replace the keyboard,” asserts Netra CEO, Richard Lee. The content that will dominate digital information flow will be visual, and for that reason image recognition is becoming a key component of marketing.

His company derives insight from visual data, fostering understanding of how consumers engage with brands through engagement with images. Netra  is a leader in visual intelligence and search that uses machine learning to help marketers make sense of imagery on social media.

Some brands are already using image recognition to connect with and effectively market to their customers. They include Neiman Marcus. The upscale retailer offers its customers the Snap. Find. Shop  app that enables them to use their phones to snap pictures of styles they like and find similar styles carried by the store.  The app is demonstrated here:

The app allows customers to bypass typing in description of the clothing and rely on the image alone to convey what they seek. That kind of search is what we will be seeing more of in future, according to Lee. 

Read more in AI Makes Visual Intelligence Possible

Renewables take to the waves

For major electronics OEMs, transitioning to renewable energy entails not only using it in their own factories but calling on those that supply components to do the same. Apple has done just that. As a result, many of its suppliers are turning to solar and wind power, and some are even reaching out to sea to get it. 

As Bloomberg recently reported, for its own operations, Apple can boast of using tapping into renewables for 96% of its own energy use. That includes not only the corporate offices Lisa Jackson, Apple's vice president in charge of sustainability and government affairs, says, but also “our data centers, our stores, even our distribution centers.” However, as she told Bloomberg Television, the company is resolved to do even better by “moving onto our supply chain.” 

As Apple posted in March, together with its suppliers, the company anticipates that by the end of next year, it “will be generating over 2.5 billion kilowatt hours per year of clean energy.” To put that in perspective, that is tantamount “to taking over 400,000 cars off the road for a year,”  the company said.

Apple’s goal of reaching 100% renewable energy for its production entails getting its suppliers to commit making the necessary changes for their energy sources. Apple now has seven supplier companies committed to renewable energy. Among them is Ibiden. It has the distinction of being the first company in Japan to commit to use only renewable energy in producing components for Apple.

Ibiden is set for renewable energy production that is anticipated to “produce over 12 MW of solar power — more than the energy they need for Apple manufacturing — and support Japan’s nationwide efforts to limit its carbon emissions.” In addition to standard facilities, Ibiden’s energy will come from “one of the largest floating solar photovoltaic systems in the country.” By floating the solar panels, energy can be harvested from the sun without taking up limited land space in Japan.

This trend of moving out to the water to harness renewable energy is also being applied to wind power.

Read more in 

Innovation in Renewable Energy Greens Supply Chain

Mother's Day Marketing

Public domain pic at http://www.publicdomainpictures.net/pictures/170000/velka/muttertag-14609069654cp.jpg

Motherhood may be priceless, but there actually is a price tag associated with Mother's Day. Given that the market for this particular holiday is expected to hit a record-high this year, savvy marketers have already put their brands in the game.

On the second Sunday in May, Americans take time out to show appreciation to their mothers, typically with cards, flowers, dinners out, and other assorted gifts. All that adds up to $23.6 billion, according to NRF's forecast.

In anticipation of this substantial spending occasion, you'd expect to see massive marketing campaigns. But it seems that brands are not doing quite as much as they could. I popped into Target and saw only minimal signs of the imminent holiday represented by a few Mother-themed mugs in the front section, as well as the usual cards.

I shared what I've seen with Mike McMaster, VP of Lead Generation at JumpCrew. He said he noticed the same at a mall he visited over the weekend. With the exception of Macy's, he observed very little Mother's Day marketing.

The stores who fail to address the upcoming holiday in their setups are missing out on “the two Ps in marketing,” McMaster says. That refers to “placement and promotion” with targeted positioning of merchandise that ties into the promotional theme of Mother's Day.

Read more in Mother's Day: Price Tags and Hashtags

AI Transforms Business Data Models

(Image: pixone/iStockphoto)

As big data continues to grow, extracting value from it calls for new tools.

Increasingly, businesses that rely on data to drive decisions are applying AI to surface actionable insight quickly and accurately.

Finding innovative solutions to the problems raised in data analytics, particularly with respect to adapting machine learning to credit scores, is what they've been working on for the past six years at Experian's DataLabs. The EVP and Global Head of the labs, Eric Haller, spoke to All Analytics about the new direction for predictive modeling.

Read more in

AI, Machine Learning Power Transformation