The Double Loop Podcast Discusses Research From the Self-Styled “Inventor of Cross-Fingerprint Recognition”

(Part of the biometric product marketing expert series)

Apologies in advance, but if you’re NOT interested in fingerprints, you’ll want to skip over this Bredemarket identity/biometrics post, my THIRD one about fingerprint uniqueness and/or similarity or whatever because the difference between uniqueness and similarity really isn’t important, is it?

Yes, one more post about the study whose principal author was Gabe Guo, the self-styled “inventor of cross-fingerprint recognition.”

From https://www.linkedin.com/in/gabeguo/.

In case you missed it

In case you missed my previous writings on this topic:

But don’t miss this

Well, two other people have weighed in on the paper: Glenn Langenburg and Eric Ray, co-presenters on the Double Loop Podcast. (“Double loop” is a fingerprint thing.)

From https://doublelooppodcast.com/about-us/.

So who are Langenburg and Ray? You can read their full biographies here, but both of them are certified latent print examiners. This certification, administered by the International Association for Identification, is designed to ensure that the certified person is knowledgeable about both latent (crime scene) fingerprints and known fingerprints, and how to determine whether or not two prints come from the same person. If someone is going to testify in court about fingerprint comparison, this certification is recognized as a way to designate someone as an expert on the subject, as opposed to a college undergraduate. (As of today, the list of IAI certified latent print examiners as of December 2023 can be found here in PDF form.)

Podcast episode 264 dives into the Columbia study in detail, including what the study said, what it didn’t say, and what the publicity for the study said that doesn’t match the study.

Eric and Glenn respond to the recent allegations that a computer science undergraduate at Columbia University, using Artificial Intelligence, has “proven that fingerprints aren’t unique” or at least…that’s how the media is mischaracterizing a new published paper by Guo, et al. The guys dissect the actual publication (“Unveiling intra-person fingerprint similarity via deep contrastive learning” in Science Advances, 2024 by Gabe Guo, et al.). They state very clearly what the paper actually does show, which is a far cry from the headlines and even public dissemination originating from Columbia University and the author. The guys talk about some of the important limitations of the study and how limited the application is to real forensic investigations. They then explore some of the media and social media outlets that have clearly misunderstood this paper and seem to have little understanding of forensic science. Finally, Eric and Glenn look at some quotes and comments from knowledgeable sources who also have recognized the flaws in the paper, the authors’ exaggerations, and lack of understanding of the value of their findings.

From https://doublelooppodcast.com/2024/01/fingerprints-proven-by-ai-to-not-be-unique-episode-264/.

Yes, the episode is over an hour long, but if you want to hear a good discussion of the paper that goes beyond the headlines, I strongly recommend that you listen to it.

TL;DR

If you’re in a TL;DR frame of mind, I’ll just offer one tidbit: “uniqueness” and “similarity” are not identical. Frankly, they’re not even similar.

Will Ferrell and Chad Smith, or maybe vice versa. Fair use. From https://www.billboard.com/music/music-news/will-ferrell-chad-smith-red-hot-benefit-chili-peppers-6898348/, originally from NBC.

Intelligently Writing About Biometrics

Let’s say that your identity/biometric firm has decided that silence ISN’T golden, and that perhaps your firm needs to talk about its products and services.

Silence is not an optimal communication strategy. By Lorelei7, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=3164780

For example, let’s say that your firm fights crooks who try to fraudulently use synthetic identities, and you want to talk about your solution.

So you turn to your favorite generative AI tool to write something that will represent your company in front of everyone. What could go wrong?

Battling synthetic identities requires a multi-pronged approach. Layering advanced technology is key: robust identity verification using government-issued IDs and biometrics to confirm a person’s existence, data enrichment and validation from diverse sources to check for inconsistencies, and machine learning algorithms to identify suspicious patterns and red flags. Collaboration is crucial too, from financial institutions sharing watchlists to governments strengthening regulations and consumers practicing good cyber hygiene. Ultimately, vigilance and a layered defense are the best weapons against these ever-evolving digital phantoms.

From Google Bard.

Great. You’re done, and you saved a lot of money by NOT hiring an identity blog writing expert. The text makes a lot of important points, so I’m sure that your prospects will be inspired by it.

Bot-speak is not an optimal communication strategy either. Generated at craiyon.com.

Well…

…until your prospects ask what YOU do and how you are better than every other identity firm out there. If you’re the same as all the other “me too” solutions, then your prospects will just go with the lowest price provider.

So how do you go about intelligently writing about biometrics?

No-siree.

Intelligently writing about biometrics requires that you put all of this information together AND effectively communicate your message…

…including why your identity/biometrics firm is great and why all the other identity/biometric firms are NOT great.

If you’re doing this on your own, be sure to ask yourself a lot of questions so that you get started on the right track.

If you’re asking Bredemarket to help you create your identity/biometric content by intelligently writing about biometrics, I’ll take care of the questions.

Drive content results with Bredemarket Identity Firm Services.

Oh, and one more thing: if you noted my use of the word “no siree” earlier in this post, it was taken from the Talking Heads song “The Big Country.” Here’s an independent video of that song, especially recommended for people outside of North America who may not realize that the United States and Canada are…well, big countries.

From https://www.youtube.com/watch?v=cvua6zPIi7c.

I’m tired of looking out the window of the airplane
I’m tired of traveling, I want to be somewhere

From https://genius.com/Talking-heads-the-big-country-lyrics.

Get the Balance Right

Have you ever created content that contradicts itself?

Let me take you back to 1978, when the Who released an album entitled “Who Are You”—whose title song is beloved by identity/biometrics professionals over 45 years later.

Fair use. From the album “Who Are You.”

But there’s another song on the album that seems at first glance to speak to the times of 1978.

Bands of the last decade like the Who had apparently been eclipsed by bands like the Sex Pistols, a band that had already imploded.

In this environment, the Who recorded a song called “Music Must Change,” a song that seemed to speak to the changing of the guard.

Until you listened to the song’s obscure lyrics and orchestral backing, which makes as much sense as an entire double album about a musician spitting at his audience. (That album would come in 1979.)

Meet the new song…same as the old song.

From https://youtu.be/ROG9llPP9qE?si=nyeRi2bXIiOCjNUh.

Did the Columbia Study “Discover” Fingerprint Patterns?

As you may have seen elsewhere, I’ve been wondering whether the widely-publicized Columbia University study on the uniqueness of fingerprints isn’t any more than a simple “discovery” of fingerprint patterns, which we’ve known about for years. But to prove or refute my suspicions, I had to read the study first.

My initial exposure to the Columbia study

I’ve been meaning to delve into the minutiae of the Columbia University fingerprint study ever since I initially wrote about it last Thursday.

(And yes, that’s a joke. The so-called experts say that the word “delve” is a mark of AI-generated content. And “minutiae”…well, you know.)

If you missed my previous post, “Claimed AI-detected Similarity in Fingerprints From the Same Person: Are Forensic Examiners Truly ‘Doing It Wrong’,” I discussed a widely-publicized study by a team led by Columbia University School of Engineering and Applied Science undergraduate senior Gabe Guo. Columbia Engineering itself publicized the study with the attention-grabbing headline “AI Discovers That Not Every Fingerprint Is Unique,” coupled with the sub-head “we’ve been comparing fingerprints the wrong way!”

There are three ways to react to the article:

  1. Gabe Guo, who freely admits that he knows nothing about forensic science, is an idiot. For decades we have known that fingerprints ARE unique, and the original forensic journals were correct in not publishing this drivel.
  2. The brave new world of artificial intelligence is fundamentally disproving previously sacred assumptions, and anyone who resists these assumptions is denying scientific knowledge and should go back to their caves.
  3. Well, let’s see what the study actually SAYS.

Until today, I hadn’t had a chance to read the study. But I wanted to do this, because a paragraph in the article that described the study got me thinking. I needed to see the study itself to confirm my suspicions.

“The AI was not using ‘minutiae,’ which are the branchings and endpoints in fingerprint ridges – the patterns used in traditional fingerprint comparison,” said Guo, who began the study as a first-year student at Columbia Engineering in 2021. “Instead, it was using something else, related to the angles and curvatures of the swirls and loops in the center of the fingerprint.” 

From https://www.newswise.com/articles/ai-discovers-that-not-every-fingerprint-is-unique

Hmm. Are you thinking what I am thinking?

What were you thinking?

I’ll preface this by saying that while I have worked with fingerprints for 29 years, I am nowhere near a forensic expert. I know enough to cause trouble.

But I know who the real forensic experts are, so I’m going to refer to a page on onin.com, the site created by Ed German. German, who is talented at explaining fingerprint concepts to lay people, created a page to explain “Level 1, 2 and 3 Details.” (It also explains ACE-V, for people interested in that term.)

Here are German’s quick explanations of Level 1, 2, and 3 detail. These are illustrated at the original page, but I’m just putting the textual definitions here.

  • “Level 1 includes the general ridge flow and pattern configuration.  Level 1 detail is not sufficient for individualization, but can be used for exclusion.  Level 1 detail may include information enabling orientation, core and delta location, and distinction of finger versus palm.” 
  • “Level 2 detail includes formations, defined as a ridge ending, bifurcation, dot, or combinations thereof.   The relationship of Level 2 detail enables individualization.” 
  • “Level 3 detail includes all dimensional attributes of a ridge, such as ridge path deviation, width, shape, pores, edge contour, incipient ridges, breaks, creases, scars and other permanent details.” 

We’re not going to get into Level 3 in this post. But if you look at German’s summary of Level 2, you’ll see that he is discussing the aforementioned MINUTIAE (which, according to German, “enables individualization”). And if you look at German’s summary of Level 1, he’s discussing RIDGE FLOW, or perhaps “the angles and curvatures of the swirls and loops in the center of the fingerprint” (which, according to German, “is not sufficient for individualization”).

Did Gabe Guo simply “discover” fingerprint patterns? On a separate onin.com page, common fingerprint patterns are cited (arch, loop, whorl). Is this the same thing that Guo (who possibly has never heard of loops and whorls in his life) is talking about?

From Antheus Technology page, from NIST’s Appendix B to the FpVTE 2003 test document. I remember that test very well.

I needed to read the original study to see what Guo actually said, and to determine if AI discovered something novel beyond what forensic scientists consider the information “in the center of the fingerprint.”

So let’s look at the study

I finally took the time to read the study, “Unveiling intra-person fingerprint similarity via deep contrastive learning,” as published in Science Advances on January 12. While there is a lot to read here, I’m going to skip to Guo et al’s description of the fingerprint comparison method used by AI. Central to this comparison is the concept of a “feature map.”

Figure 2A shows that all the feature maps exhibit a statistically significant ability to distinguish between pairs of distinct fingerprints from the same person and different people. However, some are clearly better than others. In general, the more fingerprint-like a feature map looks, the more strongly it shows the similarity. We highlight that the binarized images performed almost as well as the original images, meaning that the similarity is due mostly to inherent ridge patterns, rather than spurious characteristics (e.g., image brightness, image background noise, and pressure applied by the user when providing the sample). Furthermore, it is very interesting that ridge orientation maps perform almost as well as the binarized and original images—this suggests that most of the cross-finger similarity can actually be explained by ridge orientation.

From https://www.science.org/doi/10.1126/sciadv.adi0329.

(The implied reversal from the forensic order of things is interesting. Specifically, ridge orientation, which yields a bunch of rich data, is considered more authoritative than mere minutiae points, which are just teeny little dots that don’t look like a fingerprint. Forensic examiners consider the minutiae more authoritative than the ridge detail.)

Based upon the initial findings, Guo et al delved deeper. (Sorry, couldn’t help myself.) Specifically, they interrogated the feature maps.

We observe a trend in the filter visualizations going from the beginning to the end of the network: filters in earlier layers exhibit simpler ridge/minutia patterns, the middle layers show more complex multidirectional patterns, and filters in the last layer display high-level patterns that look much like fingerprints—this increasing complexity is expected of deep neural networks that process images. Furthermore, the ridge patterns in the filter visualizations are all generally the same shade of gray, meaning that we can rule out image brightness as a source of similarity. Overall, each of these visualizations resembles recognizable parts of fingerprint patterns (rather than random noise or background patterns), bolstering our confidence that the similarity learned by our deep models is due to genuine fingerprint patterns, and not spurious similarities.

From https://www.science.org/doi/10.1126/sciadv.adi0329.

So what’s the conclusion?

(W)e show above 99.99% confidence that fingerprints from different fingers of the same person share very strong similarities. 

From https://www.science.org/doi/10.1126/sciadv.adi0329.

And what are Guo et al’s derived ramifications? I’ll skip to the most eye-opening one, related to digital authentication.

In addition, our work can be useful in digital authentication scenarios. Using our fingerprint processing pipeline, a person can enroll into their device’s fingerprint scanner with one finger (e.g., left index) and unlock it with any other finger (e.g., right pinky). This increases convenience, and it is also useful in scenarios where the original finger a person enrolled with becomes temporarily or permanently unreadable (e.g., occluded by bandages or dirt, ridge patterns have been rubbed off due to traumatic event), as they can still access their device with their other fingers.

From https://www.science.org/doi/10.1126/sciadv.adi0329.

However, the researchers caution that (as any good researcher would say when angling for funds) more research is needed. Their biggest concern was the small sample size they used in their experiments (60,000 prints), coupled with the fact that the prints were full and not partial fingerprints.

What is unanswered?

So let’s assume that the study shows a strong similarity between the ridges of fingerprints from the same person. Is this enough to show:

  • that the prints from two fingers on the same person ARE THE SAME, and
  • that the prints from two fingers on the same person are more alike than a print from ANY OTHER PERSON?

Or to use a specific example, if we have Mike French’s fingers 2 (right index) and 7 (left index), are those demonstrably from the same person, while my own finger 2 is demonstrably NOT from Mike French?

And what happens if my finger 2 has the same ridge pattern as French’s finger 2, yet is different from French’s finger 7? Does that mean that my finger 2 and French’s finger 2 are from the same person?

If this happens, then the digital authentication example above wouldn’t work, because I could use my finger 2 to get access to French’s data.

This could get messy.

More research IS needed, and here’s what it should be

If you have an innovative idea for a way to build an automobile, is it best to never talk to an existing automobile expert at all?

Fair use. From https://interestingengineering.com/transportation/bizarre-concept-cars-you-never-even-knew-existed.

Same with fingerprints. Don’t just leave the study with the AI folks. Bring the forensic people on board.

And the doctors also.

Initiate a conversation between the people who found this new AI technique, the forensic people who have used similar techniques to classify prints as arches, loops, whorls, etc., and the medical people who understand how the ridges are formed in the womb in the first place.

By National Museum of Health and Medicine – http://nmhm.washingtondc.museum/exhibits/single_cell/imgs/14_Fetus_3_months.jpg, Public Domain, https://commons.wikimedia.org/w/index.php?curid=9998241

If you get all the involved parties in one room, then perhaps they can work together to decide whether the technique can truly be used to identify people.

I don’t expect that this discussion will settle once and for all whether every fingerprint is unique. At least not to the satisfaction of scientists.

But bringing the parties together is better than not listening to critical stakeholders at all.

By Lorelei7, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=3164780

You Can’t Make a Silk Purse Out of an AI-generated Sow’s Ear

By Rictor Norton & David Allen from London, United Kingdom – Show Pig, CC BY 2.0, https://commons.wikimedia.org/w/index.php?curid=43222404

I’m sure that you’ve heard the saying that “you can’t make a silk purse out of a sow’s ear.” Alternative phrases are “putting lipstick on a pig” or “polishing a turd.”

In other words, if something is crappy, you can’t completely transform it into something worthwhile.

Yet we persist on starting with crappy stuff anyway…such as surrendering our writing to generative AI and then trying to fix the resulting crap later.

Which is why I’ve said that a human should ALWAYS write the first draft.

The questionable job description

Mike Harris found a job post asking for a human copyeditor to rework AI-generated content. See the details here.

I’m sure that the unnamed company thought it was a great idea to have AI generate the content…until they saw what AI generated.

Rather than fix the source of the problem, the company has apparently elected to hire someone to rework the stuff.

A human should always write the first draft

Why not have a human write the stuff in the first place..as I recommended last June? Let me borrow what I said before…

I’m going to stick with the old fashioned method of writing the first draft myself. And I suggest that you do the same. Doing this lets me:

  • Satisfy my inflated ego. I’ve been writing for years and take pride in my ability to outline and compose a piece of text. I’ve created thousands upon thousands of pieces of content over my lifetime, so I feel I know what I’m doing.
  • Iterate on my work to make it better. Yes, your favorite generative AI tool can crank out a block of text in a minute. But when I’m using my own hands on a keyboard to write something, I can zoom up and down throughout the text, tweaking things, adding stuff, removing stuff, and sometimes copying everything to a brand new draft and hacking half of it away. It takes a lot longer, but in my view all of this iterative activity makes the first draft much better, which makes the final version even better still.
  • Control the tone of my writing. One current drawback of generative AI is that, unless properly prompted, it often delivers bland, boring text. Creating and iterating the text myself lets me dictate the tone of voice. Do I want to present the content as coming from a knowledgeable Sage? Does the text need the tone of a Revolutionary? I want to get that into the first draft, rather than having to rewrite the whole thing later to change it.

I made a couple of other points in that original LinkedIn article, but I’m…um…iterating. I predict that there’s a time when I WON’T be able to sleep on my text any more, and these days the “generated text” flag has been replaced by HUMAN detection of stuff that was obviously written by a bot.

And that’s more dangerous than any flag.

But if you insist on going the cheap route and outsourcing your writing to a bot…you get what you pay for.

If you want your text to be right the FIRST time…

Drive content results with Bredemarket Technology Firm Services.

Claimed AI-detected Similarity in Fingerprints From the Same Person: Are Forensic Examiners Truly “Doing It Wrong”?

I shared some fingerprint-related information on my LinkedIn feed and other places, and I thought I’d share it here.

Along with an update.

You’re doing it wrong

From https://www.newswise.com/articles/ai-discovers-that-not-every-fingerprint-is-unique.

Forensic examiners, YOU’RE DOING IT WRONG based on this bold claim:

“Columbia engineers have built a new AI that shatters a long-held belief in forensics–that fingerprints from different fingers of the same person are unique. It turns out they are similar, only we’ve been comparing fingerprints the wrong way!” (From Newswise)

Couple that claim with the initial rejection of the paper by multiple forensic journals because “it is well known that every fingerprint is unique” (apparently the reviewer never read the NAS report), and you have the makings of a sexy story.

Or do you?

And what is the paper’s basis for the claim that fingerprints from the same person are NOT unique?

““The AI was not using ‘minutiae,’ which are the branchings and endpoints in fingerprint ridges – the patterns used in traditional fingerprint comparison,” said Guo, who began the study as a first-year student at Columbia Engineering in 2021. “Instead, it was using something else, related to the angles and curvatures of the swirls and loops in the center of the fingerprint.”” (From Newswise)

Perhaps there are similarities in the patterns of the fingers at the center of a print, but that doesn’t negate the uniqueness of the bifurcations and ridge ending locations throughout the print. Guo’s method uses less of the distal fingerprint than traditional minutiae analysis.

But maybe there are forensic applications for this alternate print comparison technique, at least as an investigative lead. (Let me repeat that again: “investigative lead.”) Courtroom use will be limited because there is no AI equivalent to explain to the court how the comparison was made, and if any other expert AI algorithm would yield the same results.

Thoughts?

https://www.newswise.com/articles/ai-discovers-that-not-every-fingerprint-is-unique

The update

As I said, I shared the piece above to several places, including one frequented by forensic experts. One commenter in a private area offered the following observation, in part:

What was the validation process? Did they have a qualified latent print examiner confirm their data?

From a private source.

Before you dismiss the comment as reflecting a stick-in-the-mud forensic old fogey who does not recognize the great wisdom of our AI overlords, remember (as I noted above) that forensic experts are required to testify in court about things like this. If artificial intelligence is claimed to identify relationships between fingers from the same person, you’d better make really sure that this is true before someone is put to death.

I hate to repeat the phrase used by scientific study authors in search of more funding, but…

…more research is needed.

Working With Familiar Faces

Often consultants work with someone whom they have never met before.

Sometimes they get to work with friends they have known from previous experiences, which can be a good thing.

From “We Are Your Friends.” https://vimeo.com/11277708.

First example: A couple of years ago, when consulting for a large client, I worked on a proposal with one of the client’s partners, and one of the employees in the partner organization happened to be a former coworker from MorphoTrak.

Second example: This morning I’m meeting with Gene Volfe, a former coworker at Incode Technologies (we started at Incode on the same day). We’re working on a project together that requires Gene’s demand generation skills and my content skills…which we will be employing for the benefit of another former MorphoTrak coworker.

Third example: Speaking of Incode, two of my former coworkers are reuniting at a different company. As a sign that these two know each other well, one made a point of saying to the other, “Go Bills!”

And yes, Gene, I remember how you like Google Docs…

When Follower Counts Matter

I see social posts in which the authors thank their followers for getting them to a certain follower count, and I receive Instagram messages promising me that for just a little money I can get tens of thousands of followers.

I definitely ignore the latter messages, and personally I ignore the former messages also.

Because follower counts don’t matter.

Just because Bredemarket has X followers doesn’t necessarily mean that Bredemarket will make lots of money. I could use viral tactics to attract countless followers that would never, ever purchase Bredemarket’s marketing and writing services.

In fact, I could live just fine with 25 followers…provided that they’re the RIGHT followers.

But while this is normally true, I’ve run into a couple of instances in which follower counts DO matter. Because you need a certain heft to get the large companies to pay attention to you.

My invisible WhatsApp channel

A little over a month ago I started a WhatsApp channel devoted to identity, biometrics, ID documents and geolocation. Why?

I began mulling over whether I should create my own WhatsApp channel, but initially decided against it….

I’d just follow the existing WhatsApp channels on identity, biometrics, and related topics.

But I couldn’t find any.

From https://bredemarket.com/2023/11/29/announcing-a-whatsapp-channel-for-identity-biometrics-id-documents-and-geolocation/.

So I started my own to fill the void, then waited for similarly interested WhatsApp users to find my channel via search.

But there was a catch.

Although it isn’t explicitly documented anywhere, it appears that using the WhatsApp channel search only returns channels that already have thousands of subscribers. When I searched for a WhatsApp channel for “identity,” WhatsApp returned nothing.

WhatsApp channel search for “identity.”

As a result, I found myself promoting my WhatsApp channel everywhere EXCEPT WhatsApp.

Including this blog post. If you want to subscribe to my WhatsApp channel “Identity, Biometrics, ID Documents, and Geolocation,” click on the link https://www.whatsapp.com/channel/0029VaARoeEKbYMQE9OVDG3a.

Click the link https://www.whatsapp.com/channel/0029VaARoeEKbYMQE9OVDG3a to view the channel.

My non-linkable YouTube channel

I also have a YouTube channel, and you CAN find that. But it also suffers from a lack of subscribers.

On Monday I received an onimous-sounding email from YouTube with the title “Your channel has lost access to advanced features.”

The opening paragraph read as follows:

To help keep our community safe, we limit some of our more powerful features to channels who have built and maintained a positive channel history or who have provided verification.

Ah, verification. I vaguely remember having to provide Alphabet with my ID a few months ago.

The message continued:

As of now, your channel doesn’t have sufficient channel history. It has lost access to advanced features. This may have happened because your channel did not follow our Community Guidelines.

While I initially panicked when I read that last sentence, I then un-panicked when I realized that this may NOT have happened because of a Community Guidelines violation. The more likely culprit was an insufficient channel history.

Your channel history data is used to determine whether your content and activity has consistently followed YouTube’s Community Guidelines.

Your channel history is a record of your:

Channel activity (like video uploads, live streams, and audience engagement.)

Personal data related to your Google Account.

When and how the account was created.

How often it’s used.

Your method of connecting to Google services.

Most active channels already have sufficient channel history to unlock advanced features without any further action required. 

From https://support.google.com/youtube/answer/9891124#channelhistory.

Frankly, my YouTube channel doesn’t have a ton of audience engagement. Now I could just start uploading a whole bunch of videos…but then I risk violating the Community Guidelines by getting a “spamming” accusation.

As it turns out, there’s only one “advanced feature” that I really miss: the ability to “Add external links to your video descriptions.” And I’m trying to tone down my use of external links because Alphabet (on YouTube) and Meta (on Instagram) discourage their use anyway.

But for now the previously-added external links to videos such as this one are now disabled.

From https://www.youtube.com/watch?v=oIB9SPI-yiI. The link at the bottom of the description is non-clickable.

Perhaps if I post long-form videos more frequently and get thousands of subscribers, I will get enough “audience engagement” to restore the advanced features.

So if you want to increase my YouTube follower count, go to https://www.youtube.com/@johnbredehoftatbredemarket2225 and click the Subscribe button.

So let’s get followers

But the question remains: how do I get thousands of people to subscribe to my WhatsApp channel and my YouTube channel?

Perhaps I can adapt a really cool TikTok challenge to WhatsApp and YouTube.

You can create the exciting Savage Challenge on TikTok and ask your audience to participate in it. In this challenge, people will have to learn and follow the choreography of Megan Thee Stallions’ highly loved song, “Savage.”

From https://www.engagebay.com/blog/tiktok-challenges/

I’m not familiar with that particular song, so I’d better check it out.

Well…

I’m not sure if this fits into my “sage” persona.

And if I go to the local car wash with a baseball bat and start knocking out car windows, I may end up in jail. And that usually does NOT increase the follower count. Because as Johnny Somali persumably found out in Japan, you can’t film videos when you’re in jail.

Five Reasons Why 17X Certified Resume Writer Pitches Fail

Are you a 17X Certified Resume Writer?

Do you seek your prospects by searching for LinkedIn profiles with green #OpenToWork banners?

From https://www.linkedin.com/in/jbredehoft/.

Do you find that your prospects resist your pitches?

From https://www.linkedin.com/posts/jbredehoft_i-have-a-question-for-people-who-need-to-activity-7150154185278144512-tPMt/.

Here are five reasons why your pitches may not be resonating.

  1. You don’t say WHY you exist.
  2. You don’t say HOW you’ll make me a lot of money.
  3. You don’t say WHAT you will emphasize in my resume…because you never read my profile.
  4. You’re a “me too” resume writer.
  5. You say nothing about product marketing, identity, biometrics, or technology.

If you’re a 17x Certified Resume Writer with generic failing pitches, Bredemarket can’t fix your issues, but maybe someone else can.

The five reasons

Reason One: You don’t say WHY you exist

Let’s face it. 99% of the 17X Certified Resume Writer pitches read “You have an #OpenToWork banner, and I write resumes, so you should buy my services.”

This tells me NOTHING about you, or why you do what you do.

  • Was there a childhood experience that propelled you into the resume writing field?
  • Or did a simple tweak to your own resume propel you forward?
  • Or are you just doing this because it beats delivery driving?

Who are you? Why should I care?

Maybe you should do something like this. For example, here’s why my consulting firm Bredemarket exists:

I am John E. Bredehoft, and I have enjoyed writing for a while now….I guess I’m a “you can pry my keyboard out of my cold dead hands” type.

From https://bredemarket.com/who-i-am/.

Reason Two: You don’t say HOW you’ll make me a lot of money

Remember that I don’t care about your service. I care about how I’m going to get a company to hire me and pay me billions of dollars every year. (More or less.)

I’ve got the brains, you’ve got the looks, let’s make lots of money. By US Federal Reserve – Public Domain, https://commons.wikimedia.org/w/index.php?curid=70290373.

So, how will you do this? Do you have a process that results in stellar resumes? Or do you just type stuff at random and hope it comes out OK?

For example, here’s Bredemarket’s process. Did you see that my first two reasons in this particular post were “Why” and “How”? Now you know where I got those terms. And guess what comes next.

Reason Three: You don’t say WHAT you will emphasize in my resume…because you never read my profile

Be honest. When I see these pitches, I draw one of two conclusions:

  1. You saw my #OpenToWork banner and immediately fired off a generic pitch without looking at my LinkedIn profile, in which case I have no reason to work with you.
  2. You DID read my LinkedIn profile, but you’re such a poor communicator that you didn’t bother to say what you saw in my LinkedIn profile, in which case I have no reason to work with you.

Reason Four: You’re a “me too” resume writer

You may not realize this, but you are not the only 17X Certified Resume Writer out there. At the same time that you are sending your “You have an #OpenToWork banner, and I write resumes, so you should buy my services” pitch, other people are sending THEIR “You have an #OpenToWork banner, and I write resumes, so you should buy my services” pitch.

Your pitch doesn’t say why I should pick YOU. Or why you are great and why everyone else sucks. You all look the same to me.

Dionne Quintuplets – School Days, painting by Andrew Loomis, 1938. By Andrew Loomis – https://www.flickr.com/photos/lac-bac/7797309642/in/album-72157631099965608/, CC BY 2.0, https://commons.wikimedia.org/w/index.php?curid=56000992

As I look at your undifferentiated “me too” pitch and all of their undifferentiated “me too” pitches, none of which cover the “why,” “how,” or “what” of your 17X Certified Resume Writer services. When everyone says “me too” without differentiation, no one stands out.

By Ben Schumin – Own work, CC BY-SA 2.5, https://commons.wikimedia.org/w/index.php?curid=1123246

As I said earlier: “If the 17x certified resume writers are unable to convey THEIR OWN unique value, why should I believe that they can convey MINE?”

Reason Five: You say nothing about product marketing, identity, biometrics, or technology

I end up shaking my head at the pitches that use the following introductory question to send me through their sequence:

I’m curious about which specific role you intend to apply for?

(I had to edit that pitch quote because the original version I received had a space between “for” and the question mark. I am in the United States. Punctuate accordingly.)

If you had actually read my profile (see reason 3 above), you’d know that I self-describe (at least this week, pending future edits) as a “Senior Product Marketing Manager experienced in identity and technology.” You’d also know that I talk about #identity, #biometrics, #facialrecognition, and #productmarketingmanager. You’d also know that my advertised top skills are Product Marketing, Content Marketing, Artificial Intelligence (AI), and Competitive Intelligence.

From Sandeep Kumar, A. Sony, Rahul Hooda, Yashpal Singh, in Journal of Advances and Scholarly Researches in Allied Education | Multidisciplinary Academic Research, “Multimodal Biometric Authentication System for Automatic Certificate Generation.”

That’s a wealth of information right there, even without looking at my work history, my skills, or my posts.

Too bad you didn’t use it in your pitch.

Time to fix it

I’ll grant that an introductory pitch doesn’t have a lot of real estate, but you should be able to rework your pitch to accommodate all five gaps in your current marketing.

Unfortunately, the word count for your pitch will be well below 400 words, the minimum word count that Bredemarket supports.

But you should be able to find someone.

Just avoid the people with the generic pitch.

From https://www.pinterest.com/pin/121737996155096419/.

SOMEONE is Using my 29 Years of Identity/Biometrics Experience

On behalf of a recruiter I am re-examining my consulting experience in the identity/biometric industry, and came to this realization:

If Bredemarket hasn’t consulted for you, it’s a guarantee that Bredemarket has applied its 29 years of identity/biometric experience consulting for your competitors.

Do you want your competitors to realize all the benefits?

I didn’t think so.

Drive content results with Bredemarket Identity Firm Services.