Marketers Must Take Stock of Their Data-Driven Power Now

With the 2020 elections already underway, social media marketing is in the spotlight. Although I am not sure if the spotlight was ever really off of its data-driven science since the 2016 election. Although all of the major social networking platforms have been dragged in front of congress to discuss how they use data, it was the relationship between Facebook and Cambridge Analytica that drew the most media attention and become the poster child.

With the 2020 elections already underway, social media marketing is in the spotlight. Although I am not sure if the spotlight was ever really off of its data-driven science since the 2016 election.

Although all of the major social networking platforms have been dragged in front of congress to discuss how they use data, it was the relationship between Facebook and Cambridge Analytica that drew the most media attention and become the poster child.

What data-driven marketers need to recognize is that what happened with Facebook and Cambridge Analytica was not some off-the-books, sneaky misuse of social data. Rather, it was executed very much in line with the broader vision of social media marketing. That has implications for how we use social media as part of our digital marketing mix.

Why Data-Driven Marketers Must Take Stock Now

What makes social media a powerful platform for marketers is that it not only targets individuals based on demographics, but it could also targets based on their location, personality and current context.

Considering all of the conscious and unconscious information users can share on social platforms, there is a powerful amount of information algorithms can mine to generate marketing content and messages most likely to resonate with users. Not only can social media know where you are and what you like, but also your closest friends and your emotional state on any given day. It is even likely that social media algorithms have a better understanding of your underlying emotions and motivations than you do. To anyone who has spent time micro-targeting, this is not a surprise. Given enough data, a shockingly perceptive algorithm can be developed. This is why social media had mile-high stock valuations even when platforms were still hemorrhaging cash.

Let’s face it; marketing has always included an element of manipulation. The function of consumer insights and research is designed to provide marketers levers for manipulation. With some exceptions, we have been able to sleep at night knowing that the consumer stood a chance or that we were also offering a real benefit, so some manipulation was just part of it. When we started using rich data with algorithms to develop more targeted models, many of us saw this as the ultimate example of customer empathy. This was going to empower marketers to become highly relevant to their consumers.

Those who were not on board were behind the times. (To confess, I used to view most cautionary voices as laggards or technophobes. Some were, some weren’t, but they were also right to worry.)

Today, we need to take stock of how that empathy is used. With great empathy comes the power of even greater manipulation. Despite all of the data policies out there, we are not addressing the real question: How much manipulation is too much?

Is it fair to push an antacid ad at someone who posts about a visit to the county fair and winning the pie-eating contest? Seems “big brother-ish,” but benign?

How about pushing anti-anxiety medication ads to a college student going through a breakup during finals week?

While this sounds horrible, we technically can.

Don’t Do It Just Because You Can

How companies manage and leverage consumer data is becoming part of the company’s ethical standards, but we need to extend beyond data privacy to data use.

Just like use of child labor, environmental footprints and other ethical standards, standards on the use of consumer data will be a critical way that companies define their brands and the role they wish to play.

The ‘Algorithmification‘ of Everything

If I had asked any of my schoolmates what an “algorithm” was, their eyes would have glazed over and they would probably have asked me what I had been smoking. Fast-forward a few decades and we’ve got the algorithmification of everything, including marketing.

If I had asked any of my schoolmates what an “algorithm” was, their eyes would have glazed over and they would probably have asked me what I had been smoking. Fast-forward a few decades and we’ve got the algorithmification of everything, including marketing.

Those glazed looks would’ve happened a long time ago, long before Facebook was a glimmer in Mark Zuckerberg’s eye and he had started to bring together the more than 2 billion people who log in at least once a month. That Facebook population is now what Evan Osnos of the New Yorker says, were it a country; “ … would have the largest population on Earth … [and] as many adherents as Christianity.” When they log in, they are shaking hands with unnumbered algorithms and putting into those invisible fingers their faith and their data to be parsed, analyzed and manipulated, and hopefully not stolen.

What is an algorithm? Programmers like to say it is a word used by them when they don’t want to bother explaining what they do.

And because algorithms have become so ubiquitous, we seldom give them a thought — except when our IT colleagues start telling us why making any small change in our marketing program will take weeks or months and cost a bundle, or until something goes badly wrong as Facebook and others have discovered about their hacked data.

Our legislators, not usually well-versed on technology matters, have now started making a lot of noise about regulations: They are closing the server door after the data has bolted — an unlikely way to solve the essential problems.

Automation has always been the Holy Grail for marketers; not surprising when the ability, speed and relatively low cost of using artificial intelligence (AI) to number-crunch and manage segmentation of media and analysis of data gets better and better every year. eMarketer reports that: “About four in 10 of the worldwide advertisers surveyed by MediaMath and Econsultancy said they use AI for media spend optimization. This is another application of AI that is increasing among marketers as their demand-side platforms add AI features to increase the probability that a given programmatic bid will win its auction.”

Where is it headed? No one knows for sure. It’s all in the hands of the algorithms and they appear to be multiplying like rabbits. If you revere Darwin, as I do, you’ll expect them to get better and better. But before you totally buy into that, you would do well to read Melanie Mitchell’s thoughtful New York Times article “Artificial Intelligence Hits the Barrier of Meaning.”

There are more and more times when we applaud the use of the algorithms and can see that if properly created, they offer many benefits for almost every area of our marketing practice, as well as other areas of our lives. We really don’t have to panic (yet) about the machines and their algorithms taking over. As Neil Hughes wrote here last month; “The reality is that machines learn from systems and processes that are programmed by humans, so our destiny is still very much in our own hands.”

Machines screw up just like we do; and all the more so, because they are doing just what we told them to do.

All this machine thinking doesn’t come without dangerous side effects. Sometimes, when we try to communicate with inflexible AI systems supposedly designed to simplify and ease customer interactions, the “I” in “AI” becomes an “S,” replacing “A-Intelligence” with “A-stupidity.”

If, as defined, “an algorithm is a procedure or formula for solving a problem, based on conducting a sequence of specified actions,” we can only optimistically hope that the specified actions will take into account individual customer differences and make allowances for them. The moments when they don’t are when we start screaming and swearing; especially if we are on the customer end of the transactions.

As The New York Times wrote in a recent article: “The truth is that nobody knows what algorithmification of the human experience will bring.”

“It’s telling that companies like Facebook are only beginning to understand, much less manage, any harm caused by their decision to divert an ever-growing share of human social relations through algorithms. Whether they set out to or not, these companies are conducting what is arguably the largest social re-engineering experiment in human history, and no one has the slightest clue what the consequences are.”

However important algorithmification may seem to us, our marketing efforts and our use of AI and its algorithms are not very significant in the greater scheme of things outside of our limited business perspective. But don’t dismiss their growing impact on every facet of our future lives. As data guru Stephen H. Yu opined in his recent piece “Replacing Unskilled Data Marketers With AI”:

“In the future, people who can wield machines will be in secure places — whether they are coders or not — while new breeds of logically illiterate people will be replaced by the machines, one-by-one.”

You had better start to develop a meaningful relationship with your algorithms — while there is still time.

What the DMV Taught Me About Brand Trust in the Age of Algorithms

After I shifted my residency from Pennsylvania to Virginia, I put off for way too long the job of going to the DMV to change my driver’s license. When I finally went recently, it was just as awful an experience as I expected. While I did lose years off my life, I also came away with new insights about customer experience and brand trust in the age of the algorithm.

building trustAfter I shifted my residency from Pennsylvania to Virginia, I put off for way too long the job of going to the DMV to change my driver’s license. When I finally went recently, it was just as awful an experience as I expected. While I did lose years off my life, I also came away with new insights about customer experience and brand trust in the age of the algorithm.

Let me set the stage. After explaining my needs (license, registration) to a greeter, I was given a ticket with the the number D72. I then went to sit among 100 or so lost souls watching a ticker go by: A31, T76, F17, H125, B7, A32 C38 … And I watched. And watched. After about an hour it dawned on me that I had not seen one “D” number go by in all that time.

I wandered around seeking an explanation for this strange D-free streak. I saw a poster that said something like, “We have a numbering system that prioritizes the various services with an employee with the right level of experience and training. We find that this is most effective process.”

So in other words, “We have a sort of secret system, and will not really explain it to you, but trust us, it works (for us).”

Rather than provide comfort, this bit of bureaucratic prose only wound me up further: What does my “D” ticket say about me? Where do I stack in the pecking order? What trade-offs are they making that are invisible to me, and that cost me precious time? Should I have gamed the system by doing things one at a time? Can I swipe my neighbor’s faster-moving C ticket? (He’s sleeping on shoulder, so really wouldn’t miss it.)

My conversation with the greeter didn’t help matters. She explained that, yes, D tickets were really slow — harder to deal with. Plus, 11-3 was the lunch hour, and therefore things get really bogged down at that time. I opined that 11-3 was more accurately a lunch four-hours, not a lunch hour, representing nearly half the day. Her silent, reptilian stare chilled my spine and sent me back to my seat.

At four hours and twelve minutes, I gave up and handed the win to the State of Virginia and went home to drink heavily.

This is where the lesson for marketers comes started to dawn on me.

None of us would ever seek to recreate such an experience. But in the age of the algorithm, analytic optimization and the coming era of AI, we run the risk of inadvertently creating similarly mysterious and unsettling experiences — and thereby undermining brand trust.

Top 5 Search Ranking Factors and How to Improve Them

Cracking search engine algorithms is both the holy grail and the windmill chase of search engine optimization. These algorithms are fiercely guarded secrets that constantly evolve. Just when absolute clarity seems within reach, the search for answers begins anew. That said, we’re far from clueless about how these algorithms work.

Cracking search engine ranking algorithms is both the holy grail and the windmill chase of search engine optimization. If the algorithms behind Google, Bing and other search providers were revealed, then optimizing any website for a top page ranking would be easy. But these algorithms are fiercely guarded secrets that constantly evolve. Just when absolute clarity seems within reach, the search for answers begins anew.

That said, we’re far from clueless about how these algorithms work. In 2015, the marketing company Moz conducted a survey to find the most important factors in search engine rankings. More than 150 search marketers contributed, offering opinions on more than 90 possible ranking factors. Moz also partnered with other data companies to examine correlations between websites and webpages with higher search positions.

The survey’s findings don’t tell us exactly how search engines work, but they definitely shed light on key elements of SEO. Here we’ll review the survey’s top five search ranking factors and how you can improve these factors on your website.

1. Domain-Level Link Features

Domain-level link features encompass the quantity and quality of links to your website that help to establish its authority in your field of expertise. The more inbound links you have from other quality sources, the more your site is viewed as a trusted authority that’s worthy of a higher page rank.

Building a network of links to your website has always been a critical element of SEO. It’s not difficult, but it takes time. Start by asking customers and business partners to link to your site from their websites, blogs and social media pages. You can also start a blog yourself; eventually, your interesting and helpful content is likely to be shared. In addition to registering your site with Yelp and other business directories, you can also leave comments on relevant forums or do something special to get noticed by the local media. All of these things can help you earn links that can boost how your website is perceived by search engines.

2. Page-Level Link Features

Page-level link features are the same as domain-level link features, only this references the volume and quality of links that point to specific pages of your website. You can improve this factor just as you would with domain-level link features, by slowly building up a network of inbound links from other reputable sites.

One page-specific link feature to keep in mind is the phrase used in the hyperlinks, also known as anchor text. When possible, hyperlink a few important keywords on your webpage to relevant pages deeper within your site, which helps to establish authority for those keywords. Don’t hyperlink more than a few keywords, though, because that’s a red flag for Google that you’re gaming the algorithms and it could result in a penalty.

3. Page-Level Keyword & Content-Based Features

From the search engine algorithm’s perspective, the nuts and bolts of your content is slightly more important than the content itself. Yes, you want each of your webpages to be unique and compelling, but you also want each page to be properly optimized. The most important keywords for each webpage should echo through your content, headers, images and meta tags. Otherwise, the search algorithms may deem your pages as poor sources of information.

Can a Machine Think for You?

I expect most of you are going to go with “No.” You might balk at the entire idea. But I had a conversation last week that pointed out that, if they’re working, isn’t that exactly what you’re counting on your marketing automation tools to do?

“As soon as we started thinking for you, it really became our civilization.” — Agent Smith, “The Matrix,” 1999, Warner Bros.
“As soon as we started thinking for you, it really became our civilization.”
— Agent Smith, “The Matrix,” 1999 Warner Bros.
People don’t make memes of this quote. For me, one of the most memorable lines of the movie.

Can a machine think for you?

I expect most of you are going to go with “No.” You might balk at the entire idea. But I had a conversation with Adobe’s Chris Wareham, senior director of product management for Adobe Analytics, last week at Adobe Summit where it became clear that, if they’re working, isn’t that exactly what you’re counting on your marketing tools to do?

“The state of the industry with data is to point a lot of really, really smart postgraduates with math at the problem and hope for good answers,” said Wareham. “And that’s not scaling.”

The bottleneck is that not everyone can be a data scientist, not everyone can do that kind of thinking, or has the training to do it themselves. Not everyone works effectively that way.

However, marketing departments today can’t afford to wait a week for the DBA on their IT teams to turn those reports out. That’s where Adobe’s virtual analyst comes in. According to Wareham, “the gap we’re filling in the industry is the need for people to be data-driven even in very simple interactions that they have.”

Wareham compares it to the revolution in we’ve seen in website analytics. Once (probably before many of you remember) finding out how much traffic was coming to your website involved getting daily or weekly reports from a guy called “The Webmaster.” Pretty quickly tools emerged to automate those reports, then deliver the numbers in real time. Google Analytics provides all that information, and a lot more we never dreamed of, in real-time.

“They were very complex things that made a very complex job really simple,” says Wareham. “So we’re starting to apply those same types of capabilities to a customer analytics problem set. Broadening the data set, leveraging the machine learning to automate a lot of those analytics processes, so a less sophisticated person can get a lot more leverage out of the data.”

And that’s where the robots come in. (Well, “virtual assistant,” but that’s really just one servo-enabled titanium chassis from the same thing, right?)

“Our usage of machine learning, our usage of things like the automated analyst, is really about applying machine learning to fix a problem,” says Wareham. To actually replace a data scientist takes more than reporting stats or tracking goals. The virtual assistant needs to be able to recognize the trends, opportunities and personas that a data scientist would, and that means breaking the rules. … Or at least the business rules many databases use to automate marketing

“Wherever we see rules, that smells like smoke to us,” says Wareham. “We want to get rid of the rules, and make everything that is currently rules-based algorithmically based, so it can learn, and it helps our customers get leverage out of the data.”

Robots breaking rules? Asimov would not approve, but it might be exactly the thing marketers need.

Whether this sounds joyous or terrifying probably depends on if you’re picturing Johnny Five or The Terminator.

Johnny Five, "Short Circuit," 1996 TriStar Pictures.
Johnny Five, “Short Circuit,” 1996 TriStar Pictures.
"The Terminator," 1984, Orion Pictures.
“The Terminator,” 1984, Orion Pictures.

Either way, it’s an interesting time to be a marketer.

Myths and Misconceptions: The Real Truth About Content Marketing and the Search Engines: Part II

Lately, I’ve been hearing a lot of people saying things such as: “Google doesn’t like content or article marketing since they changed their algorithms” and “article directories are not useful for search engine marketing and link-building efforts anymore.” I like to remind people of a few fundamental rules of online marketing, specifically involving content, that virtually never changes and is extremely helpful to know (and do!) … Previously, I provided the first three rules, here are the last three:

[Editor’s note: This is Part Two of a two-part series.]

Lately, I’ve been hearing a lot of people saying things such as: “Google doesn’t like content or article marketing since they changed their algorithms” and “article directories are not useful for search engine marketing and link-building efforts anymore.”

I like to remind people of a few fundamental rules of online marketing, specifically involving content, that virtually never changes and is extremely helpful to know (and do!) … Previously, I provided the first three rules, here are the last three:

4. Targeted Link-Building. Links, whether it’s a one way back link or a reciprocal back link, are still links. Quality links help SEO, and that is indisputable. But, again, there’s some ground rules to do it right within best practices … and do it wrong. Links should be quality links, and by that I mean on sites that have relevant content and a synergistic audience to your own. It should also be a site with a good traffic rank. I prefer to do linkbuilding manually and do it strategically. I research sites that are synergistic in all ways to the site I’m working with (albeit one-way or reciprocal links). Doing it manually allows more targeted selection and control over where you want your links to go. Manual selection and distribution can also lead to other opportunities down the road with those sites you’re building relationships with, including cross-marketing or editorial efforts such as editorial contributions, revenue shares and more. In my view, this approach is both linkbuilding and relationship building.

5. Location, Location, Location. Where you link to is important. When doing SONAR or content marketing, I always tell clients to deep link—that is, not just link to their home page—which, to me, doesn’t make any sense anyway, as there’s too many distractions on a home page. Readers need a simple, direct call to action. Keep them focused. It’s always smarter to link to your source article, which should be on one of your subpages, such as the newsletter archive page or press release page. Now you have a connection. The article/content excerpt you pushed out is appearing in the SERPs (search engine result pages) and its redirect links to the full version on your archive or press page. You’ve satisfied the searcher’s expectations by not doing a “bait and switch.” There’s relevance and continuity. And to help monetize that traffic, that newsletter archive or press Web page (which you’re driving the traffic to), the background should contain fixed elements to “harness” the traffic it will be getting for list growth and cross-selling, such as fixed lead gen boxes, text ads, banner ads, editorial notes and more. These elements should blend with your overall format, not being to obnoxious, but being easily seen.

6. Catalyst Content. It’s always important to make sure you publish the content on your website first … I call this your “catalyst content.” This is the driving source which all other inbound marketing will occur and be focused around. Your website articles should be dated and be formatted similar to a news feed or blog. Also, posting timely press releases will work favorably, as they will be viewed by Google and human readers as the latest news (again favorable to Google’s latest “freshness” update). At the same time, send your content out via email (i.e. ezine) to your in-house list before external marketing channels see it. This helps from an SEO standpoint, but also helps with credibility and bonding with your subscribers and regular website visitors, as they should get your information before the masses.

There you go. My best practices for marketing with content. I don’t practice nor condone “black hat” marketing tactics. I’ve always been lucky enough to work for top publishers and clients who put out great, original content.

It really does all boil down to the quality of the content when you talk about any form of article and search engine marketing. Content is king, and when you have strong editorial, along with being a “creatively strategic” thinker, you don’t need to engage in “black hat” or questionable SEO/SEM.

Algorithms are always changing. It’s good to be aware of the latest news, trends and techniques, but also not to put your your eggs in one basket and build your entire online marketing strategy based on the “current” algorithms. Using solid content, analyzing your website’s visitor and usage patterns and keeping general best practices in mind are staple components that will always play an important role in content marketing.