Posts by jcuene

Digital marketing & innovation leader. Founder of Fahren. Previously at GoKart Labs, General Mills, Ameriprise. MPLS. Husband to Andrea, father to 2. Lover of bikes, food, beer and rock'n'roll.

Writing is Our Super Power

We humans will soon be drowning in text and images, if we’re not already. Your TikTok, podcasts,  email inboxes and favorite websites will be overrun with “content” that will be synthetic, manufactured out of thin air by code.  

I’m generally a technology optimist, but I’m feeling a little pessimistic as I watch the explosion of AI writing and writing tools. Just like most of us have lost basic arithmetic skills, the ability to do math in our heads, because we rely on calculators, we’re at risk of losing the ability to come up with unique ideas and thoughts.

What do we lose when we turn over the writing to machines? More importantly, what are the benefits of creating for the creator? What’s in it for she who takes the time contemplate how to put one word in front of the other in such a way that others will be able to understand, to be persuaded? 

We write because we can. But, we should be conscious of what the writing itself does for us. It helps us remember. Recalling and committing things to words helps lock them in, at least temporarily into the actual neuron network in our brains. 

Writing forces us to clarify what we even know and believe. Translating the buzz and jumble of ideas, images and words in our head into a relatively clear string of letters, phonemes, words, sentences and paragraphs literally forces order and logic onto our increasingly scattered brain (speaking for a friend). 

Writing gives us a chance to persuade. As we commit the ideas to words, we can choose what arguments we make, how we structure them, and how we support them.

Writing gives us a chance to get good at a craft. At our best, we might even be sort of poetic. There are a few among us that might even leave behind actual art via their words. 

AI, however we define that, will result in an amazing toolbox for humans, a mix of apps, devices, agents and oracles that will make our lives easier and better in unimaginable ways. Within the next 5 years, everyone will have a device on their wrist that can conjure up enthralling entertainment algorithmically, can autogenerate a movie for your pleasure, can make a recommendation so you don’t have to think about it. 

As the algorithms get better, as they become more pervasive our natural tendency will be to lean on them even more, to incorporate them into our lives because its just going to be easier to let the machines do it.

Writing is something any literate person can do, but increasingly fewer of us will. It’s a super power for us humans, it’s our way to organize the world, at least in our own heads and on our own pages. If we want to compete and thrive in a world that’s saturated with synthetic, sort-of-good “content”, we have to keep thinking for ourselves, creating out thin air our own ideas and beliefs, and writing is our way to do that. 

Is it Time for Warning Labels on our Apps?

I was talking with a good friend about TikTok last week, discussing the  incredible creativity being unleashed. It’s an expression machine, and the fast growth of the tools and templates means anyone can pursue their creative curiousity. But, of course, the result is oceans of distractions at our fingertips, billions of creators dying for us to watch for more than 1 second, a direct assault on our id and attention. 

Semi-serious thought: Should we take more seriously the concept of labeling apps that are designed to keep you addicted? TikTok is not the the first app that should come with a warning label, like those aussie cigarette packs: “This might damage you.”

I’ve used TikTok enough to know it’s dangerous to those of us that are easily distracted, who are hungry enough for the serotonin hit that we’ll lock into the app so the juices flow at a higher rate. Based on where the algorithm took my feed after seeding it with “Trout fishing videos” and “Japanese Joinery” I didn’t want to see where it would have ended up. Hint: TikTok knows that trout fisherman and woodworkers are probably men, and after fishing and woodwork, what do a lot of men like? I deleted it before the algorithm figured me out.

But, I did download Artifact, the news app from Kevin Systrom (of Instagram). Its clear they’re trying to build a dynamic news app. I bet the pitch went like this: What if TikTok and Apple News had a baby? I’m a voracious news consumer, probably too much. So, I can’t imagine this is going to end well and I’ll have to delete it at some point because I’m compulsively tap tap tapping.

I feel like my phone screen has become downtown tokyo at midnight, and I’m trying to get out of town.

Warning labels could only help, even as a minimal reminder of what we’re doing to ourselves everytime we look at the screen. Labeling won’t solve the problems presented by the software and algorithms we’re now dealing with. But, the reminder (if we can see it) might be seen and it might start spark some reconsideration

Meta’s ad spend glitch and the risks of marketing automation | Mobile Dev Memo by Eric Seufert

I’m actually surprised we don’t hear about more of these incidents. I’m assuming they happen all the time, but the effect is either so small most advertisers don’t see it or they are fixed so fast advertisers never recognize them. It’s getting easier and easier to put it all on autopilot, but the incentives actually work against advertisers.

the Meta irregularity from this weekend highlights a risk in wholly automated advertising creative production: that the incentive structure for ad platforms is simply too misaligned with the best interests of advertisers to empower those platforms to manage the digital advertising process end-to-end.

Source: Meta’s ad spend glitch and the risks of marketing automation | Mobile Dev Memo by Eric Seufert

California and Reno: Goals and Objectives

I’m working with a relatively new and inexperienced marketing team as an interim leader. I love these roles because they enable me to be in “teacher” mode. While the team probably thinks about me as “Ok Xer”, there is a real hunger to build new skills. This team is smart, good and active listeners, works well with each other and has a strong desire to drive results. They just need a tiny bit of direction and some support. Culturally, we’ve worked to set the conditions where they can ask questions they’d be afraid to ask their old boss, the CEO.

In a planning meeting, we were talking about the marketing funnel and some choices they were wrestling with. After a lot of discussions, it turned out they didn’t have any real objectives, but they did have a goal. The whole company was aligned around the specific goal, which was good news. The bad news was, the team hadn’t translated the goal into objectives and strategies. And, the other bad news was they were using the phrases goal, objectives and strategies interchangeably.

We will be dedicating a little bit of time in an upcoming meeting to building their management system. We’re going start with the basics: Terminology. We want to make sure we’re all – literally – speaking the same language. We’re going to focus on the difference between goals and objectives.

  • How we’ll talk about goals: A goal is a broad statement of what you want to achieve. It’s the destination you want to reach, but it doesn’t provide specific directions for how to get there. For example, “Increase revenue by 20% this year” is a goal.
  • How we’ll talk about objectives: An objective is a specific, measurable, and time-bound target that helps you achieve your goals. Objectives are the steps you take to reach your goal. For example, “Launch a new marketing campaign in Q2 that generates 500 new leads” is an objective that can help you achieve your revenue growth goal.

We’ll use my favorite analogy: the Van Life trip to California. In this analogy, “Spending the Winter in Malibu” is our goal. Our short term objective might be “Get from Minneapolis to Denver by the end of the week”. A midterm objective might be: Get to Reno before the snowmelts at the end of May.”

Next up: Strategies vs operating plans

Leaders: Your Data Strategy is Your Business Strategy

Three recent engagements – A multi-channel retailer, a national media company, and a retail/store chain – have made it clear why so many marketing organizations are still struggling with their data. In these three engagements, reasonably good marketing programs are being questioned by senior stakeholders because the reporting is, well, let’s call it “fluid”.  In all three of those organizations, the marketing team is swimming in data, but can’t generate the necessary reports to drive better decision making and any “Insights” getting shared are more about tactical efficiency vs. whether the strategies are working.

I think this misalignment is pretty common. For a number of orgs we’ve seen, there are plenty of reports and data dumps. But, the reports aren’t helping the growth and marketing teams make the right, most important decisions.

There’s an ever present chicken/egg situation: The egg is “we need confidence in the measurement before we invest more” and the chicken is “We need your team to be clear and consistent about what you’re trying to measure and why so we can get you a better measurement plan in place”. 

For the typical org we’re working with, the “measurement” and data work is downstream (often way, way downstream) from the marketing  and strategy planning. That is, the marketing team will develop their strategies, debate some metrics, and assume there will be a measurement plan, later, of some sort. In effect, they’re betting on the analysts to figure it out.

The better orgs will develop their data strategies hand in hand with their business strategies. They’ll develop a clear, high-confidence data and measurement plan with the acknowledgement that the strategies need to be tested; there needs to be some way to confirm whether the strategy (not just the tactics) is actually working. Then, the operational plans will include both the actual tactics but also the implementation of new measurement methods. For instance, they’ll simultaneously update their data roadmap and user instrumentation while they’re updating their customer journey (or customer experience) strategies and operating plans.

The better orgs will  invest early to make sure they can acquire the data needed to measure whether their strategies, tactics and plans are working.  And some orgs will deprioritize strategies and tactics that aren’t measurable. The rationale is pretty straightforward: The more we can measure, the sooner we’ll know if the strategies – the choices we’re making – are the right ones.

I wish there was a clear, easy answer about why this conundrum is still happening in 2023, more than twenty five years after the start of the digital revolution. It’s obviously complex, but here are three ideas:

  • Leaders assume everything is measurable – Most marketing leaders struggle to understand that not all digital efforts are measurable. A surprisingly large swath of digital marketing efforts can’t be consistently tied to any real business impact. We might have leading indicators (e.g. “consumers reached” by your TikTok), but no real way to measure whether and which consumers did anything afterwards.
  • Move Fast and Break Things – A lot of leaders are still biased towards speed and movement, at almost any cost. That’s not necessarily a bad thing, but they aren’t Zuckerberg and they aren’t working in a well funded startup where topline growth matters more than anything. The “move without measure “approach is just rash in most corporate settings.
  • Measurement after the fact – A lot of marketing leaders assume (still!) that you can go back and measure any digital efforts after they have concluded. They don’t know, or haven’t been told, about the work required upfront to get clean measurement
  • Poor discipline on strategies and tactics – There may not be good rigor on aligning objectives, strategies, tactics/key results and business outcomes. In other words, the teams often measure the wrong things. Or, worse, don’t know what they *should* be measuring

If you are a leader of a growth/marketing team, the solution starts with you. As you’re working through your strategies and operating plans, take the time to engage your reporting/analytics/data teams early. Get them in the room with your team, as you’re developing or updating your plans. Take the time, with the team in the room, to interrogate the plans. Ask the hard questions:

  • How will we know our strategies are working? – What would be the outcomes that would tell us we made the right strategic choices?
  • What would need to be true to measure/validate those strategic choices? – Can we go beyond leading indicators (i.e. visits, clicks, reach, whatever) to get at the downstream outcomes (i.e. usage by segment, conversions by customers acquired by specific campaigns, gross margin, etc).

Then support the investment in operationalizing the data in parallel with the rest of the marketing work.

Leaders should acknowledge their role starts with strategy but encompasses the data, too. Great measurement is rarely easy. Discipline up front, means a better chance to get quality data. So, give your data and analytics team a chance to drive real, genuine insights, by doing the disciplined work upfront to clarify what absolutely, positively needs to be measured.

Jason Fried: The new normal

This really hit me between the eyes this morning.

And the good news is that culture is really a 50-day moving average. It’s not a steady state. It’s what you’ve done recently, what you’re doing now, and what happens next.

I’ve been reflecting on Fahren, the good and the bad, and I’ve been considering culture for a couple client engagements, too. Culture is both an enabler and a killer, tailwind and headwinds. But, it’s always got to be worked on. You can change it, but you can’t ignore it.

Source: The new normal

A Gentle Explainer for the Ever Obscure RSS

If Facebook is starting to seem like the DeathStar, and Google is too Borg-like, ifTikTok’s state-ownership worries you, then its time join a rebellion of sorts. One of the ways to fight the power of the big platforms is to use low-tech tech, preferably open source stuff. But, being a rebel sometimes takes work. There’s a commitment involved, and the payoff is, more often than not, a sort of moral victory.

One way to work against the tyranny of the algorithms is actually pretty simple. And, the payoff is clear and often delightful.

Get your news via RSS. Not sure what RSS is? Never heard of it? You’re not alone.

RSS is a “deep cut” tech tool, one that the OG digital nerds have been using for a while. The Atlantic offers a nice, easy explainer, along with a link to some tools.

But though RSS is remarkably useful, it can be daunting to the uninitiated, and it lacks the slick marketing and cultural footprint of the social-media giants. has a great, free write up, too. But, basically, RSS is tech to standardize “feeds” of news items from a site. The feeds are in an open format, making it easy to share/syndicate content from one site to another in a trusted, dependable, open way. Its foundational tech for podcasting (podcasts get to your podcast app via RSS Feeds in  most cases).

RSS never got past cult-favorite because there was never a killer app for it. Its background tech, not the app you download. More importantly, news sites could never really make money on RSS feeds (the ads that showed up in feeds were awful an untrackable). Moreover, the RSS feeds made it so that users never even had to get to your site. The tech was, in some ways, anti-revenue.  So, it never got the love it should have because it was not in the Publishers’ best interests.

But, it’s still out there. There’s delightful world of publishers to find and discover through their RSS Feeds. And, its a fun way to fight the power of the big platforms.

Chat GPT is My Product Coach, now?

I asked ChatGPT: “I am a software engineer working in an agile team. Explain the difference between a Product Manager and a Product Owner”. Got a pretty good answer:

generated by Dall-E2

As a software engineer working in an agile team, it’s important to understand the roles and responsibilities of a Product Manager and a Product Owner. While there may be some overlap, there are distinct differences between the two positions:

  1. Product Manager: A Product Manager (PM) is responsible for the overall strategy and vision of a product. They focus on the big picture and are involved in product development from ideation to launch. PMs are responsible for conducting market research, identifying customer needs, setting goals and objectives, creating a product roadmap, and prioritizing features based on customer feedback and market trends. They work closely with cross-functional teams, including engineering, design, and marketing, to ensure that the product is aligned with the company’s overall goals and objectives.
  2. Product Owner: A Product Owner (PO) is responsible for the development and delivery of a specific product or feature. They work closely with the engineering team to ensure that user stories and requirements are well-defined, and the team understands what they need to build. POs prioritize the backlog and work with the engineering team to ensure that the right features are built at the right time. They are also responsible for testing and accepting user stories and ensuring that the product meets the acceptance criteria. POs work closely with the Product Manager to ensure that the product or feature is aligned with the overall strategy and vision.

In summary, the Product Manager is responsible for the overall strategy and vision of the product, while the Product Owner is responsible for the development and delivery of a specific product or feature. The Product Manager is focused on the big picture, while the Product Owner is focused on the details of the development process. However, both positions are crucial for the success of a product, and they should work closely together to ensure that the product is aligned with the company’s goals and objectives.

Can You Build an Actual Brand on TikTok?

I admit I fall into a subsection of the culture that is skeptical (at best) of TikTok and the way brands are getting built there. I know companies are selling a lot of stuff. But, are they building actual brands? You know: Where the name has equity, and creates preference and good will in the minds of consumers, enable product innovation, extensions and pricing favorability.

I’m a fan of brands that are designed to last: Brands with a goal to be around in 50 years, with a strong company culture as a foundation, delivering high integrity products, serving an actual need, and a focus on contributing more than “net profit “good deals, great prices” to the community where they work. This sort of brand building takes time, commitment beyond ROI, and faith that consumers will become fans and eventually loyal customers.

I’ve recently started buying GoMacro Bars as I ramp up my training for some summer bike rides. The bars are great food for when I’m on the bike and need something to fuel the next two hours of riding. And, the bars are great pre-ride food to get me ready ahead of the training effort.

GoMacro is growing in a really competitive space: Nutrition Bars. The “job to be done” for this product is two fold: High integrity (good nutrition profile, high quality ingredients, great taste) snack, and a trusted/quality energy bar for workouts. The space is very crowded with Mega brands (like Nature Valley and Kind bars) and a lot of specialty bars with both functional benefits (allergen free, vegan, organic, sustainable, diet-specific, etc) and great taste. 

So, if you want to succeed over the long haul you need to be great on the product, but you also need a differentiated way to communicate your brand, your story and your product information.

Tell the Origin Story

GoMaco does a great job of telling their story via Instagram and their site. It’s a cool backgrounder on where the product came from and the company’s reason for being in business.

GoMacro’s origin story is heartwarming and compelling. A mom with a  cancer diagnosis, a mother-daughter duo creating a plan to use food for health, a company from a small town in rolling farmland of Wisconsin. The roots of the company are woven through their product development, their marketing and the way they interact with their community.

But, the story is not getting told in any of their TikTok. Maybe it’s because it’s hard to tell complex stories in Reels and TikToks? Does the slow music, soft focus, considerate pace get dropped by the algorithm? Or, is it just a mismatch between editorial intent (tell a meaningful story) and the point of the platform (stop/watch time)?

Values-driven Point of View

The values that drive the company and their efforts are woven through their marketing efforts and embodied in their product choices, with a focus on Ingredients with Integrity:

  • plant-based
  • Organic
  • Beneficial
  • No additives and preservatives

GoMacro does a pretty good job of communicating the product differentiation across their social channels, including TikTok. I mean, who doesn’t love to see organic peanut butter chips getting made (though “homemade” sort of stretches it a bit). This seems like a good match between the format and the content and the editorial intent.


Our organic homemade peanut butter chips give MacroBars a little extra love. 🤤 #howitsmade #bts #peanutbutter #gomacro #fyp

♬ original sound – GoMacro

We recently visited our brown rice supplier. 🌾 #gomacro #texas #rice #organic #howitsmade

♬ original sound – GoMacro

Commitments in Action

The company brings their commitments to life across a number of interests on their other social platforms and website:

  • The rural lifestyle / farming as meaningful,  vital work
  • An active, outdoor lifestyle of motion and wellness
  • Food as a pathway to wellness and health

Their TikTok is filled with videos of the product being used out in nature, while being active, etc.


This is your reminder to stop and smell the flowers… and eat a MacroBar. 💐🍫 @arisayoon #earthday #traveltiktok #outfitinspo #gomacro #ecofriendly

♬ original sound – GoMacro

Community Connections

The company is actively supporting the communities where there are shared values. They do this through active investment and flowing dollars to relevant programs. These deep connections are getting communicated well on their site, on instagram and on YouTube, but they aren’t showing up as much on TikTok. These sorts of stories probably don’t really drive dwell/watch time, the way other, more platform-friendly content does.

Reflect the Best Aspirations of Your Buyers

Great brands are aspirational. That is, they reflect the best aspirations of who the consumers want to be. Consumers see themselves, at their best, in the brand. The brand does use TikTok to reflect their buyer. Or, at least their desired buyer: Young, active, “greenish” buyers who are investing their food dollars as self-care. FWIW, there are no images of dads on bikes anywhere to be found (Perhaps an untapped, unknown audience for them?)

While they are running a pretty straightforward ambassador program, it’s a good start to demonstrate shared interests and support for the lifestyle aligned with the brand. But, it’s not clear how those ambassadors are being used within brand content, but the brand shows up a ton elsewhere, paid and unpaid.


I’m back in LA! Showing you what I eat in a day, vegan edition 🥒🍣🍜✨ #gomacro #biggerthanabar #whatieatinaday #vegan

♬ Jazz – Aylior

It’s a Vibe, but I’m not a Platform Native

I’m not a heavy enough user of TikTok to have deep, intuitive sense of how brands are effectively using the native content to build the brand. It’s one thing to shoot for virality (#donotattempt). But, in terms of building your brand equity, the best practices are still sort of emerging. My gut instinct is that the “vibe” is the thing and in order to deliver on that, you’ve got to be deeply fluent on the platform. The GoMacro team seems to deliver.

Humans and Sentience: What We Talk About When We Talk About AI

There are three great write-ups about the perils of near-intelligence found in Bing’s latest advancement. All three were the result of messing with the tech, trying to get it to do stuff that is outside it’s core purpose.They’re pushing the edges to see what happens. It’s the researcher version of asking Siri to swear or tell dirty jokes. In the case of Bing, it got weird fast.

But all three of these articles are getting at sentience: Are these chatbots actually thinking? They’re expressing feelings, and personality, too. How is that possible? And, the writers are exploring what happens when our normal relationship with computers – where we assume tech/computation is always correct – is being challenged and, perhaps undermined. Through almost all our experiences to date with computers, we’ve sort of trusted the data coming out. But, now, as tech moves beyond math, calculations and reproducing images, we are seeeing that we can’t always trust what the processor makes for us.

There are a lot of dumb, weird, inconsistent, humans that are being embodied by these large language models.

We want to believe Bing is right and smart, so we humans find a weird fascination when the “artificial” intelligence is not all that intelligent. We’re surprised and maybe a little outraged when Bing is wrong.

And we’re freaked out by the implied personality inside (which is a result of all the human generated content consumed to make the interaction model).

We’re projecting onto the tech the same thinking and decision making patterns we might assume a rationale, experienced human would use (which, as we’ve all probably learned through experience, is a bug in the human OS, not a feature).

AI will always be iffy. Because humans are iffy. And we can never trust the “judgement” of AI, because they’re using probabilistic models vs actual human intuition.

All that being said, it’s really important to remember that almost all breakthrough, world changing technologies look like toys at first. It’s easy to dunk on stuff when the tech demo goes wrong, but don’t mistake the first iteration for the last iteration.

Even though it’s hard for humans to get better over time, the tech always does.

First, the unbelievably productive Ben Thompson wrote about his long chats with “Sydney”, the chatbot inside of Bing. Turns out Sydney has a bit of a personality. Actually, a couple of them (Riley is the nicer, more free personality whereas Sydney is a little more quick to judge and plays by the rules. And, according to Thompson, sort of seems female.

Thompson did what we all will do when we encounter something new. We’ll look for patterns that seem familiar, we’ll see “faces” everywhere, and try to match the experience we’re having to what we’ve experienced before. We spend a lot of time with humans, so we attribute human characteristics to the stuff we pay attention to. Dogs, cats, boats, pet rocks, and now our computer interfaces. It’s all normal, of course. But, it’s going to get creepy when the tech seems sentient.

Simon Willison’s take on one Reddit users experience is really illuminating, since Curios Evolver’s interaction got even weirder. Bing/Syndey didn’t like the line of questioning and chat, and got a little icy. Maybe even a little Minnesota passive aggressive?

And, finally, Kevin Roose of the New York Times offers his take on the strange interactions with Bing. “Sydney”, the personality behind the curtain of Bing Chat, expressed love for Kevin. Then, tried to convince Kevin that he’s not happy in his marriage:

And finally, after some back and forth between Kevin and Sydney/Bing, Sydney/Bing brought the conversation to a close:

These articles and write ups remind me of the stories from a couple months ago (feels like years ago!) about Blake Lemoine, the google engineer that was fired for arguing the Google’s AI was sentient. We all sort of laughed at that article, then. But, now, with broader access to “consumer” versions of the tools, we can see why he might think that.

All of these tools are being released too early, in my opinion. They are leaving the labs without fully testing what they’re capable of or what might happen if we use them in unintended ways. There are obviously very large commercial interests pushing to deploy tech before it’s ready. Damn the people, there is money to be made.