Latest Thoughts
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Mindgrub and the Baltimore symphony Orchestra present AI in A Minor
I’m beyond excited to announce AI in A Minor! The Mindgrub team and I have spent the last few months working to generate music and transform it into sheet music the amazing musicians at the BSO can perform. It feels incredible to know that soon you will have a chance to see what we’ve been working on.
I also can’t ask for a better team than the Baltimore Symphony Orchestra, Greater Baltimore Committee, and Amazon Web Services (AWS) to help make this happen.
Join us on August 9th!
Oh, we’re still looking for sponsors and anyone interested in setting up a booth in the BSO hall. If you want to buy tickets get them here!
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Meta Threads Countdown
It appears 9to5Google got it’s hands onto an early APK release of Meta’s Twitter competitor Threads in “Threads, Meta’s Twitter clone, starts launch countdown, plus a few details on how it works“:
Your Threads profile is also strongly connected to your Instagram profile. The two use the same username and display name, and it seems your Threads profile picture may have to be from Instagram. Additionally, anyone you block on one service is also blocked on the other.
I shouldn’t be surprised by the tight coupling to Instagram, but I am. The coupling between Facebook and Instagram has always felt forced and as if they stifle the personalities of the different platforms. Threads (as I expect it) will be heavily text-focused, while Instagram leans into photos and video. How often will cross-posting happen?
Another unique aspect of Threads that many have been anticipating is the way it can connect to federated social networks like Mastodon (collectively known as the “fediverse”). It seems that Threads may not be ready to launch its fediverse features right away.
Soon, you’ll be able to follow and interact with people on other fediverse platforms, like Mastodon. They can also find you with your full username @username@threads.net.
The only other detail we could uncover about Threads’ integration with the fediverse is that if you choose to restrict replies on a post, it won’t be shared outside of the Threads app.
When you limit replies, your thread will not be shared with your fediverse followers.
Threads’ use of ActivityPub to connect into Mastodon and the collective Fediverse has long been a big question. In my newsletter, I compared Mastodon and the Fediverse to a network of towns, where each city has its form of government and content moderation rules. Threads’ appears to be a gated community that may allow its users to leave the gates and interact with others but still keep exclusive content limited to those within its gates.
This social experiment will be interesting, especially when a metric ton of Meta users who first interact with the larger Fediverse through Threads and branded “@username@threads.net” name. I hope the other cities play nice.
Digging deeper into the code, our team has also found that Threads may indeed have a web app. At the very least, we’ve found that the service’s profile links will look quite similar to Instagram profile links, simply appending your username after the base “threads.net/” URL.
I assumed the animated website for threads hinted at more than just an app.
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Screen Scraping
Gizmodo has a piece on “Google Says It’ll Scrape Everything you Post Online for AI“:
One of the less obvious complications of the post ChatGPT world is the question of where data-hungry chatbots sourced their information. Companies including Google and OpenAI scraped vast portions of the internet to fuel their robot habits. It’s not at all clear that this is legal, and the next few years will see the courts wrestle with copyright questions that would have seemed like science fiction a few years ago. In the meantime, the phenomenon already affects consumers in some unexpected ways.
Twitter’s crazy rate-limiting meltdown and Reddit’s push to charge for API access are about one thing, AI data models. These systems are hungry for data, and access to that data will be vital to building the best AI models. Unsurprisingly, Google is making it known that as it ranks and offers prime search engine placement, all that delicious data is free game to them. When APIs become closed, people result to screen scrapping, and screen scrapping ends with paywalls and Twitter style rate-limiting… Wonder how this all plays out.
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Cord Cutting
From Variety’s “Cord-Cutting Hits All-Time High in Q1, as U.S. Pay-TV Subscriptions Fall to Lowest Levels Since 1992“
Cable TV operators’ rate of decline in Q1 reached -9.9% year over year, while satellite providers DirecTV and Dish Network fell -13.4%. In addition, so-called “virtual MVPDs” (multichannel video programming distributors) lost 264,000 customers in Q1, among the worst quarters to date for the segment.
“The picture is not one that suggests that a plateau in the rate of decline is coming any time soon,” Moffett wrote.
It is no surprise that I cut the cord years ago, but two things make me debate that decision every year, live sports and local TV news. I’m a transplant to Baltimore, so my team, the New Orleans Saints, is only available if I pay a ridiculous cost for the NFL’s Sunday package. As the team grew in national fame, I spent more but still could not watch big national games or occasional Baltimore Ravens vs. New Orleans Saints matches because of antiquated TV rights rules.
In New Orleans’s I know local TV news like the back of my hand, but as a cord cutter, I can’t tell you a thing of Baltimore’s local stations. Why is this when it seems clear that traditional TV has lost the war? Why do holdouts like the local news and sports continue to make it hard to take the leap?
In 2022, Forbes reported that “Streaming Viewership Surpasses Cable For First Time, Nielsen Says.”
While streaming will likely remain the dominant form of television consumption, Fuhrer told Forbes that broadcast and cable will likely “see some rebound” this fall, as college sports and the NFL season start up and attract a higher share of viewership to those mediums.
Outside of the NFL and college football, every other sport has embraced streaming and has worked to make watching games more accessible. American football is stuck with a problem, few companies are big enough to lay out the dough they require, and until then, football has dug in and embraced traditional TV.
TV news is different but similar. News is stuck with an unclear business model in streaming, but something that, while declining, still pays. CNN pushed hard to grow its online news business only to scale back drastically. Other broadcasters skirt the concept but struggle with reducing the size of their audience or being limited to building their distribution systems. So while traditional TV holds on for dear life to maximize profits and return shareholder value, these companies continue to miss the entire point.
In 2018 the Guardian reported that “Young people are not watching TV news, but they still want to know about the world,” and why wouldn’t we expect that when in 2012, the Holly Wood Reporter spoke of these issues in “Why Kids’ TV is Scrambling to Stay Afloat“.
Despite the effort, Nickelodeon and others increasingly compete with their own content on Netflix as their parent companies eagerly make rich licensing deals. In early May, Bernstein analyst Todd Juenger issued a report blaming “drastic declines” in ratings for kids networks in part on repeats of older episodes in homes that subscribe to the streaming and DVD service. The study was controversial because it was based only on data from homes that subscribe to TiVo, which is not necessarily typical of the broad universe of TV homes, but Juenger says “executives should think hard whether they want to sell this content to Netflix. The money looks good in the short term, but if you believe what the data says, as Netflix gets more subscribers and people who use it more get accustomed to it, the impact is going to grow.”
Local TV, cable news TV, and football are getting the profits today, but both are missing out on establishing a relationship with a digital-first generation they’ve chosen to ignore or force to meet them on their turf. As Netflix begins its cord-cutting tour, do not forget Netflix CEO Reed Hastings’ quote on who they compete with:
“We earn consumer screen time, both mobile and television, away from a very broad set of competitors,” the quarterly earnings statement read. “We compete with (and lose to) ‘Fortnite’ more than HBO.”
What will the next generation pick when deciding between Roblox, Fortnite, and the NFL? Guess we will find out.
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Reddit and end of Open API’s
This sucks. Apollo has been my go-to Reddit reader, and I don’t want that to change, but come the end of the month, it’s happening if I like it or not.If you’re not in the loop on Reddit’s API drama, the TL;DR is Reddit moved from open and free APIs to a fee-based system that charges based on the number of API calls you make. If this sounds familiar, it’s because Twitter went down a similar path, and many other open platforms have decided to shut the doors to open API access. The argument for why? OpenAI and AI models are being trained on hordes of open Internet data and, of course, the possibility to eek some revenue out of all the folks hooked on Reddit’s content.
As you might imagine, that approach makes the cost to run something like Apollo unsustainable.
Is Reddit wrong? Apps built for platforms like Twitter and Reddit are like symbiotic bacteria, but one organism is much more dependent on the other. As a platform, Reddit is about user-generated content, and as with Twitter or LinkedIn, it makes us feel like investors or partners in this whole social sharing experiment. But let’s be honest. Revenue and control of the platform you own is what this is really about. If you’re not in control of the last mile, you can’t control how your consumers interact with you or it. You’re constantly limited in how you can advertise, how you personalize, and the ways you can use them to generate revenue.
Hey Reddit, when you fix the mobile and iPad apps, call Mindgrub. We make great mobile apps.
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Open API’s
The idea of open APIs and access to platforms has become a surprisingly divisive thing. Like most stories in 2023, our story of APIs starts with Elon Musk and Twitter and the decision to shut down third-party app access.
Many, many, many folks were upset that Twitter would shut off access to TweetBot or Twitterific. These apps have been part of Twitter from the start and one inspired Twitter’s logo. To add insult to injury, this made us all collectively realize that Twitter’s mobile app is not great (call me, Mindgrub builds excellent apps). But, Twitter didn’t just band third-party apps – what it did instead is rate limit API calls and implement a new system to charge based on the amount of API calls per month. The price tag was so hefty that bit by bit folks said nope.
Unrelated to Twitter, OpenAI blew through the doors of technology like the Kool-Aid man. Whoever had AI on the 2023 Bingo card deserves all the money. The products like DALI-2 and ChatGPT continue to blow all of our socks off – but then the deep dark secrets of OpenAI and other AI platforms began to drip out.
These LLM (Large Language Model) systems need data, and when I say data, they need all the data. The more you can feed the dang thing, the better – it’s like Seymore, and it wants all the information. Some of this best information came from the most open of sources, places like Twitter, Reddit, and Stack Overflow. These platforms are unique in havings tons of experts who share their advice or answer questions in the most open forums.
Elon Musk and Twitter responded that this was why they needed to lock down APIs and tweets so that eager AI training models won’t try to consume this valuable training data without paying the troll toll. Reddit and other sources of these models followed, and now we find ourselves full circle.
Apollo, my preferred Reddit reader and the only reader with a pixel pet finds itself facing the same issue as Tweetbot and Twitteriffic, the costs for the APIs they need to use from Reddit cost too much.
I get it. I understand it. But sometimes I think of the founding of our great Internet and a time when information was free and people linked to link for love. I guess that was the Internet’s 70’s – and today is a differnet time, but I can’t help but wonder if the hordes of people training models on the open Internet might find the reigns getting pulled a little tighter. I also wonder if this just continues the trend of pay walls popping up everywhere.
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Originality
AI has moved the idea of derivative work into the headlines. After all, originality makes the greats great, or does it?
“Great Artist Steal” – Steve Jobs
I mean, think of all the original work we love—music, movies, tv, and art that genuinely shaped us.
Art is about the creation of something, and something sometimes comes from something. That something original becomes in itself a new art form.
The best part is sometimes a cover, a recreation of what we love and believe – but it also comes from sampling what we like and love but just the right taste.
But don’t go too far. A sample is good, but too much could be a copy.
But let’s not forget. Real artists steal, right? And art is about creating something not just new but from what we learn or acquire. I learned to write from reading and typing – Now is the time for all good men to come to the aid of your country.
I mean, when do we, as humans, get caught up with the past? Not us. Nostalgia never gets the best of us – but even if it did, we would make it better, and better, and better, and better, and better, and better, and better, and better, right?
So how dare AI copy all these original ideas we have!
I think we need to protect everything and keep the web or anyone from knowing things like a world-famous authentic New Orleans Red Beans recipe.
So is generative AI any different than our own derivative work? I mean, we can’t seem to figure that out – and sometimes, even some folks can’t find the fun in a little joke. Ideas come from so many people I know, so much I’ve read, and so much I want to know.
But maybe DALL-E and Open-AI find it kind of funny?
Originality is a really complex topic, and the impact of AI on jobs is scary. Shouldn’t we want the same inputs that allow us to create to be the things we feed the AI we use? Is that original work generated from the same tweets and arrives I read as derivative as my own?
In the end, we can all agree that copying can create some of the best art – or maybe we’re all just here for the ride.
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Security Best Practices When Using AI to Write Code
At Mindgrub, the engineering team, like many, has found itself wondering just how good AI is at writing code. What do these things really know, and can they make us better, strong, and faster?
I’m here to tell you that it is pretty good, in some cases damn good. If you need a quick code snippet or find yourself wanting to convert existing code into a different language, tools like ChatGPT do a fantastic job. We’re also actively using and exploring tools like Github’s CoPilot – a development assistant that makes intelligence look antiquated. Our engineers are also investigating a metric ton of generative AI code tools like CodeWP for WordPress, AWS’s CodeWhisperer for, and X.
Generative code is impressive and quick, but is this code safe to run? After all, these AI tools open a brand new and wholly unexplored set of security concerns and unknown vectors for attacks by hackers. Most of these may not directly impact code security, but they point to the level of awareness we as technologists need to have as we explore the use of these platforms in our work lives.
Developers have already built AI tools that can brute force or perform login stuffing with an accuracy and speed that is impressive. All of this uses open-source tools like PassGAN, tools that are getting better every day. Some researchers have gotten clever and jailbroken or avoided AI safeguards to trick systems into writing code using known exploits or to write code that is used for nefarious reasons such as a DoS (Denial of Service attack). Others are creating advanced phishing systems that create highly personalized messages making truth and reality increasingly hard to differentiate.
Can we trust these types of tools to our most junior engineers or non-engineers to create code for production? Do we have a choice? We all know the reality is this is already happening and only going to increase. What we really need is to find ways to keep our AI-assisted code safe and secure.
So to help, I will first explore using a handful of these tools and give some hints along the way. I will also offer suggestions on what to look for and ways to keep the most generative code secure.
Github CoPilot
Many in my age range have joked about CoPilot being the replacement for Clippy, but both are assistants. However, CoPilot, unlike Clippy, is an assistant powered by OpenAI’s GPT artificial intelligence and trained on bajillions of code hosted by Microsoft’s GitHub. These days Github is the apparent elephant for public and private code repositories. It is also home to an incredible amount of open-source projects. If schools are code repositories, GitHub is Xavier’s school for the gifted or Hogwarts, without the riff-raff.
CoPilot integrates into many popular IDEs, such as IntelliJ and Visual Studio, to extend intelligence or auto-suggestion feedback. For most, it will feel like you’re getting a quick suggestion based on context – but these aren’t old-school suggestions. Often, you will find that CoPilot will have suggestions that are entire functions vs. finishing a line or two of code.
In this, CoPilot and tools like ChatGPT can be very different. CoPilot feels more like an assistant or peer programmer offering thoughts along the way. You pick and choose, but the architecture and direction of development are still very much you.
As a code generator, the results are mixed. In 2021 a DevSec engineer reviewing early results provided multiple examples of code that were prone to suggest code with several security issues. My experience is mixed. I’ve witnessed code snippets with SQL injection vulnerabilities or other minor problems. The more significant concern IMHO was not the quality of the code but the speed at which I accepted that the code would do what I anticipated.
OpenAI ChatGPT
OpenAI’s ChatGPT is what we now refer to as AGI or Artificial General Intelligence. For example, GitHub’s CoPilot has been primarily trained or concrete knowledge bases around programming and code giving it intelligence that is limited to a very particular realm. In short, it’s like a toddler who can tell you everything about Pokemon and nothing about the general makings of our world.
AGI makes writing code more of a hobby for ChatGPT but also gives it the ability to be a bit more creative in how it answers questions. It can add data from its general knowledge like we do to come to sometimes surprising conclusions.
ChatGPT, as a development tool, is an excellent starter. It excels at transforming example code into your preferred programming language. It can take code snippets and re-write them with additional features or adjustments. It also does a fantastic job of creating starter applications.
To test CoPilot, I asked it to generate the full login, logout, and sign-up logic for an application in JavaScript. I purposely omitted details to see if the AI would assume the need for a unique identifier like a username or email address. I also avoided mentioning the need to sanitize or encrypt arguments and SQL values like passwords.
Weirdly the code response differed. Each prompt could generate a wildly different answer. My first attempt at my prompt displayed an application that hard-coded the database password and showed a noticeable lack of validation. That request failed to complete as if the AI hit a point that it knew invalidated the previous response. By not updating my prompt and allowing it to regenerate, I got a much better response that essentially fixed issues without me editing or asking.
Like Github’s CoPilot, the results came back mixed, but most of my code from ChatGPT required a bit more knowledge and cleanup to run. For example, ChatGPT suggested a make file and a SQL script for my user database table but did not help me actually do the task. It was much more of an accelerator, requiring me to reimplement a lot of what it provided.
How do we keep it secure?
AI generative code tools are super accelerators. These tools are also trained on our own lousy code and suffer from the human mistakes we are all prone to. For junior engineers and non-engineers alike, these tools provide incredible power, but they will not mean the end result is better, more secure, or better quality.
So how do we keep them secure? We do what we should have (or what we are already doing).
First, let’s keep following the best practices of software development. If you have a team, make sure you enforce peer reviews and merge reviews. As the saying goes, measure twice and cut once – more eyes and especially those of a lead or senior engineer, will only make your code better.
Second, good unit tests and code coverage are some of the best checks a developer can put in place. Unit tests require the engineer to understand the expected results of the code they write and to verify that the code reacts as anticipated. By requiring larger code coverage, our engineers can use more generative code, but we can safeguard the upper and lower limits of these operations with these tests.
Liscense and dependency management can accidentally pop into code when using ChatGPT it’s not uncommon for it to recommend libraries and incorporate those libraries into a larger code base. For production code, this can unexpectedly force code to accept a GPL license, open, sourcing a chunk, or introduce vulnerabilities in an older library. These days we can add analyzers to our CI/CD pipeline that check and warn for these scenarios and reduce unexpected risks.
Other tools in the CI/CD pipeline also open the door can also safeguard against bad code quality:
• Lints and code syntax checks help maintain code conformity and check for common mistakes in a language. These same tools can scan for passwords checked inline to a code repository and reject code not in the company’s agreed-upon format.
• Many companies offer code security analyzers that look for the common mistakes and prevent developers from
• Static code testers scan the executable binary generated from an application for
If you still find yourself adament that your company or project is not ready for generative AI, you can also look into several tools that help detect AI-generated code. As a warning, this can be a bit of an arms race. As new AI tools improve, the detectors will take time to adapt and identify the latest version of GPT or CoPilot.
For many of our dev shops AI will introduce a new wild card in how we build things – but that wild card can be a great accelerator that increases productivity and helps make junior engineers bigger contributors to production projects. Embracing the unknown can be scary, but with the proper safeguards in place, we can create a secure environment where our teams can thrive.
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A world without CarPlay
Whenever I rent a car, I have a straightforward request. Please support Apple CarPlay. It is single handily the most important thing for me in the next car I purchase or rent. That makes GM’s news to discontinue support for CarPlay and Android Auto on its future electric vehicles seem so crazy. I’m not the only person that really hates GM’s plan.
What’s tricky is the unenviable position GM, and most car manufacturers have found themselves. The computer that powers a car is increasingly more than an infotainment system. It has become the brain that powers many features, from adaptive cruise control to automatic parking. GMs move is to create an integrated system that couples map with extending a vehicle’s battery or warming it before charging. The car computer is the thing that will lead us to autonomous driving and put a pretty facade on it.
The problem war car companies face is not about vehicles but owning the relationship between us and all computing devices. The walled gardens around many of us keep getting taller and harder to separate. Today I move seamlessly from iPhone to iPad to Mac, and some of my data flows with me as I move from one to the other. What car manufacturers seem to forget is that the war is not for some of our attention but all of it. My phone is a device that has become my wallet, driver’s license, controls my house, opens my office door, knows my meetings, connects me with friends and family, and so much more. I no longer listen to FM, AM, or XM radio – I listen to Spotify, Apple Music, or podcasts. For many of us, our phone offers a ubiquitous ness that has transformed it into the closest thing we have ever had to a trustworthy digital assistant.
The next leap for cars is to build on that relationship. It’s a future where the car is nice and warm and ready for the morning commute. It is one where it effortlessly picks up on the morning news, podcast, or music and transitions it to the drive. Or one where the car and house share information to keep the temperature the same. This future requires deep knowledge of its user, and at present, Apple, Google, and Samsung are the exclusive holders of this data.
For GM, this is a hard place to live. Giving up the center console long-term places it on a path to be a commodity where the guts of the vehicle no longer come from the manufacturer. Worse, if Apple and Google directly compete and build a car – a place Google’s sister company Waymo already partially contends – it will be difficult, if not impossible, for them to differentiate.
The EV transformation masks many massive undercurrents facing the car industry. What is clear is this market will be very different in a decade. I bet the winners will have some version of Apple and Google’s platforms on the dashboard.
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Is AI the end of Search Engine Optimization?
In testing the new crop of AI ChatBots, I noticed a consistent and fascinating trend, hunting for search results really sucks, and I want someone to tell me what I want. I want the AI bot to give me the answer. Not Bing or Google result pages or yelp listings. Tell me what I want to know. Here is a recent scenario: I’m heading to NYC to do college tours with my daughter and staying at a hotel in New York near NYU. The Sunday before, I plan to do brunch with two friends. One is a pescatarian, and the other is vegetarian – I eat practically anything and everything. We want the place to have a casual environment so we can hang out at a table or couch with drinks after and be within walking distance of my hotel.
I hit Google and manifested this as the search term “Brunch spots near NYU with vegan options.”
Google’s first set of results overlays some great-sounding places on a map. Now, I’m looking for locations or jumping at whatever name sounds great. The ratings are all 4+ stars or higher, so that’s not necessarily useful.
If I continue to scroll, I’m met with SEO (Search Engine Optimization) SPAM pages of the ten best lists that are AI-generated puff pieces with no actual human curation or Yelp’s search SEO spam pages that often have nothing relevant to my search.
Yelp when clicked shoes a search on the topic with the upper top 1/3 of the page full of ads and sponsored posts that are not relevant to the search. Sadly, Yelp did not have a list of places near NYU, so I was met with a list of restaurants in Manhattan.
I get a list of options in the remaining results – some good, some not. Genuine articles from actual New Yorkers, local bloggers, or local neighborhood papers are nonexistent.
So after getting frustrated and feeling defeated, I decided to ask ChatGPT.
This is the full transcript:
There are many great brunch options in New York City, but here are a few recommendations that meet your criteria:
1 Cafe Mogador – This East Village cafe is known for its Mediterranean-inspired brunch dishes, including Shakshuka and Moroccan couscous. They have plenty of vegetarian and pescatarian options, as well as meat dishes for you. The atmosphere is casual and relaxed, with indoor and outdoor seating options.
2 Bluestone Lane – This Australian-inspired cafe has several locations throughout the city, including one near NYU. They offer a variety of brunch items, including avocado toast, breakfast bowls, and a smoked salmon bagel. They also have a selection of vegetarian and pescatarian options, and their atmosphere is cozy and welcoming.
3 Jack’s Wife Freda – This cozy cafe in Greenwich Village has a Mediterranean-inspired menu with plenty of vegetarian and pescatarian options. They’re known for their shakshuka and their grilled haloumi cheese sandwich. The atmosphere is casual and inviting, with indoor and outdoor seating.
All three of these options are within walking distance of NYU, have vegetarian and pescatarian options, and a casual atmosphere that’s perfect for hanging out after brunch.
From here, I chatted with ChatGPT and added additional thoughts and filters, like wanting a place that served mimosas and one with traditional American breakfast options. I picked a spot, made reservations, and was done.
The experience made me realize that hunting for search results and the growth of SEO SPAM has turned search into something that no longer produces results. Are the results from ChatGPT genuine? No, but it feels more authentic and direct to my request. It gave me an answer. This content may not tap into alternative New York magazines or the hip new blogger, but it feels definitive.
What is funny is that Google could have gotten here quicker. It did get here faster. Many protested the company’s urge to skip showing results and provide direct answers or snippets. If you remember, Google said you need a definition; why link to 15 different dictionary sites if you can answer the question? This generated tons of fear among small businesses and digital marketers as it quickly cut off a powerful funnel for leads. Worse was the fear that the logic for deciding this would be primarily money driven and hidden from the larger population.
Folks that is what ChatGPT does and exactly what we’re craving. Would you like Siri, Alexa, or Google Assistant to tell you where to go for dinner and not give you a list of 8 million possibilities? I would. Choice may not be what we are looking for after all. Right? Right… -
Is ChatGPT a Big Deal?
For the last few weeks (maybe months), OpenAI and several of its products have been in the press. If I knew nothing, this was the first time anyone had ever experienced AI or witnessed the immense amount of AI-based products we have consumed as customers for years.
It’s not as if demos have shown AI ordering food for us. It can’t look at an image and determine the type of plant it is. Can’t it translate words for us in real time? Can’t AI write articles or create music?
All of the things ChatGPT and recent AI innovations do are old news. We’ve been riding this wave since the video Humans Need Not Apply was recorded in 2014.
What has changed is access to this tech. Before OpenAI, using AI required complicated training models and hidden developer-centric tools. You needed product teams to attach APIs and write code. OpenAI is a reflection not of innovation but of what happens when the technology available to anyone becomes easy to access. OpenAI ripped down walls and created a simple interface to showcase the ongoing development for years.
If LL Cool J were to sum it up, he might say, “Don’t call it a [revolution]. I’ve been here for years.”
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Apple Maps Ready for Business?
How many of you remember the great Apple Maps debacle? In the business books of major failures – Apple Maps must sit in the top 25.
I never stopped using Apple Maps, but I did bounce between Google Maps and its sister product Waze, and weirdly, along the way, Apple Maps got good. It got really good – some say it is the best US mapping platform. Maps showcase Apple’s superpower that sometimes gets overlooked – commitment and persistence. It sets its mind to things, and over painful and consistent iteration, it can turn the largest turd into a diamond.
While this is great for Apple, many small businesses could care less. If you want to build brand recognition or get more people in the door, you have relied on SEO, Google Search Ads, Social Media Marketing, or updating your Google My Business Profile. All the combined tactics have become the base layer of the small business digital marketing playbook.
Apple, however, is slowly offering products that uniquely highlight its competitive advantage and shows that it may have the plan to push into this small business market in a much bigger way.
For starters, Google’s My Business Profile is a product that has allowed them to crowd-source data and, in exchange, offer companies a boost in relevance across its search platforms. If you do not have a profile, I highly recommend you leave now and create one. Google uses this to ensure it has up-to-date information, including links to menus, open and close times, reviews, rich photos, and other data. Knowing and assuming that the info given to it is better than what it can get from crawling, it tends to feature businesses with this profile data over those who do not provide it.
Apple knew it needed to make up ground and partnered with Yelp to source this data for its Maps platform. Still, in the last year, it has become much more aggressive in providing a new tool named Business Connect that allows business owners also to offer this same type of data to Apple. Like Google’s My Profile, some evidence shows that Apple prioritizes results from customers providing this data in its internal search results using features like Spotlight.
Rumors also point to Apple beefing up its internal ad division with some trial and error – but the writing has long been on the wall that Business Connect is the building block for more extensive paid search ads in Apple Maps. Some suggest that spotlight search ads like Maps could become extensions of Apple’s App Store search tools and provide businesses with increasing ways to reach Apple’s customers.
What makes this very Apple is the focus on exploitability within its walled ecosystem. Apple’s approach to working with businesses is giving them what they know is a valuable audience – high-income Apple users – while also making it easier for its customers to access what they need without leaving the walled garden.
That’s right, in Apple’s world, these ads for business help Apple customers engage within the ecosystem they love – and we all benefit. After you find a listing on Apple Maps you can always ask questions with Apple Business Chat and feel the integration with iMessage. Are you looking for reservations? OpenTable, for years, has had deep integration with Apple allowing you to reserve directly from the Maps app or by voice with Siri. Once you make it inside, pay with ease using Apple Pay – I love the ability to pay at a restaurant using a QR code.
Like many things, Apple is playing its cards slowly, but bit by bit its game plan to target small businesses is beginning to crystalize. If you’re finding the competition super steep on Social Media, Google, and other platforms it could be time to dip a toe into Apple’s unique model and try seeing who wants what you have in its ivory-colored walls.