One of search marketing’s SEO Rockstars recently shared his thoughts on SEO for generative AI, calling attention to facts about Google’s search results, explaining how the new AI search really works, and calling out fear-based marketing that overstates disruption in order to sell so-called “GEO” services.
Greg Boser is a search marketing pioneer with a deep level of experience that few in the industry can match or even begin to imagine.
His post was in response to a tweet by someone else that in his opinion overstated that SEO is losing dominance. Greg began his SEO rant by pointing out how some search marketer’s conception of SEO is outdated but they’re so new to SEO that they don’t realize it.
For example, the practice of buying links is one of the oldest tactics in SEO, so old that newcomers to SEO gave it a new name, PBN (private blog network), as if giving link buying a new name changes it somehow. And by the way, I’ve never seen a PBN that was private. The moment you put anything out on the web Google knows about it. If an automated spambot can find it in literally five minutes, Google probably already knows about it, too.
Greg wrote:
“If anyone out there wants to write their own “Everything you think you know is wrong. GEO is the way” article, just follow these simple steps:
1. Frame “SEO” as everything that was a thing between 2000 – 2006. Make sure to mention buying backlinks and stuffing keywords. And try and convince people the only KPI was rankings.”
The second part of his post calls attention to the fact that Google has not been a ten organic links search engine for a long time. Google providing answers isn’t new.
He posted:
“2. Frame the current state of things as if it all happened in the last 2 weeks. Do not under any circumstances mention any of the following things from the past 15 years:
2009 – Rich Snippets
2011 – Knowledge Graph (things not strings)
2013 – Hummingbird (Semantic understanding of conversational queries)
2014 – Featured Snippets – (direct answers at position “Zero”)
2015 – PPA Boxes (related questions anticipating follow-up questions)
2015 – RankBrain (machine learning to interpret ambiguous queries)
2019 – BERT (NLP to better understand context)
2021 – MUM (BERT on Steroids)
2023 – SGE (The birth of AIO)”
The next part is a reaction to the naive marketing schtick that tries to stir up fear about AI search in order to present themselves as the answer.
He wrote:
“3. Overstate the complexity to create a sense of fear and anxiety and then close with “Your only hope is to hire a GEO expert”
I think it’s reasonable to say that AI Search is complex because Google’s AI Mode and to a lesser extent AI Overviews, is showing links to a wider range of search intents than regular searches used to show. Even Google’s Rich Snippets were aligned to the search intent of the original search query.
That’s no longer the case with AIO and AI Mode search results. That’s the whole point about Query Fan-out (read about a patent that describes what Query Fan-out might be), that the original query is broken out into follow-up questions.
Greg Boser has a point though in a follow-up post where he said that the query fan-out technique is pretty similar to People Also Ask (PAA), Google’s just sticking it into the AI Mode results.
He wrote in a follow-up post about Query fan-out:
“Yeah the query fan thing is the rage of the day. It’s like PAA is getting memory holed.”
I agree with Greg to a certain extent that AI Mode is not a threat to SEO. The same principles about promoting your site, technical SEO and so on still apply. The big difference is that AI Mode is not directly answering the query but providing answers to the entire information journey. You can dismiss it as just PAA above the fold but that’s still a big deal because it complicates what you’re going to try to rank for.
Michael Bonfils, another old timer SEO recently observed that AI search is eliminating the beginning and middle part of the sales funnel, observing about AI search:
“This is, you know, we have a funnel, we all know which is the awareness consideration phase and the whole center and then finally the purchase stage. The consideration stage is the critical side of our funnel. We’re not getting the data. How are we going to get the data?”
So yeah, AI Search is different than anything we’ve seen before but, as Greg points out, it’s still SEO and adapting to change is has always been a part of it.
Read Greg Boser’s post on X:
If anyone out there wants to write their own “Everything you think you know is wrong. GEO is the way” article, just follow these simple steps:
1. Frame “SEO” as everything that was a thing between 2000 – 2006. Make sure to mention buying backlinks and stuffing keywords. And try… https://t.co/Eqy0spIj8B
— Greg Boser (@GregBoser) May 29, 2025
Featured Image by Shutterstock/Thomas Christoph
Today’s marketers spend sleepless nights puzzling over how much of their budget is lost along the mazelike programmatic supply chain, if they can trust CTV middlemen, or whether supposedly epoch-defining AI tools are in fact Mechanical Turks.
The disinfectant of sunlight, in theory, provides a means of resolving those concerns. But as more agencies put proprietary software tools and data platforms (like Havas Media Group’s Converged or WPP Media’s Open Intelligence) at the center of their appeal to new clients, agency execs are toying with the shades.
How much credibility can they gain from proximity to tech kingpins, when most marketing services groups work with the same big firms? How transparent should they be around vendor partnerships, their own commercial deals, and how they develop the tools giving them an edge? How much information is too much for marketers burdened with their own workload?
Let’s talk it out.
U.S. media agency Horizon is betting that clients want to know how the sausage gets made. It’s staging an open request for information (RFI) process as it considers the tech vendors required to develop the next phase of Blu, the agency’s proprietary data platform software.
Rather than hold its cards close while it plans and develops the platform, it’s gone public with the desire to add new vendors to the tech stack behind Blu.
Partially, that’s in the hope it’ll attract the best tech companies available, according to John Koenigsberg, the agency’s evp and head of product partnerships (he is also, in the spirit of transparency, the son of agency CEO Bill Koenigsberg). “The more open we are, the greater the likelihood that we’re gonna unearth matches or opportunities,” he said.
Koenigsberg said the company currently works with up to 15 vendors on the platform (the figure can vary depending on clients’ own vendor arrangements), including TransUnion and Snowflake. It’s expecting to double that number by the end of the RFI process, and has already heard from 175 companies.
There’s a secondary element, though — the hope that by building in the open, Horizon can attract clients that want a cutting-edge service. It’s not alone in that belief.
“Being open and upfront builds trust and it also gives clients a unique perspective that they can use [on] their own journey,” said Sander Stromph, global svp AI & change management at Monks.
The stance makes sense given the continued, constant presence of procurement teams — which are likely to assess an agency’s capabilities in more black-and-white terms than a CMO might — in agency reviews.
When WPP Media launched its new Open Intelligence platform this week, the company’s executives pointed to the pedigree of the tech and data partners involved in building it, from Google and Snap to Experian.
On Thursday (June 5), it released an announcement highlighting the publisher and ad tech partners involved with the platform, including Disney, PubMatic and The Trade Desk. Like Horizon, WPP Media designed its platform to operate with clients’ existing partners as well as its own.
“We aren’t incentivized to force you to consume a data asset and to buy through a specific platform in a black box, non-transparent, potentially poor quality way,” said InfoSum CEO Lauren Wetzel, one of the executives fronting Open Intelligence, in an interview with Digiday.
At the end of the day, clients come to agencies for help growing their sales. For many clients, how that growth happens is less important than the fact that it happens at all.
Transparency itself is a subjective term in an industry where there’s little common ground on measurement or meaningful KPIs. And in a global economy wracked with geopolitical uncertainty and when decision-making is being deliberately delayed, CMOs don’t have the time to scrutinize every minute detail. A little packaging or editorial judgement on the part of the agency isn’t unwelcome.
One area that has implications is agency pricing. Looking for a way to account for the time saved by the use of AI tools, Monks previously attempted to shift away from charging for its services based on hourly fees, providing clients with breakdowns of its own AI, data and labor costs (the company didn’t provide a specific cost example).
Based on client feedback, that approach had proven “too complex,” co-founder and chief AI officer Wesley ter Haar said, given the time it takes to calculate. “They’re really just buying the end products, and I don’t think they’re necessarily looking for that level of granularity,” he added.
Stromph also noted that the RFI process used by some clients only allowed for hourly-based pricing models, meaning Monks would have to calculate its price based on the old way to compete for new business.
Monks is now in the midst of reviewing that model and moving toward an output-based means of charging for its work.
Its experience holds lessons for marketers and agencies — that full transparency can lead to information overload.
Horizon’s “north star”, according to Koenigsberg is “how these technologies can help drive growth for our clients.” Given that, perhaps it’s better that agencies remove some of the details that can get under marketers’ feet.
Posters, logo designs, sculptures, drawings, video illustrations, apparel… we live in a time when an artist can do it all and more. One such artist is Lia Kantrowitz, a multitalented designer whose interest in design began with catharsis. “I started out just making personal work and that’s still a major portion of the work I put out, and is the main driver for techniques I’ve learned,” says Lia. “Drawing and making art is cathartic for me, and is less about the subject matter and more about a feeling I’m trying to evoke.” Lia’s style mutates wonderfully between flash tattoos and graphite renderings of barbed wires, dragons and tarantulas. One moment, her animations recall postcards from the wild west. In another, she evokes the vintage psychedelic imagery of Eiichi Yamamoto’s Belladonna Of Sadness.
Lia puts aside the grunge DIY aesthetic for something clean and collected with editorial designs that bloom in primary colours or monochromatic apparel works designed for screenprinting ease. Currently based in Queens, New York, there’s an urban element from Manhattan’s spunkiest borough that shines in Lia’s work, a punk earnestedness that gives it a lot of teeth. “I used to straddle both the hand drawn and digital realm, but in the past couple of years I’ve pivoted to mostly doing everything by hand,” says Lia. Feeling technological fatigue, Lia spends as much time as possible drawing, only using the computer to finalise work. “I want art and illustration to remain a therapeutic practice and working on my computer all the time feels antithetical to that.” With images as evocative as barking dogs, embracing swans and fairies playing giddy up, Lia is successful in allowing emotional stories to bleed out.
Every tweet, direct message, and comment holds weight. Social media has long been a connectivity platform, where users engage with friends, colleagues, and family.
In recent years, it’s also evolved to become a feedback mechanism for businesses.
In many industries, customers are communicating with a business on social media. It’s a key customer service channel, one in which savvy businesses must consistently monitor to ensure they’re meeting customers’ expectations.
In many cases, it’s the first place customers turn for help.
For brands, this shift presents a massive opportunity but also a real challenge.
Customers expect rapid responses. Research shows that 41% of consumers expect a response from a business within 24 hours. Plus, they’re not afraid to call out a business publicly if they don’t respond or effectively meet their needs.
Today, social media is no longer exclusively about amassing the most followers and likes. It’s about building genuine relationships with customers through timely responses, authentic engagement, and proactive customer service.
The Hootsuite Social Media Consumer Trends 2024 report found that 53% of social media users say the most appealing thing a brand can do on social media channels is to quickly respond to direct questions and comments.
In this post, we’ll explore how social media can be used as a strategic lever for building lasting customer relationships and how your business can implement social-first strategies that elevate both service and reputation.
When social media platforms like X (Twitter) and Facebook first launched, brands used them primarily as one-way communication channels.
They’d share promotions, advertise events, showcase new products, and announce pertinent updates.
However, over the last few years, this paradigm has completely flipped. Businesses are now using social media as a two-way communication channel, fostering deeper relationships with customers that turn into loyalty.
With feedback being front and center on social media, customers quickly realized they could get faster responses by mentioning a brand (@brand) rather than using traditional customer service channels, such as chatbots or phone calls.
In turn, businesses realized the importance of social media as a customer service channel, leveraging technology to reply to customer concerns at scale and ensuring timely follow-up.
Social media has become a natural extension of customer support. There are several factors that have contributed to the rise of social as a customer service tool, including:
Mobile accounts for over 62% of market share worldwide, with desktop falling behind at 36%.
Mobile phones are the go-to for browsing, shopping, and messaging. With smartphones now the default device, consumers will engage with brands on the go.
Whether it’s sending a direct message to an airline about a canceled flight or mentioning a retail brand on X (Twitter) seeking information about shipping status, customers are more comfortable than ever with connecting with businesses across all social platforms.
Given the convenient nature of mobile devices and mobile apps, social engagement has become more seamless and accessible than ever before.
Millennials and Gen Z are the dominant force in purchasing power. They’re also the two generations who have grown accustomed to digital-first experiences, including communication.
Both these generations grew up with mobile phones, the internet, and companies that deliver expedited experiences, like Amazon’s two-day shipping.
As such, they demand instant answers to their inquiries, just as they’d expect a friend to reply quickly to a text message.
Social media has evolved into a critical customer service tool, and the major platforms are stepping up to make communication easy.
For example, Facebook offers Messenger API integrations, and X (Twitter) supports customer service workflows.
On the other hand, Instagram allows for quick or automated replies, as well as live support features. TikTok is advancing its features to allow brands to address product questions or service complaints.
Customer service has followed the conversation, and those conversations have gone social.
Customer expectations continue to rise, and as they do, they’re reaching out for support from businesses in divergent formats, including across social media platforms.
Enter social customer care, which has quickly become a crucial endeavor and a need for every business.
Social customer care is growing smarter and more seamless, powered by automation, fueled by data, and defined by customer expectations for immediacy and personalization.
Let’s break down the trends driving this shift in social media customer service.
Consumers are widely adapting to artificial intelligence, engaging with it for streamlining tasks, seeking information, and contacting support.
AI chatbots have also come a long way from being basic autoresponders with a few canned responses.
Natural language processing (NLP) has become much more advanced, enabling AI to detect sentiment and context at deep levels to:
Be sure to pair AI chatbots with human agents (a.k.a. “agent assist”) to increase resolution speed, ensure human touch in feedback management, and maintain empathy when customers reach out for help.
Technology is getting smarter, and social media tools now integrate directly into customer relationship management systems, help desk software, marketing suites, and more.
This allows support teams to have quick access to order history, view past conversations, and personalize responses without asking for repeat information.
Sales, customer success, support, marketing, and customer experience no longer exist in siloes.
Together, they’re able to promote positive customer experiences across every touchpoint, whether a customer is seeking assistance during the awareness stage or needing help post-purchase through improved visibility.
Customers have become accustomed to receiving quick and seamless support.
Voice and video support offer attractive alternatives to traditional customer service options.
As technology continues to evolve and align with consumer behavior trends, short-form content has opened the door for new and unique types of customer service interactions.
For example, brands responding to customer questions with personalized videos to help walk through concerns or offer visual guidance.
Alternatively, support agents are also leveraging voice messages to talk through customer support, sending customers a short voice message in Instagram DMs or WhatsApp.
This eliminates the need for customers to pick up the phone and talk to an agent in real time, while offering more personal support.
Livestreaming has emerged as a powerful way for brands to build trust and transparency.
Platforms like Facebook Live, Instagram Live, YouTube Live, TikTok Live, and Twitch make it easy to connect with audiences in real time.
Whether hosting Q&A sessions or holding virtual “office hours,” livestreams allow brands to engage directly with customers and address questions on the spot.
These diverse customer support formats help humanize support and can enable faster resolution through rich media.
Social listening has emerged as a powerful ally for spotting issues immediately, allowing businesses to be proactive and swift when addressing consumers.
Social media support has evolved from tracking @mentions. Now, social listening tools empower brands to scan for brand mentions, product feedback, competitor and industry keywords, and more – even if the business isn’t tagged.
Smart brands tracking myriad feedback across social media platforms are able to then:
For example, a beauty brand may see numerous mentions about a leaky mascara tube on Instagram and Facebook.
Before it spirals any further and fuels negative brand perception, the brand could investigate the issue, fix it, and proactively respond to comments regarding the product defect and the steps they took to rectify it through the power of social listening.
Not all social responses are public.
“Dark social” is becoming a preferred communication method through platforms like WhatsApp, Messenger, and Telegram, as conversations are private and not broadcast for all to see, as is typically the case with social media conversations. Although, preference is regional and demographic-specific.
The “dark” nature of this communication allows for more personalized one-on-one conversations, which can be especially valuable in international markets, industries with sensitive queries (like financial services and healthcare), or any other industry where confidentiality is needed.
Just as with traditional customer service channels, social media customer care requires a nuanced approach to ensure satisfaction at every touch point.
A one-size-fits-all approach will no longer suffice. Smart businesses will evolve from reactionary to proactive support, irrespective of social media channels.
Feedback will be monitored across the diverse, fragmented social media landscape, where new content types are consistently introduced and new platforms emerge, eager to garner attention.
According to a recent study, engagements received on Facebook and Instagram continue to grow year-over-year, whilst engagements on X (Twitter) remain steady.
The study shows that customers are engaging across myriad social media channels.
Whether a customer mentions your brand on Twitter or your product on Facebook, equipping your customer service teams with the tools and technology to respond in near real time is a must.
A few best practices to implement into your social media customer service strategy include the following.
Consumers have grown accustomed to speedy responses. The Sprout Social Index™ shows nearly 75% of consumers expect a brand to reply within 24 hours or less.
Quick customer service is necessary, and customer expectations continue to grow.
While speed is critical, it can’t be at the cost of humanity. Aim for a first response to a customer within an hour or faster.
The use of pre-approved templates can be beneficial for common queries, but customization will be necessary for escalated issues where emotions can be heightened.
Be sure to acknowledge each issue with empathy and respond in your brand’s tone.
Customers are still not entirely eager to receive responses from AI. A Gartner study found that over half (64%) of customers would prefer that companies didn’t use AI in their customer service.
Sometimes, a tweet isn’t enough to squelch an issue.
When deeper issue resolution is needed, brands should keep public replies brief and take the conversation to a more private forum, such as DMs or email.
Brands must train agents to recognize when more personal support is warranted and needed, and how to make the transition to a private conversation more seamless to mitigate customer frustration.
Customers may feel better served knowing they’re engaging with a member of the support team.
To help users distinguish your business from your support staff, it can be beneficial to have a separate dedicated support handle, such as @NikeService vs. @Nike.
A dedicated support handle can reduce confusion, make users feel heard, and ensure support requests aren’t lost in the void.
Consider a customer who has reached out for support in the past via Facebook due to a high-ticket product defect.
Your brand rectified the issue by providing the customer with a new part and a partial refund. Now, consider the product experiences further issues in the future, and the customer reaches out again.
They may start to feel like just a number if the second support agent isn’t equipped with the customer’s full product history and was never made aware of the previous product issue.
This, in turn, creates a negative brand experience, which can lead to a bad review and the loss of a customer.
Smart brands give their social media customer service representatives the tools and resources to access customer history to avoid potential pitfalls like the scenario mentioned above.
Empowering your frontline employees not only helps your customers but also your business’s brand reputation.
Customers want to feel seen and heard, irrespective of where they’re reaching out to you. Check in with your customers after their issues have been resolved.
Customer follow-up surveys are a great tool to employ post-service to assess how your customer service team is doing.
Whether a customer reached out to your business via Instagram DM or a chatbot on your website, it’s important to ensure customers know they matter to your business.
Customer support managers should track key performance indicators (KPIs) consistently to accurately assess employee performance and keep a pulse on customer satisfaction.
A few common KPIs businesses will want to measure are:
By measuring what matters most, businesses can pinpoint critical issues before they become widespread.
For example, if customers continue to voice concerns over short battery life in a toothbrush on TikTok, the business can flag this for its product team, look further into whether it’s a smaller issue that impacted a batch of shipments, or assess if a bigger quality assurance issue is at play.
Using social media as a customer service tool is non-negotiable.
The social media landscape is no longer just a forum for fun. It’s evolved to the point where customers are actively seeking support and voicing their concerns for the wider public to see.
It’s a service battlefield, where brands either win or lose customer loyalty.
Social media has to be a core support channel, not just a nice-to-periodically check.
When your social support mirrors your online support, brands will differentiate themselves from the businesses that aren’t responding with speed and empathy.
Moving forward, the first step you can take is to audit your social media support today.
Ask yourself: Is your business meeting response time expectations? Is your team equipped with the best tools to enable smooth support? And how will your business escalate issues when they arise?
The brands that will thrive in the long run are those building systems for service, not just likes, today.
More Resources:
Featured Image: Accogliente Design/Shutterstock
The very public feud between President Donald Trump and Elon Musk made headlines and brought viewers to the cable news networks. CNN and MSNBC saw increased numbers compared to a typical evening, but Fox News’ The Five remained the top show and the only program with more than 3 million total viewers. CNN’s Anderson Cooper 360 landed in first place for the network, while The Last Word with Lawrence O’Donnell had the most total viewers for MSNBC.
25-54 Demographic (Live+SD x 1,000)
Total Day: FNC: 179 | CNN: 78 | MSNBC: 66
Prime: FNC: 292 | CNN: 117 | MSNBC: 105
FNC: CNN: MSNBC: 4PM Cain:
194 Hunt:
134 Wallace:
114 5PM Five:
314 Tapper:
125 Wallace:
108 6PM Special Report:
271 Tapper:
160 Melber:
96 7PM Ingraham:
289 Burnett:
136 Weeknight:
104 8PM Watters:
355 Cooper:
124 Hayes:
101 9PM Hannity:
238 Collins:
117 Psaki:
95 10PM Gutfeld!:
283 Phillip:
109 O’Donnell:
120 11PM Gallgher:
186 Coates:
75 Ruhle:
93
Total Viewers (Live+SD x 1,000)
Total Day: FNC: 1.610 | CNN: 414 | MSNBC: 706
Prime: FNC: 2.758 | CNN: 669 | MSNBC: 1.298
FNC: CNN: MSNBC: 4PM Cain:
1.746 Hunt:
623 Wallace:
1.111 5PM Five:
3.279 Tapper:
640 Wallace:
1.188 6PM Special Report:
2.493 Tapper:
577 Melber:
1.203 7PM Ingraham:
2.441 Burnett:
714 Weeknight:
992 8PM Watters:
2.976 Cooper:
776 Hayes:
1.190 9PM Hannity:
2.476 Collins:
647 Psaki:
1.218 10PM Gutfeld!:
2.820 Phillip:
583 O’Donnell:
1.486 11PM Gallagher:
1.404 Coates:
327 Ruhle:
967
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With the new Nintendo console released (see our Switch 2 unboxing), you would expect the Nintendo Switch 2 Welcome Tour to be a packed-in title showcasing new features. And yet, there’s the rather unwelcome fact that you’re charged for what could be described as an interactive instruction manual.
But with its predecessor on track to be Nintendo’s best-selling console of all time and the Switch 2 already flying off shelves while bringing back the midnight console launch, the Kyoto company hardly needs to give anything away for people to buy in.
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Google updated the Recipe Schema.org structured data documentation to reflect more precise guidance on what the image structured data property affects and where to find additional information about ranking recipe images in the regular organic search results.
The SEO and publisher community refers to the text results as the organic search results or the ten blue links. Google refers to them as the text results.
Structured data helps a site’s content become eligible to rank in Google’s rich results but it generally doesn’t help content rank better in the text results.
That’s the concept underlying Google’s update to the Recipe structured data guidance with the addition of two sentences:
“Specifying the image property in Recipe markup has no impact on the image chosen for a text result image. To optimize for a text result image, follow the image SEO best practices.”
Recipe structured data influences the images shown in the Recipe Rich Results. The structured data does not influence the image rankings in the regular text results (aka the organic search results).
Google offers documentation for image best practices which specify normal HTML like the and elements. Google also recommends using an image sitemap, a sitemap that’s specifically for images.
Something to pay particular attention to is to not use images that have blurry qualities to them. Always use sharp images to give your images the best chance for showing up in the search results.
I know that some images may contain slight purposeful blurring for optimization purposes (blurring decreases image size) and to enhance the perspective of foreground and background. But Google recommends using sharp images and to avoid blurring in images. Google doesn’t say it’s an image ranking factor, but it does make that recommendation.
Here’s what Google’s image optimization guidance recommends:
“High-quality photos appeal to users more than blurry, unclear images. Also, sharp images are more appealing to users in the result thumbnail and can increase the likelihood of getting traffic from users.”
In my opinion I think it’s best to avoid excessive use of blurring. I only have my own anecdotal experience with purposely blurred images not showing up in the search results. So, to me it’s interesting to see my experience confirmed that Google treats blurred images as a negative quality and sharp images as a positive quality.
Read Google’s updated Recipe structured data documentation about images here:
https://developers.google.com/search/docs/appearance/structured-data/recipe#image
Read more about images in Google’s text results here.
Read about blurry and sharp images here:
Featured Image by Shutterstock/Dean Drobot
The announcement on Wednesday that HubSpot built a deep research connector to ChatGPT generated a lot of excitement among HubSpot users and martech observers, but there is some cause for concern around data security.
A number of online voices are claiming this is a paradigm shift for SaaS applications and AI.
But opening access to customer data to any technology can be a little scary. When it’s an AI company like OpenAI, the creator of ChatGPT, it gets even more scary. LLMs like ChatGPT need to train on data.
To assuage those concerns, HubSpot specifically stated in its press release announcing the product that ChatGPT could not use the data for training purposes. HubSpot is a public company, and as such, does not include throw-away lines in its press releases. It meant it.
Still, doing just about anything with customer data carries risk. Corporate legal and financial departments exist to mitigate risk, so whether you can use this connector and to what extent is going to depend on your organization’s appetite for risk. Many companies have policies in place about sharing customer data with apps. They should be followed.
Beyond the risk and compliance issues, the old saying “garbage in, garbage out” still applies. How clean is the data in your CRM? How well will ChatGPT be able to understand it?
Dig deeper: Why AI-powered customer engagement projects fail before they start
Through the series, Dexter also explores an alternative reality – one where he hadn’t moved to Britain as a child. “I always heard about School of Hope because if I wasn’t in the UK, I would be attending the same school,” Dexter explains. The school was enthusiastic about the project, Dexter recalls, and he took the opportunity to highlight the influence of the teachers and assistants who ran both of the schools, as well as their pupils. “I also went to a place called Chester Village around ten times,” he adds, “I loved that place; they had 21 homes, and each home was fitted with a disabled room.”
Once on location, Dexter, as per his practice, doesn’t shoot straight away; instead, he sits and speaks to his subjects. “I wanted the people to trust me, so I could get a true picture of what they have been through in Jamaica,” Dexter says. “I also interviewed some of the older people to get a true understanding of what they have been through.” As such, there is a thorough sense of understanding throughout every image, alongside an attentive and kind eye.
In each portrait, experience and subtlety intermingle to forge an understated yet powerful series, sensitive to its subjects and audience without diminishing their characters. Far from it, in fact. The series ultimately celebrates the figures of Jamaican society that, as Dexter suggests, have long gone without a voice of their own. One voice in particular that stood out to Dexter was Sylvia Grant, the person who first brought him to Chester Village. “Her picture stands out to me the most because I know the trials she has faced,” Dexter ends, “she is a five-time Paralympian, a strong person and a real motivator.”
BrightEdge Enterprise SEO platform released new data showing distinctive patterns across major AI search and chatbot platforms and also called attention to potential disruption from Apple if it breaks with Google as the default search engine in Safari.
One of the key findings in the BrightEdge data is that traffic to websites from AI chatbots and search engines is highest from desktop users. The exception is Google Search which is reported to send more traffic from mobile devices over desktop.
The report notes that 94% of the traffic from ChatGPT originates from desktop apps with just 6% of referrals coming from mobile apps. BrightEdge speculates that the reason why there’s less mobile traffic is because ChatGPT’s mobile app shows an in-app preview, requiring a user to execute a second click to navigate to an external site. This creates a referral bottleneck that doesn’t exist on the desktop.
But that doesn’t explain why Perplexity, Bing, and Google Gemini also show similar levels of desktop traffic dominance. Could it be a contextual difference where users on desktop are using AI for business and mobile use is less casual? The fact that Google Search sends more mobile referral traffic than desktop could suggest a contextual reason for the disparity in mobile traffic from AI search and chatbots.
BrightEdge shared their insights:
“While Google maintains an overwhelming market share in overall search (89%) and an even stronger position on mobile (93%), its dominance is particularly crucial in mobile web search. BrightEdge data indicates that Apple phones alone account for 57% of Google’s mobile traffic to US and European brand websites. But with Safari being the default for around a billion users, any change to that default could reallocate countless search queries overnight.
Apple’s vendor-agnostic Apple Intelligence also suggests opportunities for seismic shifts in web search. While generative AI tools have surged in popularity through apps on IOS, mobile web search—where the majority of search still occurs—remains largely controlled by Google via Safari defaults. This makes Apple’s control of Safari the most valuable real estate in the mobile search landscape.”
Here are the traffic referral statistics provided by BrightEdge:
With Apple’s Worldwide Developers Conference (WWDC) nearing, one of the changes that many will be alert to is any announcement relative to the company’s Safari browser which controls the default search settings on nearly a billion devices. A change in search provider in Safari could initiate dramatic changes to who the new winners and losers are in web search.
Perplexity asserts that the outcome of changes to Safari browser defaults may impact search marketing calculations for the following reasons:
“58% of Google’s mobile traffic to brand websites comes from iPhones
Safari remains the default browser for nearly a billion users
Apple has not yet embedded AI-powered search into its mobile web stack”
BrightEdge data shows that desktop usage is the dominant source of traffic referrals from AI-powered search tools like ChatGPT, Perplexity, Bing, and Gemini, with Google Search as the only major platform that sends more traffic via mobile.
This pattern could suggest a behavioral split between desktop users, who may be performing work-related or research-heavy tasks, and mobile users, who may be browsing more casually. BrightEdge also points to a bottleneck built into the ChatGPT app that creates a one-click barrier to mobile traffic referrals.
BrightEdge’s data further cites Apple’s control over Safari, which is installed on nearly a billion devices, as a potential disruptor due to a possible change in the default search engine away from Google. Such a shift could significantly alter mobile search traffic patterns.
Read more at BrightEdge
The Open Frontier of Mobile AI Search
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