SuperMarketers

If you are a High Growth B2B SaaS, SuperMarketers Is Your Done-For-You Demand Gen That You've Been Needing. 

Our primary goal is to boost your SaaS revenue effortlessly with our expert, done-for-you demand generation services—saving you stress and costs compared to running an in-house marketing team.

Book Your Free 45 Minute Strategy Session To Learn How To Use AI To Scale Your SaaS More Profitably and Efficiently: 

👉 https://tidycal.com/genfurukawa1/45-min-marketing-strategy-session-with-gen-furukawa

Founder

MarketerHire

Course Creator and Lead for MarketerHire's first AI course. 

The course is a 30 Day Intensive on Content & SEO, teaching marketing experts and freelancers in the MarketerHire community.

Marketer in Residence

Content at Scale

Joined Content at Scale as VP of Marketing to build brand awareness in the AI writing space. 

In my short time there: 
- Built Content at Scale's Prompt Library -- created 10k prompts to help entrepreneurs, marketers, business leaders learn how to use AI to accomplish their goals. 
- Helped launch a community for Content at Scale. Educated members on AI use cases for marketing with weekly workshops, webinars, and tutorials. 
- Recorded 14 podcast episodes on AI and Marketing with industry leaders like Brian Dean (Backlinko, Mike King (iPullRank), Travis Jamison (Investing.io).

VP Marketing

Prehook

I co-founded and sold Prehook, a quiz platform for Shopify merchants. 

Our goal was to build a software to help Shopify merchants learn more about their customers with quizzes. 

In just a few minutes, merchants could publish a quiz to ask a few questions, capture an email/SMS, and recommend a product. No coding required. 

Brands like Spikeball, Smile Direct Club, Evolve Skateboards, JOI, Teelixir, Camille Beckman and hundreds grew their audience, captured zero party data, and drove incremental revenue with Prehook's quizzes. 

Created thought leadership around ecommerce quizzes and zero party data in:
- our blog
- weekly newsletter
- podcast (CartOverflow.com)
- industry events (2x eCommerce, AdWorld, ProductLed Growth Summit)
- Guest on industry podcasts (eCommerce Fastlane, $100 MBA, eCommerce Badassery etc)

Co-Founder

CartOverflow.com (podcast)

Learning and sharing ecommerce marketing with smart people doing cool things. Weekly episodes with interesting guests (operators, agencies, service providers, SaaS folks) alongside co-host Jeremy Biron. episodes at www.cartoverflow.com

Co Host

Retainable

Retainable helps B2B companies reduce churn.

Boost your monthly recurring revenue, instantly. Retainable helps B2B software companies create a flywheel — increased retention; higher lifetime value; higher MRR. Email me if you have questions: gen@retainable.com

Jungle Scout

On the founding team and first marketing hire, helped lead growth of the company to over 100k customers. 

Working alongside CEO and executive team, I am responsible for the marketing strategy, recruiting/hiring, and execution of all Jungle Scout products. This includes Jungle Scout, Jump Send, Splitly, and Fetcher. These marketing efforts have helped establish Jungle Scout as the market leader for all Amazon seller software and educational resources. 

Particular focus on customer acquisition and retention. The primary marketing responsibilities include growth from SEO, content, paid, social, email, copywriting, conversion rate optimization, YouTube and more.

Helped lead Jungle Scout's international marketing strategy, particularly the growth in the Chinese market. This includes recruiting and hiring the first marketer focused solely on the Chinese market, and establishing the Go To Market strategy, junglescout.cn site, and helping to manage the growth of the team in China. These efforts have contributed significantly to Jungle Scout's Annual Recurring Revenue.

Vice President of Marketing

Amazon Product Research, Made Easy. 

Leading the digital marketing efforts for the industry-leader in Amazon product research, I focus on strategy and execution of: content, email, SEO, paid acquisition, analytics, split testing, conversion rate optimization, copywriting, and more.

Head Of Marketing

Fetcher.com

Growth

Splitly

Splitly is the only tool to help Amazon sellers maximize profits by running automated split tests.

Jump Send

Building a marketplace for the top Amazon Email Automation and Coupon Distribution Tool. I focus on helping sellers leverage email follow up campaigns to gather product reviews and improve conversion rates.

Done-For-You B2B SaaS Marketing | Founder @ SuperMarketers: Generate More Leads Effortlessly | Let Proven Experts Handle It All | Book A Call To Learn How 👇

Are you a SaaS leader looking to improve your marketing -- more high-quality, inbound leads at scale?  

SuperMarketers is a Done-For-You marketing agency that handles everything: Strategy, Execution, Marketing Ops, and Growth. 

We can do this more efficiently, and with greater impact, with our proprietary AI-driven marketing system. 

At a fraction of the cost of growing your in-house team or working with traditional agencies. 

I can do this because I've been in your shoes. 

I was a bootstrapped co-founder of an eCommerce SaaS, called Prehook. 

We sold in April 2023. 

It was a six figure sale. 

I know that it would have been a bigger outcome if I had the SuperMarketers growth system. 

I am deep in the AI and marketing space: 

I teach AI and marketing (for MarketerHire, a global network of top tier digital marketers). 

I podcast about AI and marketing (podcast is called SuperMarketers of course).

Helping write a book on AI and marketing (with Jon Nordmark, CEO of Iterate.ai).

And of course I help B2B SaaS brands grow profitably leveraging AI and automation--market leaders like Octane AI, Iterate.ai, Pipio.ai, and more.  

Previously I was part of the founding team and VP of Marketing at Jungle Scout, leading a team of 25 marketers through the $110M fund raise lead by Summit Partners. 

Book a 1 on 1 Strategy Call With Me To Learn Exactly How You Can Use Ai To Scale Your Marketing More Profitably and Efficiently, Without Spending Any Money. 

➡️ Book It Now: https://tidycal.com/genfurukawa1/45-min-marketing-strategy-session-with-gen-furukawa

🌷 Gen Furukawa

Ross Hudgens analyzed 200 websites to see what's working in search.

1️⃣ ChatGPT traffic is flattening. 

2️⃣ Google traffic is growing.

But the type of content that ranks has completely changed.

For most B2B companies, pipeline is steady or growing even if topline traffic is soft.

The shift is in what kind of content actually drives results, specifically: 

✅ Guides and playbooks still get the most traffic.
✅ Comparison pages are holding strong.
✅ Pricing and cost pages are performing well.
✅ Case studies saw a lift in engagement.
✅ Trend content is getting attention.

What's dying:
🟥 "How to" posts are losing visibility.
🟥 "What is" definitions are getting buried.
🟥 Anything that can be answered in a single snippet isn't getting clicks anymore.

If an LLM can summarize it in one sentence, users never hit your site.

Some suggestions that Ross suggests: 
1. Move resources toward bottom funnel. 
2. Build out pricing pages. 
3. Create detailed comparisons. 
4. Add interactive tools like calculators or templates. 
5. Refresh your case studies.

And if you're going top funnel, make it complex, like use visuals, embed video, add proprietary data. 

Just make it multimodal enough that it can't be compressed into a snippet.

The main takeaway is that search is definitely going away, simply the bar for content is just getting higher.

Done-For-You B2B SaaS Marketing | Founder @ SuperMarketers: Generate More Leads Effortlessly | 1x SaaS Founder & Exit | Book A Call To Learn How 👇

A lot of AI content still seems AI and robotic because people give the model way too much freedom.

AI writes by choosing the most predictable next phrase. 

This pattern creates the same rhythm, the structures, and the same “AI cadence” everyone can spot instantly.... (ie "it's not X, it's Y").

But if you tell the LLM to “sound human”, it is ineffective because the model simply picks more predictable language that fits that request.

So if you want the writing to feel human, you have to break the model’s probability loop.

You can start by forcing a specific voice instead of adjectives, ideally your own! 

Specifically named styles collapse the generic phrase pool and push the model out of autopilot.

Also, add oddly specific details that only a real person would mention.

Humans anchor to moments and specifics, while models default to generalities unless you pin them down.

Another tip is to create a running list of common phrases and structures that models lean on.

The goal is to eliminate the smooth, symmetrical phrasing that gives away AI-generated work.

In short, don’t ask the model to “be human.”

You give it constraints that make predictability impossible.

I’ve been rebuilding my content workflow inside Claude Code, and it’s already changing how I work.

I'm not technical, and kinda regret the initial apprehension about using a "coding" tool....ChatGPT and Claude are definitely sufficient to bridge that gap. 

The screenshot shows part of the system I’m building to turn raw transcripts into structured insight...it can be for a podcast, sales transcript, internal call, etc. 

The folders on the left are not code projects, but just steps in a system that turns raw thinking into structured content.

This is probably how we will all work in the near future, creating small agents to handle a specific part of the process. 

Using this repeatable logic saves time and creates consistency.

For example, one agent takes a podcast transcript and turns it into the things I actually need, like Title, description, time stamps, etc. 

Another agent applies the AEO lens. It looks at what parts of that transcript are extractable, highlights ideas that match the patterns LLMs tend to surface and the pieces that help a concept travel into AI search.

Another agent turns those insights into outlines and content plans. This is near automated and instantaneous, with better quality because the inputs are structured.

In short, Claude Code forces any repeatable task intoa workflow that runs the same way every time.

Still early, but this approach already produces clearer insights and cleaner AEO structure. It also gives me more confidence in the content I deliver for clients.

Google just dropped Gemini 3 and it finally understands the world the way we do.

It reads video, audio, images, movement, and text together as one coherent input.

It goes beyond pattern matching and actually reasons through what is happening in a clip.

You can upload any video and get a true breakdown of what is happening frame by frame.

I tested it by uploading a video of my basketball shot to see if it could analyze motion, timing, pace, and mechanics.

It gave me strengths, weaknesses, corrections, and a plan based only on a few short clips.

But if you want more helpful applications as a marketer: 

👉 You can upload your top ads and ask Gemini why they land, why others flop, and where creative fatigue is creeping in.

👉  You can upload competitor ads to get a precise breakdown of hooks, pacing, messaging gaps, and unique angles they are winning with.

👉  You can record your landing page and ask Gemini to identify friction points, confusing copy, layout issues, and missed opportunities.

👉  You can pair video with analytics and ask which frames or moments likely cause drop-off or bounce.

👉  You can upload sales call recordings and transcripts to surface objections, tone shifts, emotional cues, and coaching moments.

👉  You can upload a product demo from a competitor and get a structured comparison of positioning, missing claims, and angles you should counter.

This is the first time marketers can turn raw video into structured insights without manual review.

This is also a preview of how search and discovery will evolve as multimodal understanding becomes the default.

And yes, I have a long way to go to improve my basketball shot...when asked who my shot resembles, one name was Kevin Martin, historically one of the funkiest shots in league history 😂

I built a small AI agent this week that does something I used to do manually.

It watches what’s being posted on LinkedIn in a niche. 

It captures what gets engagement. 

Then it analyzes the post the way an LLM would. 

Topics, hooks, angle, and how the idea is structured.

The output lives in Airtable, so it’s not just “inspiration”, but actually queryable intelligence.

How it works: 
	•	Pulls posts from specific thought leaders in a topic area, for me that was AEO and AI marketing.
	•	Stores the original post link and basic context.
	•	Adds structured metadata so you can filter and learn patterns fast:
	•	topic cluster
	•	hook type
	•	content format
	•	angle
	•	engagement proxy

This "intelligence hub" is actually a way to build leverage too. 

I’m not a developer. The build is mostly just clarity on inputs and outputs.

The setup for this: 
	•	Apify collects the posts.
	•	Claude Code is the control layer. I describe what I want in natural language, and it generates the logic plus the structure.
	•	Airtable is memory. The hub gets smarter every time new posts land.

One underrated move: 

I asked Claude Code to design the Airtable schema first. It gave me the fields and field types. I pasted it into Airtable and the table was basically done in under a minute.

AI doesn't generate more net new content, but is used to replace: 
	•	manual research
	•	random ideation
	•	low-signal posting

With:
	•	a living dataset of what the market is rewarding
	•	repeatable patterns you can actually see and filter
	•	direction that compounds over time

Oh and also inside the agent, there is a sub-agent for things like:
	•	hook optimization
	•	voice consistency checks
	•	banned phrases and banned structures

That’s how you keep outputs on-brand instead of generic.

WHat other agents would be helpful to build out for marketers?

LLMs do not read your article in its entirety.

It slices it into small chunks and only keep the chunks that express a single idea with absolute clarity.

If a chunk is scattered, the model drops it. and conversely, if a chunk is clear, it becomes part of an answer.

Here are five simple ways to create content chunks that are valued by LLMs: 

- A definition.
- A set of steps.
- A comparison.
- A direct question and answer.
- A real example.

These formats survive chunking, get reused in answers, and scale your ideas without extra effort.

Long rambling paragraphs that feel smart but break into unusable pieces....this was my (cringey) writing style in college, seemed to make sense but is not valuable then, or now. 

Write in a way that makes your ideas easily extractable, for LLMs and your readers. 

One idea per chunk.
One chunk per format.
Five formats that consistently show up in AI answers.

That is the blueprint.

Google just made a quiet but important change to AI search.

When you search something in AI Mode, Google now includes WHY certain sources are relevant.... before it shows the links.

This is important and relevant because AI search is no longer just about ranking, or being mentioned or cited, but being explainable is now important. 

Google’s AI is literally telling users “Here’s why I trust these sources.”

Content that wins now is:
 • clearly scoped
 • structurally organized
 • explicit about the problem it solves
 • easy for an AI to summarize and justify

And generic content is harder to explain. Death to AI slop 😅 

So when creating content: 
- Write content AI can summarize in one sentence.
- Use definitions, steps, examples, and FAQs.
- Build content systems, not one-off posts.

Structure matters a lot for visibility in AI search, and this is one more step in that direction.

MarketingMentors is made up of a team of experienced marketeers that will guide you and help you strategise and excute the best marketing plan for your company. We run programmes that train you in all the aspects of marketing.

MarketingMentors

I’ve been testing Google’s new Gemini 3 model for a few days now, and it’s the first time I’ve looked at an AI tool and thought:

“OK, this can actually sit in the middle of a real marketing engine.”
Not as a gimmick. As infrastructure.

The interesting part isn’t just the model. It’s how Gemini + the wider Google 

AI stack fit together for day-to-day marketing work:

✅ Research – Deep research across web + your own docs, turned into a single “brain” for a product or launch.

✅ Strategy – Go-to-market plans, messaging, channels, budgets and KPIs drafted in hours, not weeks.

✅ Content & Creative – One strategy becomes blogs, landing pages, emails, social posts, ad copy, plus matching visuals.

✅ Security – Built on Google’s security stack, with admin controls and sensible guardrails (important if you work with client or customer data).

✅ Data & Dashboards – Your Sheets and exports become interactive dashboards with plain-English explanations.

✅ Search & Systems – Content structured around real questions so it actually has a chance in an AI-first search world.

The big shift for me:
🟠 Models will keep changing and getting obsolete.
🟠 Workflows and methodology will not.

So instead of asking “What can Gemini do?”, I’m asking:
🟠 How do we use it as an AI marketing strategist to build grounded GTM plans?
🟠 How do we use it as an AI data analyst to answer “Are we on track?” in a way a founder can act on?
🟠 How do we use it as an AI creative director + copywriter to keep output high but on-brand?
🟠 How do we use it as an AI builder to turn these into repeatable systems the team can run without me?

Attached is a 1-page “Google Gemini Guide to Transform Your Marketing” that shows, at a glance, how these pieces fit together and where it can plug into a real business, not just a demo environment.

...........................

Follow @Roisin for more helpful AI + Marketing Content!

Roisin Bennett

CEO, MarketingMentors | AI Strategist & Trainer | Helping SME’s simplify, implement and scale AI for business growth.

NotebookLM Just Got Its Biggest, 
Most Transformative Upgrade Yet! 🤯

Google's NotebookLM has moved from a simple note summariser to a powerhouse AI research and content studio, now offering a Studio UI and advanced discovery tools. These upgrades are a productivity game-changer for small businesses tackling strategy, research, teaching, and content creation.

👉 Advanced Research & Data Analysis

🔶 Deep Research Mode
Explore topics beyond simple answers, NotebookLM now autonomously analyses your sources, draws on public web data, and produces structured reports with citations, tables, and summaries. Perfect for untangling complex topics with dozens of sources.

🔶 Source Discovery & Integration
Find new sources via web search within NotebookLM and save hours. Seamlessly search and import from Google Drive—including Sheets, Word docs, PDFs, slides, and even handwritten notes or images.

🔶 Data Tables Artifacts
Automatically generate structured data tables so you can compare business metrics, valuations, or sales figures across sources—ideal for turning data into actionable insights.

👉 Visual Content Creation Studio

🔶 Mind Maps
Instantly organise ideas with interactive visual maps. A must-have for brainstorming or strategic planning.

🔶 Slide & Infographic Studio
Convert research into presentations or infographics in seconds. Choose formats optimised for LinkedIn or Instagram, tweak style or colour, and present data in an engaging way.

🔶 Video Overviews
Transform your notes or outlines into narrated slide summaries and explainer videos, pulling data and images straight from your sources.

👉 Hyper-Personalised Learning & Reporting

🔶 Adaptive AI Responses
Set your communication style and preference—brief, detailed, direct, or light-hearted. NotebookLM now adapts to deliver answers that fit your business needs.

🔶 Learning Guide Style & Custom Reports
The new mode prompts clarifying questions and lets you tailor reports for any topic, in 80+ languages, including blogs and client deliverables.

🔶 Flashcards, Quizzes & Audio Enhancements
Create flashcards and quizzes from materials in seconds. New audio overview formats now support multi-version creation for deeper analysis and learning on-the-go.

NotebookLM stays grounded, powered by Gemini 2.5 Flash, citing only your sources and eliminating AI hallucination for trusted, compliant decision-making.

I crafted the infographic below inside NotebookLM itself, proof the visual tools are already top-notch!

Ready to upgrade your workflow? Head to Studio in Google NotebookLM. It’s free to start!

Which feature will you try first - Deep Research or Infographics? 
Let’s chat in the comments! 👇

Business Owners: Make Your AI Work Like a Teammate, Not Just a Chatbot!

If you’re using AI for proposals, emails, reporting, or any kind of client comms, you’ll want to pay attention to the new GPT-5.2.

This is not just a smarter chatbot, it’s more like a reliable junior team member. One that follows instructions, doesn’t go off-script, and doesn’t need hand-holding. But to get that kind of performance, you need to prompt it like a manager, not just a casual user.

Here’s What You Need to Know (and Do Differently):

GPT-5.2 behaves very differently from older versions.
You get better results only when you stop using vague one-liners and start giving clear, structured instructions.

What’s new in GPT-5.2?
Much better at following instructions - fewer “drift” responses
Higher accuracy - less fluff, fewer hallucinations
Token efficient - solves problems in fewer words, which cuts cost
Great at multi-step work - like summarising contracts or analysing spreadsheets
More dependable for automation - works better inside workflows

Think of GPT-5.2 as your junior analyst, customer support agent, or content assistant. But it only shines when you give it a clear brief.

Here's how to prompt it properly:

👉Be Specific About Scope
Bad: “Help with my marketing.”
Good: “Write a 150-word LinkedIn post for UK small business owners about our new bookkeeping service. Friendly tone. One CTA.”

👉Dictate Length & Structure
Use phrases like “Give me 5 bullet points, one sentence each” or
 “1 short paragraph + 3 bullets: What changed, Risks, Next steps.”

👉Prevent Scope Creep
Add: “Only do what I asked. Don’t add extra features or sections.”

👉Add Guardrails for Sensitive Tasks
“Before answering, scan your response for unsupported numbers or bold claims, soften or flag as needed.”

OpenAI produced the official “cookbook-style” prompting guide for GPT‑5.2 which I have put in the comments.

Let me know how you're using GPT-5.2,  I’d love to hear what’s working for your business.

How to Prompt GPT 5.2

It’s easy to feel completely overwhelmed by AI right now. 

Every week, there's a new tool promising to solve all your marketing or operations problems, and for SMEs, that usually leads to more fragmentation and stress.

The fundamental mistake most businesses make is constantly asking the wrong question: "What is the best tool for X?". This focus on individual gadgets is why so many teams end up stuck in "Tool Chaos". 

We’re drowning in channels, fighting rising ad costs, and struggling because tools are everywhere but data is scattered and siloed. This leads directly to wasted time and burnout.

Last week, I presented our AI Implementation Strategy to a business group, using the deck "Beyond the Hype: Building Your AI Co-pilot". The core lesson is simple and critical: Random tools create random results, but a system creates growth.

The goal is to move from tool chaos to an AI Co-pilot. This means adopting a systemic approach. AI works best when it runs inside a clear process, not on top of chaos. This approach helps you reduce manual work, connect the dots between your tools, and make faster, better decisions.

We walked through how to define your processes and implement key components, differentiating between:

1. Custom Assistants: Smart chatbots trained on your content (PDFs, SOPs) that help you answer questions and draft content.
2. AI Agents: Workflows that go beyond answering to take action, like writing a reply, sending it, logging it in your CRM, and updating a pipeline.

The journey from random acts of AI to a cohesive system is the single most important investment you can make in your business’s future. We need to map the customer journey and decide precisely where AI drafts, where AI automates, and where human review is necessary.

P.S. I created this slide deck, along with the infographic and video overview (linked in the comments), in the new update in Google's NotebookLM. So impressed with the quality and speed of generation for structuring complex material!!

Building your AI Co-Pilot

Apparently, I’m “the AI Yoda of the Emerald Isle” and “the AI-Powered Oracle” now… and no, I didn’t come up with that myself - LinkedIn said it, Favikon confirmed it! 😅

I just got my Favikon Rewind, and honestly, it’s such a fun (and slightly eye-opening) way to look back at a year of content. If you haven’t heard of Favikon, it’s a tool that analyses your LinkedIn activity and gives you a breakdown of everything from your top posts to your best posting times, your rankings in different niches, and even your content “twin”.

It’s free, informative, and a little addictive!
Some highlights from mine:
🧠 Ranked #1 in Ireland for AI Education & Productivity
📈 Gained +10.1K new followers this year (thank you!)
📝 Wrote 133 posts with 34.7K words - clearly not short of opinions
✅ Apparently I really like the ✅ emoji (used 230 times!)
⏰ Best time to post? Monday at 8am - caffeine and carousels, anyone?

And I have to give a big shoutout to a few legends:
My top creator buddies: Charlie Hills and Pooja Jain - not surprised at all, I’m always checking in on your brilliant content.
My top fans : the one and only Charlie Hills, legends Maryrose Lyons, Khaled Elahmad - humbled, truly 🙏there’s definitely a mutual admiration club going on here 💚

And delighted to meet my content twin Chloé Einhorn - 84% match in AI Education & Productivity. Bonjour à toi, Chloé! 🇫🇷

Also loved this quote from my report (might get it framed 😉):
“Roisin, you're the guide we all need, cutting through the AI noise to show us what actually works. Your insights are so practical, you make us feel like we can actually use these tools to conquer the world!”

I’ll share details in the comments on how to get your own Favikon Rewind (yes, it’s free!) and how to make the most of it. You can also check your ranking under different categories, it’s really insightful and a bit of fun too.

Until then…
Grateful, I am.
 Keep creating, I will.
 
May the AI be with you. ✅
 -  AI Yoda of the Emerald Isle

Roisin Bennett Favikon Rewind 2025

Most brands are heading into their busiest ad period of the year still flying blind on which content and ads actually drive results. 

If you’re only looking at last-click ROAS and top-line engagement, you’re missing the levers that really move revenue.

We all want UGC and influencer content that not only looks good, but works, driving real engagement and conversions. 

But the gap between an average campaign and a standout one usually comes down to one thing: the brief. 

Too many creator briefs are still built on hunches, not on hard data. That used to be me too. 

My briefs were basically: “Highlight what you love” “Show how you use the product” “Stay authentic!” Creators were guessing. Performance was luck. 

The shift: from “Hope this works” to “We know this works” AI content intelligence tools like Aggero have completely changed how I brief creators. 

Instead of vague direction, I can now base briefs on what the data actually shows is working in my category and audience. 

👉 Here’s the new approach I’ve moved to: 

1. Turn insights into instructions Aggero analyses thousands of videos and comments to pinpoint the specific levers that lift or tank performance – words, hooks, formats, even vocal tone. So instead of “make it engaging”, I can say: 
•  “Open with a personal story about [X], not a generic intro.” 
•  “Show a genuine first reaction during unboxing – don’t script it.” 
•  “Shoot in a natural, optimistic setting – data links this to higher conversions.” 

2. Brief by data – not just demographics I’m no longer guessing at what will resonate. I can pull patterns like: 

•  Which audience segment is actually driving saves, shares and clicks 
•  Which topics, angles or pain points sparked 10–15% more engagement last time That goes straight into the brief so creators know who they’re really talking to and what should be front and centre. 

3. Bake in success drivers (and avoid drainers) 
Every brief now has clear DOs and DON’Ts: 

•  DO: Show a simple routine using the product in a real-life setting. 
•  DON’T: Overproduce it or lean on heavy jump cuts – those consistently suppress engagement. 

4. Make the data usable for creators No one wants to read a spreadsheet. I share a short summary from Aggero, pull out the key drivers/drainers, and turn them into a simple checklist and a few example prompts.
 
✅ The result 
Since taking this data-first approach to briefing: 

•  Engagement on UGC/influencer campaigns is up by 40%+ 
•  First drafts from creators are much closer to the mark 
•  There’s far less back-and-forth and much faster approvals Creators get clarity. 

Brands get predictability and better ROI. 
If you’re still relying on gut feel and generic guidance, now is the time to start baking content intelligence into every creator brief – especially in peak season. 

Use the data, brief better, and make influencer content a reliable growth channel.
Try Aggero's 7-day free trial here https://lnkd.in/eEY-bPpv

Is Gemini 3 really a big deal for business, or just another AI upgrade?

A lot of tools get launched with big promises and not a lot of follow-through.

So when Google announced Gemini 3, with people calling it “the best LLM in the world”, I wanted to know one thing:


 Is this actually different – and does it matter for small and mid-sized businesses?

Short answer: yes, it’s different.
And yes, it matters.

Gemini 3 is not “slightly better chat”

Most people will first meet Gemini 3 in the Gemini app or in Google Search and think:

“Oh, the answers sound a bit smarter.”

That’s the least interesting part.

The real shift is this:

✅ It can break problems into steps, plan, and stick to a process.
✅ It works across text, images, video, PDFs and code in one go.
✅ It’s being plugged directly into Search and Google Workspace (Gmail, Docs, Sheets, Meet).

In other words, it’s moving from “clever autocomplete” to an assistant that can actually help run parts of your business.

What can it actually do in a small business?

Here’s what this looks like in day-to-day work.

1. Operations & admin
2. Sales & marketing
3. Customer service
4. Finance & planning

👉 Why this is a real shift, not just a shinier model

The important bit is where Gemini 3 lives:

Inside tools you already use every day: Gmail, Docs, Sheets, Meet, Search.
Close to your real work – emails, documents, calls, spreadsheets – not just in a separate chat window.

That means you don’t have to “remember to use AI”.
It’s sitting in the sidebar, inside the search box, and behind the tools, quietly taking work off your plate.

👉 Where to start

If you’re a small business owner, I’d treat Gemini 3 like this:

1) Pick one painful process
2) Lead follow-up, proposals, support emails, or weekly reports.
3) Let it draft, you approve
4) Start with: “You draft, I review and send.”
5) Only automate further once you trust the output.
6) Measure hours saved

If it doesn’t save time or improve quality, change the workflow or turn it off.
Is Gemini 3 “the best LLM in the world”?

Maybe.
What matters more is this:

Used well, it becomes a quiet extra team member, 
helping you communicate faster, stay organised,
and run a calmer, more efficient business.

Gemini 3 the best LLM

ChatGPT just quietly became a team tool, not just a “talk to the bot on your own” tool.
Here's a quick visual guide on how to use ChatGPT Group Chats to supercharge a small team. 

What is ChatGPT Group Chat?
Think of it as a shared AI workspace for your team:
👉1 chat thread where everyone + ChatGPT can see the same messages and files
👉Up to a couple dozen people in one space (great for small businesses)
👉ChatGPT “listens in” to the whole conversation and helps everyone, not just the person who opened the chat
👉Instead of 5 people all prompting AI separately and pasting screenshots into Slack, you get one shared brain that sits in the middle of your project.

How to set up a Group Chat and simple use cases are explained in the Carousel.

How ChatGPT behaves in a group:
👉Inside a group, ChatGPT is more like a quiet assistant than a chatterbox:
👉It usually responds when someone @mentions it or when the answer is clearly useful
👉It can read and analyse files anyone uploads
👉It can create and comment on docs, plans, briefs and images

Privacy-wise: group chats don’t bleed into everyone’s private chats, and it doesn’t remember this forever – it’s mainly for “in the moment” work, not your long-term database.

If you run a small business and your team is already using ChatGPT individually, Group Chats are a simple next step: same tool, but now it works across the whole team.

Curious: would you use a Group Chat more for client work, internal projects, or training your team?

An aside 👉The infographic + slides you’re swiping through were built using NotebookLM’s new infographic and slides feature.

I literally dropped in a text document and it handled the layout:
- Clean, logical structure
- Slides ready for LinkedIn carousel or a team meeting
- Very intuitive to tweak, even if you’re not “design-y”
Honestly, it’s impressive how well it turned a dense text guide into something visual and easy to skim.

ChatGPT Group Chat Guide

OpenAI just dropped their new State of Enterprise AI report – and it basically confirms what a lot of us are seeing on the ground:

We’re past the “play with ChatGPT when you have time” phase.
AI is quietly becoming headcount.

A few numbers that jumped out at me 👇
800M+ people use ChatGPT every week.
In enterprises, weekly ChatGPT messages are up ~8× in a year and the average worker is sending 30% more messages.

Use of structured workflows (Projects, Custom GPTs, etc.) is up 19× - AI is moving from ad-hoc prompts to repeatable processes.
“Reasoning” usage is up ~320× meaning AI is being plugged into deeper decision-making, not just content drafting.

In other words:
Some companies still have AI sitting in a lonely browser tab.
Others now treat it like a cloud employee embedded across sales, support, ops, HR and finance.

Where it’s actually being used today:

* IT & engineering: faster incident resolution and quicker code delivery.
* Marketing & product: faster campaigns, content and experimentation.
* HR & people: better employee support, policy Q&A, onboarding and comms.
* Non-technical teams: big rise in coding-related requests from people who were never “technical” before.

Workers feel the shift too:
Most report 40–60 minutes saved per day, with heavy users saving 10+ hours a week.
~3 in 4 say they can now do tasks they couldn’t do before – not just do the same work faster.

The big warning in the report:
 We’re seeing a widening gap between “frontier” users and everyone else.
Frontier workers send ~6× more messages and lean much harder on advanced features.
Frontier companies show 2× deeper usage per seat and are weaving AI through far more workflows.
Same tools. Same models.
Completely different businesses in 12–24 months.

If your “AI strategy” is still a pilot, a press release, and a slide in the board deck, this report is a nudge:

The constraint is no longer the tech, it’s implementation and organisational readiness.
🔗 The link to the full State of Enterprise AI report in the comments.

If you’d like to unpack what this means for your team and map real AI workflows into your day-to-day operations (instead of one-off experiments) get in touch and we can walk through it together.

The State of Enterprise AI 2025

GPT-5.2 just dropped and this one actually matters for business

Most “big AI announcements” look impressive in demos… and then don’t change much about your working week.
GPT-5.2 is different, especially if your world is spreadsheets, reports, forecasts, client deliverables, or complex internal workflows.

Last week I was with a group of accountants who asked a very real question:
“Can AI actually build and update our models and reports properly or is it still just good for emails?”
With GPT-5.2, the answer is finally shifting toward yes.

What GPT-5.2 actually is:
OpenAI calls it their most capable model yet, designed specifically to excel at:
- Multi-step, complex reasoning
- Spreadsheets and structured data
- Presentations and long-form documents
- Coding, debugging, and automation

Major upgrades businesses will feel
1️⃣ Huge leap in reasoning
GPT-5.2 outperforms human experts on real 4–8 hour knowledge-work tasks.
2️⃣ Massive long-context window
You can now feed it:
- Entire project histories
- Multi-report financial packs
- Policies & procedures
- Long email threads
…and it remembers and tracks everything without losing the plot.
3️⃣ Spreadsheet intelligence you can trust
It can:
- Build and update multi-sheet models
- Cross-link tabs
- Write formulas
- Explain its logic
- Spot errors
4️⃣ Better coding & automation
Cleaner scripts, fewer hallucinations, more reliable debugging.
 Agent workflows just became far more practical..

💼 Practical use cases you can run today with GPT-5.2 (especially for accountants & SMEs)
📊 Monthly finance pack automation
- Upload CSV exports + last month’s reports.
- Ask GPT-5.2 to rebuild:
- P&L
- Cash flow
- Ratios
- Commentary
- Scenario planning
“Model what happens if revenue drops 15% and payroll increases 5% from March.”
It builds the model, you review the assumptions.
Turn complex spreadsheets into simple summaries:
“Explain this forecast to a non-financial founder in plain English.”
📂 Ops & admin automation
Extract key clauses from contracts/invoices
Turn long email threads into structured task lists
Populate sheets with key dates, amounts, dependencies
🔑 The real shift:
The gap is no longer access to the best model.
The gap is execution, who turns these models into repeatable workflows first.
If you’re curious where to begin:
Start with one process, your monthly reporting, quoting, forecasting, or client onboarding.
Plug GPT-5.2 into it.
Measure the time saved.
Then scale.
The businesses that operationalise AI fastest will pull away from the rest.

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