WEBVTT

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You might think that scaling up your marketing

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operation means one thing. More people. More

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people. More desks, more salaries. Right. A new

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strategist, an analyst, a dedicated creative

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lead. That's the legacy model. And we've found

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that the central idea from this guide on Google's

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AI stack just completely flips that on its head.

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The goal isn't more staff. The insight is this.

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You need four really defined AI functions, not

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four new human employees. that can systematically

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handle, what, like 80 % of your current marketing

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workload? Yeah, all the repetitive, time -consuming

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stuff just vanishes. We're calling them the four

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AI specialists. You have the AI marketing strategist,

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the AI data analyst, the AI creative director,

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and the AI builder. Welcome back to the Deep

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Dive. Today, we are immersing ourselves in this

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blueprint for a complete AI -powered marketing

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operation. We're not just here to talk about

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a single new feature. No, our mission is to give

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you the structure. I think we all need to stop

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that pattern of constantly chasing the shiny

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new thing, the latest model, you know, the newest

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minor update, and instead focus on building a

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stable fundamental methodology. The system. The

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system. The tools will evolve, but the system

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you build around them should last. And this shift

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is, uh... pretty profound. It moves the marketer's

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main job away from execution, making assets,

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running reports, to system design and strategic

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oversight. We're going to walk you through the

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workflows for these four functions. And this

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is the critical biting principle here. And this

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is always a collaboration. It is AI plus human.

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The AI handles that high volume, repetitive 80

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% of the work. Right. And that frees up the human

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marketer to focus on the high impact stuff, the

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strategy, the creativity, and the customer empathy

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that only they can provide. So let's jump in.

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Let's see how these functions, strategy, data,

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creative, and automation all integrate. Let's

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do it. So every good campaign starts with a solid

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strategy. But that strategy often requires this

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painstaking research that, well, it just yields

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disappointingly generic advice. Yeah. And the

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key methodology outlined here is pairing Gemini's

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incredible research capabilities with a really

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constrained synthesis tool. And that synthesis

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tool is Notebook LM. Right. Think of Notebook

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LM as a highly focused internal research assistant.

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So unlike a general search engine, it's strictly

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limited to the sources you give it. And this

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is where you get what they call grounding. And

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that grounding is what stops the generic outputs.

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So let's look at the source's five -step workflow

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for launching something complex like an online

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course platform. It starts with step one, deep

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research with Gemini. OK, so you start a session

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in Gemini and you engage the deep research mode.

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But here's the critical change. You incorporate

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your own proprietary sources. You upload your

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own files into that prompt. Like internal market

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reports. Yeah. Or maybe even analyses of past

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failures. Exactly. You ground the AI in your

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specific market reality, not just the open web.

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OK, so once that detailed report is generated,

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it's got competitive pricing, channel analysis,

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all that. Step two is simple. Just export it

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to a Google Doc. Yeah, that just cleans the data

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and gets it ready for the next phase. And step

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three is where the AI strategist really starts

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to shine, using Notebook LM. You import that

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Google Doc with all the research, plus maybe

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some external sources on industry trends. But

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there's a non -negotiable part here. The non

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-negotiable step. You must also import your own

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product overview or a detailed brief. Notebook

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LM's whole strength is that it's restricted only

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to the sources you manually feed it. Which makes

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a huge difference in the output. Because Notebook

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LM is only using those specific sources, step

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four, creating the strategy report, is inherently

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specific to you. Right. You prompt it to create

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report and you ask it to define positioning,

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pricing tiers, a detailed budget allocation,

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and a specific 90 -day execution plan. And you

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get a complete reality -checked plan, not some

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textbook template. Okay, so now you have the

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plan, you need to present it. And that's step

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five. You take that new strategy document, import

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it back into Notebook LM as your new source,

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and then you ask it to create a structured, professional

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15 slide outline. And then you take that outline,

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you shift over into canvas mode in Gemini, and

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you just paste the whole thing. You can add brand

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constraints, like a specific color palette, tone

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requirements, and ask it to generate the deck

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outline, ready for a direct export to Google

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Slides. It just compresses what used to be a

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week of planning and formatting into maybe an

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afternoon of synthesis. That ability to make

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sure the strategy recommendations aren't just

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generic internet advice seems essential. I mean,

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how critical is it to use our specific product

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details in Notebook LM? Oh, it's crucial because

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grounding the strategy in your reality dramatically

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reduces AI hallucination. Okay, so that's the

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strategies. Let's move to the analyst. A phenomenal

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strategy is, I mean, it's just expensive paper

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if you can't accurately and efficiently measure

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its success. Marketers are always drowning in

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fragmented data. Spreadsheets for budgets, APIs

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for campaign results, databases for customer

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lists. It's all over the place. Right. And the

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AI data analyst function is designed to connect

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all those dots. The source material here highlights

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a pretty big game changer for this function.

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Notebook LM can now import Google Sheets. Yes.

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This immediately enables this sophisticated...

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multi -source analysis where you know before

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you had to manually export and clean everything

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it's pure leverage so what does that look like

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in practice you upload your core strategy document

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right alongside your budget spreadsheet your

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campaign results data and your actual sales numbers

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This cross -reference capability lets the tool

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connect the plan directly to the real world,

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results in a way you can measure. It's like stacking

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Lego blocks of data and then asking the AI to

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build the instructions. Exactly. And it significantly

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reduces the risk of hallucination because the

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analysis is based entirely on your actual performance

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numbers, not some external model. So this unlocks

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some really practical analyses that used to take

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a human analyst days. For sure. Like you can

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now run a goal progress check against your...

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strategy targets. You upload the data and just

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ask. Based on the last four weeks of performance,

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which channel and content combinations are getting

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the lowest cost per acquisition according to

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the Q3 budget? Or, and this is even better for

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personalization, you could upload customer data

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and ask Notebook LM to identify the three highest

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value segments. Right. Not just based on spend,

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but based on their channel entry point and the

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content they consumed. You can find these really

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precise personalization opportunities. It just

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systematically digs through the numbers to answer

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your business questions. So we're using Notebook

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LM for that deep, grounded text and numerical

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analysis, the why behind the numbers. But you

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still need to visualize it for reporting. And

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that's the functional split. When you need charts

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and quick, professional visuals, you turn to

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Gemini. You just upload the clean data sets directly

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to Gemini. Yep. and ask it to create an interactive

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dashboard. Gemini is brilliant at the visualization

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part, generating these professional scatter plots,

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trend lines, bar charts, all formatted and ready

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to share. So we've covered the deep analysis,

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but beyond reports, what's the fastest way to

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get a visual overview of performance data? That's

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Gemini. Uploading datasets to Gemini yields immediate

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professional interactive dashboards. Okay, let's

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talk creative. Creative production is... notoriously

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the biggest bottleneck in any marketing team.

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It's often just endless revisions and a lack

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of consistency. Yeah. And the core concept here

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is that Google has launched this whole catalog

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of specialized tools and a good creative director

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knows exactly when to deploy each one. So let's

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slow down here because there are a few key cools

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to cover. Let's start at the conceptual phase.

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That's Mixboard. Think of Mixboard as your virtual

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generative whiteboard. It's really just for visual

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brainstorming, finding that initial campaign

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vibe. So you can drag and drop existing assets,

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ask it to blend them, or generate conceptual

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ideas like new packaging designs, or maybe a

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photorealistic hero shot of a product in some

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abstract setting. Right, but it's focused on

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concepts and mood, not the final production -ready

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asset. Okay. So once the concept is locked in,

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you move to another tool. You move to Wisk for

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the high -quality asset creation. This tool is

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built around blending three specific things.

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The subject, which is your product, the scene,

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the environment, and the style, so the aesthetic.

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It's designed for a really precise output. And

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Wisk solves that huge pain point for AI image

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generation, which is consistency. Totally. You

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can enable what's called precise reference to

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maintain a specific character or product packaging

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across multiple different shots, which is just

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revolutionary for brand campaigns. And it can

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also animate the static images for social content.

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Yeah, WISC can immediately animate that static

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image for use as dynamic social content. So now

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let's talk about consistency, which is where

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a lot of teams fail. And that's where Permeli

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comes in. And this seems fantastic for teams

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that don't have a lot of design resources. Permeli

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is all about automated consistency. It addresses

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that challenge by scanning your website URL.

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It just scans the URL. It scans the URL and extracts

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your entire brand DNA, your logo, specific colors,

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fonts, even the implied tone, and then generates

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ready -to -use social posts that are automatically

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compliant and on -brand. That's huge. I mean,

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nothing makes a brand look cheaper than inconsistent

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social posts that clearly came from, you know,

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five different template tools. This enforces

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guardrails at scale. For more standard, high

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-quality image generation, like a website banner

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or a newsletter header, you would probably start

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in Google AI Studio and use the latest Imogen

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model. Okay, and then the final frontier, Dedeo.

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Always the most resource -intensive task. So

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for that, there's Google Flow. Which uses the

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advanced video model, Vio. The suggested workflow

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is to create a specialized Gemini gem. Which,

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to define it simply, is just a saved, customized,

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and constrained set of instructions for Gemini.

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Exactly. You build that gem specifically to write

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these optimized, highly technical prompts for

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Vio. And the result is professional product videos,

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complete with optimized voiceover scripts. And

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what about copywriting consistency across all

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these new assets? The solution there is beautifully

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simple. A brand voice gem. You upload your existing

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brand guidelines, product details, customer testimonials

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into this specific gem. And then you use that

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constrained environment to generate all your

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ad copy and emails. Exactly. And it ensures everything

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generated sounds like it came from a single consistent

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brand voice. So if a team lacks dedicated design

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resources, which tool offers the fastest, most

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consistent branding? That's Pameli, because it

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automatically scans your website to create on

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-brand social posts. Okay, let's move to the

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fourth and final function, the AI builder. So

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we've planned the strategy, we've analyzed the

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data, and we've used the creative tools to produce

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assets. The final, and I'd argue most important,

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function is the AI builder. Their job is to take

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successful one -off processes and systemize them

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into repeatable internal apps for the whole organization.

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This is the move beyond just running prompts

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in a chat window. We're talking about architecture

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now, and the solution for this is Google Opal.

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Right. Opal is basically a no -code tool that's

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specifically designed for building these multi

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-step marketing workflows using Gemini. This

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tool ensures that your processes are standardized.

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And every workflow in Opal has three clear stages.

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User input, the generate steps where the AI works,

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and then a structured output. It forces a consistent

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methodology every time. The sources outline a

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fantastic example. a content strategy generator.

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The tool takes a keyword and a target audience

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as the user input. Then the generated sequence

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runs several steps. It researches top competitor

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content, identifies content gaps, and then outputs

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two key assets. An SEO optimized blog outline

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and a detailed social media visual prompt made

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through Imogen. And the final deliverable is

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a full content strategy document. This is efficiency

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at scale. Right. And I mean, I'll admit it. I

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still wrestle with prompt drift myself when I'm

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just in the simple Gemini chat interface for

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these really complex tasks. And that's exactly

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why systemizing these processes with a tool like

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Opal is so important for team scalability and

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consistent quality. That admission really speaks

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volumes. Opal ensures that every marketer on

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the team, regardless of their individual prompting

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skill, gets the same high quality output. And

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for more customer sophisticated needs, you'd...

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use Google AI Studio. You could build, say, a

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campaign brief generator that ingests a product

00:12:30.110 --> 00:12:32.370
photo, generates three unique launch concepts,

00:12:32.509 --> 00:12:35.509
and outputs a downloadable PDF pitch deck. And

00:12:35.509 --> 00:12:38.220
here's the real power. of the integrated google

00:12:38.220 --> 00:12:40.879
stack the infrastructure piece you can take those

00:12:40.879 --> 00:12:44.360
apps you created in ai studio and with one click

00:12:44.360 --> 00:12:47.279
deploy them across your entire organization via

00:12:47.279 --> 00:12:50.039
google cloud that's the architectural leap whoa

00:12:50.039 --> 00:12:53.019
i mean imagine scaling that single campaign brief

00:12:53.019 --> 00:12:56.019
generator tool across a global marketing team

00:12:56.019 --> 00:12:59.039
of hundreds every single market manager starts

00:12:59.039 --> 00:13:01.720
with a standardized on -brand brief it ensures

00:13:01.720 --> 00:13:05.019
global cohesion That level of centralized control

00:13:05.019 --> 00:13:08.220
is massive leverage. It's the definition of ultimate

00:13:08.220 --> 00:13:10.860
systematization for marketing operations. So

00:13:10.860 --> 00:13:12.940
what is the primary benefit of putting processes

00:13:12.940 --> 00:13:15.259
into Opal instead of just, you know, sharing

00:13:15.259 --> 00:13:17.659
good prompts in a document for the team? Opal

00:13:17.659 --> 00:13:20.240
creates reusable tools, ensuring consistent inputs

00:13:20.240 --> 00:13:22.539
and structured outputs for the whole team. So

00:13:22.539 --> 00:13:24.399
we've laid out the four critical AI functions,

00:13:24.659 --> 00:13:27.500
the strategist, the data analyst, the creative

00:13:27.500 --> 00:13:30.149
director, and the builder. Together, they form

00:13:30.149 --> 00:13:32.629
this integrated system that is lean, incredibly

00:13:32.629 --> 00:13:35.730
fast, and promotes a huge increase in your ability

00:13:35.730 --> 00:13:38.549
to experiment. And the crucial integration principle

00:13:38.549 --> 00:13:42.950
to remember is needs first, AI second. Don't

00:13:42.950 --> 00:13:45.269
force AI into a process just because the tool

00:13:45.269 --> 00:13:48.409
is available. Start by asking what process consumes

00:13:48.409 --> 00:13:51.649
the most human time? What task is the most repetitive?

00:13:52.379 --> 00:13:54.639
Address your biggest pain point with one function

00:13:54.639 --> 00:13:57.659
first, master it, and then add the others. Before

00:13:57.659 --> 00:14:00.080
we wrap up, let's just quickly revisit the critical

00:14:00.080 --> 00:14:02.320
mistakes the source material warns every team

00:14:02.320 --> 00:14:05.679
to avoid. Okay, top three pitfalls. First, feature

00:14:05.679 --> 00:14:08.740
chasing. Ignore the noise. Focus on your fundamental

00:14:08.740 --> 00:14:10.940
methodology, not the newest bell and whistle

00:14:10.940 --> 00:14:13.580
that just launched this week. Second, over -automation.

00:14:14.059 --> 00:14:16.360
Never automate tasks that require human judgment

00:14:16.360 --> 00:14:19.360
or empathy. Stick to that 80 -20 rule where AI

00:14:19.360 --> 00:14:21.860
handles the predictable tasks. And third, one

00:14:21.860 --> 00:14:24.419
that's often overlooked, ignoring brand consistency.

00:14:24.720 --> 00:14:26.840
You have to enforce those guidelines. Use your

00:14:26.840 --> 00:14:29.539
brand voice gem, use Pimeli, use precise references

00:14:29.539 --> 00:14:32.389
in WISC to maintain that cohesion. And we really

00:14:32.389 --> 00:14:34.230
have to reiterate the financial insight here.

00:14:34.330 --> 00:14:36.690
Almost everything we talked about, Gemini, Notebook

00:14:36.690 --> 00:14:40.610
LM, Mixboard, Pameli, is free or has a very generous

00:14:40.610 --> 00:14:44.070
free tier. And that cost dynamic offers massive

00:14:44.070 --> 00:14:46.470
savings compared to the old model of hiring an

00:14:46.470 --> 00:14:48.730
agency or full -time designers. That completely

00:14:48.730 --> 00:14:51.149
changes the cost -benefit analysis. Yeah. So

00:14:51.149 --> 00:14:54.549
what here is the fundamental change to the role

00:14:54.549 --> 00:14:56.690
of the marketer. You're moving from being a high

00:14:56.690 --> 00:14:59.970
volume executor and creator to a strategist,

00:14:59.990 --> 00:15:02.809
a director, and an architect of systems. Your

00:15:02.809 --> 00:15:05.370
value becomes the strategic thinking and the

00:15:05.370 --> 00:15:07.769
emotional intelligence that the AI can't replicate.

00:15:08.009 --> 00:15:11.049
The tools, the methodology, the ecosystem, it's

00:15:11.049 --> 00:15:13.990
all proven and ready. Google Stack provides everything

00:15:13.990 --> 00:15:16.610
you need to build this lean system today. So

00:15:16.610 --> 00:15:18.889
the question isn't if the AI marketing future...

00:15:19.159 --> 00:15:21.740
is here and functional, but really, will you

00:15:21.740 --> 00:15:23.759
build the system today? Reflect on your biggest

00:15:23.759 --> 00:15:25.879
operational bottleneck right now and just choose

00:15:25.879 --> 00:15:28.500
which of those four functions, strategist, analyst,

00:15:28.700 --> 00:15:30.700
creative, or builder, will address your most

00:15:30.700 --> 00:15:32.559
pressing problem. That's your starting point.

00:15:32.779 --> 00:15:35.240
Thank you for sharing your sources with us for

00:15:35.240 --> 00:15:37.759
this deep dive. We look forward to seeing the

00:15:37.759 --> 00:15:40.080
highly efficient systems you build. Until next

00:15:40.080 --> 00:15:40.379
time.
