A Prompt For Every Purpose: How to Tailor GenAI For Each Marketing Channel

More than half (57%) of advertisers now trust AI for tasks like ad investment and optimization, up from 33% in 2023. We’re past debating if AI is necessary. Now it’s about execution—how to actually use it well, across real workflows, in ways that unlock real insight.

Getting good at AI isn’t reserved for technical teams. It’s quickly becoming a baseline skill for marketers. Prompting is the control panel. It’s where you steer the machine. And if you’re not refining how you prompt, you’re not really using GenAI—you’re just watching it summarize.

AI also unlocks something we’ve never had at this scale before: frictionless hunch validation. Before, if testing an idea meant pulling data that took an hour—or even five minutes—you might skip it. But now? AI gives you the chance to move at the speed of your instinct. Computers don’t have intuition. But they can make yours a lot faster.

At Skai, we’ve spent time thinking through this shift while building Celeste, our AI marketing agent. In this post, we’ll look at how marketers should approach prompting through the channel lens, including some example prompts to help illustrate the point — Skai clients you can actually use these prompts in Celeste.

The key takeaway here is that getting better at prompting is now every marketer’s job. Better prompting comes from getting more specific—whether that’s by ad format, publisher, or channel as we’ll examine today.

You just can’t use the same prompts for every channel

Digital advertising’s top channels: paid search. retail media, and social advertising. They might all live under “performance marketing,” but the way they operate couldn’t be more different. If you feed GenAI the same prompt structure across each one, you’ll get the illusion of insight, but not the kind that helps you move.

Why do you need to prompt differently for them? Each channel sits in a different spot in the customer journey. Paid search captures demand that’s already formed. Retail media connects messaging to product availability and shelf dynamics. Social advertising shapes interest before customers are even sure what they’re looking for. A prompt that works in one place won’t translate neatly to the next.

The structure of the data shifts, too. Search deals in keywords and bid pressure. Retail is built on SKUs and inventory signals. Social revolves around formats, audiences, and creative cycles. GenAI won’t automatically understand which inputs matter most—unless you tell it.

That’s what prompting is: telling it where to look. If you’re vague, it’ll give you something clean but shallow. If you’re specific, it becomes a powerful collaborator. But specificity depends on understanding the channel.

Retail media: connecting retail dynamics to media performance

Retail media isn’t just media—it’s commerce. That means every campaign is influenced by the broader retail business: what’s in stock, what needs to move, what got negotiated in the JBP. If your prompt ignores that context and just focuses on ad dynamics, it’s going to miss the real story.

Think of retail media prompts not as reporting but as strategic business solutions. You’re not just asking “What performed well?”—you’re asking “What performed well, where, and why?” GenAI can surface those layers if you guide it with the right structure.

Prompt differently for each retailer

Retail media isn’t centralized. Each retailer has its own taxonomy, formats, optimization logic, and performance metrics. Treating them the same—whether in strategy or in prompting—guarantees insights that are too generic to act on.

GenAI can actually help bridge the gap—but only if you frame the prompt by platform. Ask for SKU performance by retailer, identify variances in ROAS or availability, and let AI surface where performance is falling apart or exceeding expectations due to retailer-specific conditions.

• Don’t: Ask for retail media insights without clarifying which retailer—lumping it all together flattens the signal. That’s fine for quarterly reports, but not for finding powerful nuggets of insight.
• Do: Prompt GenAI to break out performance by retailer and flag unique optimization or fulfillment challenges.
• Try this prompt in Celeste: Compare Walmart vs. Amazon performance across our top 25 SKUs—flag gaps in conversion, star ratings, and availability. Give two optimization recs per retailer.

Get granular at the SKU level

Campaign averages mask product-level truths. While search and social do deal with product-level feeds, they are at the core of retail media advertising. One SKU could be driving great performance while another bleeds budget, and prompts that focus only on campaign rollups won’t catch it.

Prompt GenAI to segment performance by product attributes. Ask it to flag underperformers by brand, price tier, or inventory status. That’s where real spend efficiency lives.

• Don’t: Rely on campaign-level summaries—they miss SKU-level waste and opportunity.
• Do: Prompt GenAI to analyze performance by product attributes and call out what’s dragging or overperforming.
• Try this prompt in Celeste: Show me SKUs with high spend and low ROAS that are currently in stock and rated 4 stars or higher.

Bring in business context

Retail media performance is rarely about media alone. It’s about business goals—hitting revenue targets, selling through surplus, or earning co-op dollars. GenAI won’t know what matters unless you prompt it accordingly.

Ask for summaries with those objectives in mind. This approach will help ensure that the information you receive is aligned with your specific needs and targets. Whether you’re prepping for a buyer call or reviewing a promotional flight, make the business goal part of the prompt. By including your business objectives in the discussion, you can guide the conversation towards outcomes that matter to your goals.

• Don’t: Prompt for a general performance recap if your actual goal is to prep for a JBP review.
• Do: Tell GenAI what the business objective is and ask for media insight in that context.
• Try this prompt in Celeste: Provide a performance summary for our Kroger Q2 media manager meeting—focus on revenue generators, ROAS profitability, and sell-through performance.

Tailor prompts by funnel stage

Retail media is full-funnel, but prompts often assume conversion is the only goal. That’s a miss. A display ad may not convert immediately, so it could show poor performance. However, it could build consideration and raise awareness of the brand among potential customers who may not have previously been engaged. This approach allows advertisers to create a more impactful presence in the consumer journey.

Guide GenAI to evaluate performance based on the placement’s role. Ask for top-of-funnel impact, not just bottom-line ROAS, as understanding the broader effects of a campaign can lead to more effective strategies in engaging audiences. By focusing on these metrics, businesses can better align their marketing efforts with their overall objectives and customer experience goals.

• Don’t: Judge every tactic on ROAS alone—it distorts what success actually looks like.
• Do: Prompt by funnel phase—ask for awareness impact separately from conversion data.
• Try this prompt in Celeste: What products had high engagement on top-of-funnel placements but low conversion—what’s holding them back in the last mile?

Blend retail and media metrics

Retail media isn’t just media. It’s retail too. You need iROAS, content score, availability, and pricing intel to understand what’s really happening. But GenAI won’t pull those signals together unless prompted to.

Give it a prompt that makes media metrics and retail conditions equal players. When both metrics and conditions are held to the same standard, it becomes easier to analyze their interactions. That’s how you spot where good ads failed for retail reasons, revealing insights that could lead to improved strategies in advertising and sales alignment.

• Don’t: Prompt GenAI for ROAS and leave it at that—it won’t catch inventory or content issues.
• Do: Ask it to correlate performance with retail health signals like availability or star ratings.
• Try this prompt in Celeste: List SKUs with low ROAS that also have low inventory or low ratings. Can you provide strategic recommendations on how to improve performance?.

Retail media is messy by nature. Your prompts should embrace that complexity, not simplify it away. The more context you give GenAI, the closer it gets to surfacing real, actionable recommendations.

Paid search: reacting fast to capture customer intent

Paid search is intent at its sharpest. Every query is a signal—and signals decay fast. This immediate responsiveness to user intent is what makes paid search such a crucial component of modern marketing strategies. If your prompts don’t reflect that speed and granularity, you’ll end up optimizing yesterday’s reality.

This channel rewards marketers who think in motion. GenAI can keep pace, but only if you teach it what momentum looks like. Learning to harness this dynamic approach requires not just awareness but also an adaptive mindset to pivot as needed. That starts with the prompt.

Don’t just prompt for keywords—prompt for patterns

Asking for top search terms will give you volume. But it won’t tell you what’s changing. Queries evolve constantly—especially after launches, promotions, or cultural events. Therefore, it’s essential to analyze trends over time to gain deeper insights into user behavior and preferences.

Prompt GenAI to group queries by behavior or customer stage. Ask what new modifiers are appearing. That’s how you stay ahead of what your customer is thinking, not just what they typed.

• Don’t: Pull a top 10 keyword report and call it insight.
• Do: Ask GenAI to analyze intent clusters, trend shifts, and phrase evolution.
• Try this prompt in Celeste: What new high-conversion modifiers have appeared in the last 14 days across branded search terms?

Prompt for funnel interplay, not just performance

Search is often where other channels cash in. If a social campaign worked, you’ll probably see it in branded queries. But GenAI won’t make that connection unless you lead it there. Ultimately, it’s crucial to strategically guide the algorithm to recognize these relationships and drive effective outcomes.

Use prompts to detect where search behavior aligns with other campaign timelines—and where that influence is missing. This analysis will help identify potential gaps in strategy and opportunities for better synergy across campaigns.

• Don’t: Treat search as a closed loop.
• Do: Use GenAI to find signs of lift from other channels or campaign echoes.
• Try this prompt in Celeste: As ad spend increased on TikTok campaigns over the past 14 days, did traffic on branded search queries across channels increase? Show performance by top keyword.

Spot volatility before it costs you

Search reacts in hours, not weeks. A shift in auction pressure or falling click-through rate can tank performance before your next report, highlighting the need for constant monitoring and quick adjustments to your campaigns.

Prompt GenAI to scan short-term fluctuations. Ask for hourly pacing gaps, CPC spikes, or SOV drops. Regular monitoring of these metrics will ensure you can make timely adjustments to your strategies. That’s how you stay out in front.

• Don’t: Wait for your dashboard to flag problems.
• Do: Prompt GenAI to act like a volatility sensor.
• Try this prompt in Celeste: Which non-brand campaigns have seen CTR drops or CPC spikes in the last 48 hours? Flag potential auction pressure.

Track how queries drift over time

Query sets aren’t fixed. People change how they search—even when they’re looking for the same thing. A new use case, a new feature, or a new competitor can shift phrasing fast. This fluidity in search behavior highlights the dynamic nature of user intent and demands a responsive approach to content strategy.

GenAI can detect early signals of this drift—if you ask for phrase change, not just keyword rank. This proactive approach enables users to adjust their strategies before the drift significantly impacts their content performance.

• Don’t: Assume your existing keyword coverage still matches current search behavior.
• Do: Ask GenAI to compare query phrasing over time and suggest additions.
• Try this prompt in Celeste: What emerging phrases or modifiers in category search are we not bidding on yet?

Use prompts to stress-test budget pacing

The biggest silent killer in paid search is poor pacing. Spend can run out before peak hours, or get wasted too early in the day. This often leads to missed opportunities for conversions during high-traffic periods. It’s a sin in SEM to overspend (who’s going to pay for that?), but also to underspend (how much money did we leave on the table?).

Use GenAI to analyze hourly spend trends, flag underperforming windows, and suggest bid or budget shifts by time segment. This data-driven approach enables more strategic decision-making and optimizes overall advertising performance.

• Don’t: Let daily budgets do all the decision-making.
• Do: Prompt GenAI to audit pacing and reallocation opportunities.
• Try this prompt in Celeste: Can you analyze daily budgets and provide strategic recommendations to avoid capping out on top revenue-driving campaigns?.

Search moves fast. Your prompts need to as well. Done right, GenAI becomes your pattern detector, pacing analyst, and intent translator—all at once.

Paid social: navigating creative trends and audience signals

Social isn’t built around demand. It’s built around behavior. That means prompting here has to account for context, emotion, and creative dynamics—otherwise you’ll get sterile insights about a living, breathing space.

The best prompts in social ask not just what worked, but why. GenAI can decode themes, compare formats, and surface fatigue—but only if you feed it the right ingredients.

Prompt for what resonated—not just what ran

Asking for “top ads” based on CTR won’t tell you anything new. Social success depends on tone, hook, pacing, and message. You need to prompt for the meaning behind the metric, as understanding these elements can provide deeper insights into audience engagement and overall effectiveness.

Ask GenAI what common elements drove response, then go deeper by segment. Look for patterns in save rates, comments, or watch time by format. Additionally, identify specific demographics or audience behaviors that may influence these patterns to gain a clearer understanding of engagement.

• Don’t: Settle for a ranked list of ads.
• Do: Ask for emotional drivers and creative structure insights.
• Try this prompt in Celeste: Can you analyze my social media engagement metrics and provide a summary of these results from the past 90 days? Can you break down the results by ad format and channel?

Be platform-specific, or get meaningless output

What works on TikTok won’t work in Instagram Stories. If your prompt lumps everything into “social,” GenAI can’t give you anything precise. Each platform has its own unique audience and engagement methods that dictate what content resonates best. 

Specify the platform and format. Then prompt for behavior patterns or creative differences by placement. Understanding these nuances is essential to tailoring your content effectively for each audience and platform.

• Don’t: Treat social like a single channel.
• Do: Give GenAI the context to analyze by platform and format.
• Try this prompt in Celeste: Compare engagement and drop-off between our TikTok ads and Instagram Stories—highlight pacing differences.

Prompt for early creative fatigue—not just end-of-life recaps

By the time your dashboard says an asset is fatigued, you’ve already paid the price. Prompt GenAI to catch fatigue patterns early—before results drop. By analyzing data trends in real-time, you can make data-driven decisions that optimize your advertising strategy. 

Ask for CTR decay, ad frequency thresholds, and engagement falloff trends. Understanding these metrics will help optimize our ad strategy for better performance.

• Don’t: Wait until performance drops to react.
• Do: Use GenAI to surface early warning signs.
• Try this prompt in Celeste: Which social media creative saw a 20% CTR drop after day 5 of delivery? Suggest refresh concepts based on current engagement patterns.

Use prompts to decode audience signals

Demographics aren’t enough. People behave differently across platforms and formats, and prompting should reflect that. Without understanding these nuances, strategies may miss the mark and fail to resonate with specific audiences.

Ask GenAI what kinds of hooks, visuals, or messages worked best for different audience clusters—not just age or gender. By analyzing these elements, we can create more tailored marketing approaches that genuinely engage each group and enhance overall effectiveness.

• Don’t: Rely on demographic performance summaries.
• Do: Prompt for behavioral segmentation by interest or engagement type.
• Try this prompt in Celeste: What messaging style is driving saves and shares among fitness-forward urban women aged 25–34 on TikTok?

Ask GenAI to connect engagement to action

Social performance doesn’t stop at likes; it encompasses a broader range of interactions that provide deeper insights into audience behavior. Prompt AI to tell you what happened after someone engaged—whether they clicked through, converted, or bounced, as this information can significantly enhance your understanding of user intent and preferences.

Use this to evaluate the quality of engagement, not just quantity, enabling you to tailor your strategies for better results and improved customer satisfaction.

• Don’t: Assume engagement = value.
• Do: Prompt for post-click or post-engagement outcomes.
• Try this prompt in Celeste: Which video creatives drove high engagement but had low CTR? Suggest adjustments to improve reach and click traffic

Social is creative-first and emotion-driven. Prompting here has to reflect that. When you ask the right questions, GenAI becomes less of a report generator and more of a strategist with a sharp eye for human behavior.

The marketers winning with AI aren’t asking better questions by accident

There’s no avoiding it: prompting is now part of the marketing toolkit. Not as a fringe skill, but as a daily habit. The marketers who get sharper here—who learn how to ask better questions, faster—aren’t just going to work more efficiently. They’re going to make better decisions.

And as this post shows, channel context matters more than most people realize. Retail media. Search. Social. Each one speaks its own language. Each one requires a different prompting instinct. What GenAI gives you depends entirely on what you feed it, and what you feed it should change based on the job that channel is doing.

One last thing: public AI tools are helpful. But when it comes to making high-value decisions with your own performance data, you need more than helpful. You need something purpose-built. If you’re curious what that looks like in practice, check out Public AI vs. Purpose-Built AI and Celeste. 

Because prompting better is only part of the story. 

Feeding it the right data? That’s the unlock.