7 Steps to Unlock Quality Social Performance with AI
Cheryl Ingle · July 25, 2025
content marketingai in marketingsocial media marketing
In this session, David and Cheryl explore how AI is transforming social media marketing by outlining a seven‐step framework to improve content quality and performance. They discuss platform changes, leveraging built-in AI tools, adopting a performance-first mindset, monitoring sentiment, automating routine tasks, personalizing creative content, and blending AI with human insight to drive ROI.
0:05 – David:
Hello and welcome to another edition of AI Insiders. I'm David Burkowitz, and although my AI-powered specs aren’t used for this call, I’m excited to have guests from South Africa with us today—especially Cheryl Ingle—to discuss where AI fits within social and content marketing.
1:09 – David:
Cheryl, it’s great to have you. I recently met your colleague in New York and have already learned a lot from your team. For those who are new here, we love these interactive community conversations and look forward to hearing everyone’s thoughts. Please feel free to interrupt if you have any specific questions.
1:25 – Cheryl:
Great to be here. I’m excited to share my experience in social marketing, especially how we’ve used AI to enhance performance.
2:09 – Cheryl:
Today, we’ll discuss using the power of AI to drive results in social media marketing. We’ll explore how platforms like Meta use AI for everything from algorithms to ad development, and how marketers can use it to improve content performance and overall efficiency. By the end of the session, you’ll have seven clear steps for leveraging AI’s strengths without losing the human touch.
3:15 – Cheryl:
Social has changed dramatically. AI now runs the social ecosystem, controlling what content is seen based on engagement signals. It’s not about posting frequently anymore; rather, visibility is determined by how much users interact with your content.
4:18 – Cheryl:
Content delivery has evolved. AI isn’t just changing the amount of content produced but is also influencing the rules for standing out. Today, relevance matters more than quantity because every post competes with a flood of AI-generated content.
5:25 – Cheryl:
The battleground is now quality and relevance. With so many creators—both human and bot—producing content, audiences quickly scroll past anything that doesn’t connect. Platforms reward posts that quickly generate strong engagement rather than merely filling the feed.
6:20 – Cheryl:
Platforms now reward content that engages users fast. Engagement isn’t just about likes; it includes comments, shares, click-throughs, and even the amount of time a post is viewed. Posting just for the sake of quantity can even lead to penalties.
7:24 – Cheryl:
Earlier, social platforms used simple criteria such as recency and engagement to sort content. For example, Facebook’s old EdgeRank algorithm relied on relevance, recency, engagement, and post type. Since 2015, it has shifted to a machine-learning model that now considers over 10,000 factors.
8:30 – Cheryl:
What we see today is data overload. Every piece of data is used to predict content relevance and personalize each user’s feed. What used to be a straightforward formula has become complex, so we must work with the algorithm to perform well on social.
9:28 – Cheryl:
Relevancy is key. The system collects your engagement data, filters it through prediction models, and ranks posts by what it thinks you’ll find valuable. Your feed becomes highly personalized through continuous feedback loops.
10:31 – Cheryl:
Although posting is easy, cutting through the noise is challenging. AI has shifted us from a world of scarcity to one of abundant content, making attention the scarcest resource. The goal is to remain relevant so your post isn’t skipped by the algorithm.
11:32 – Cheryl:
Our response to this change is to let platforms do the heavy lifting. AI is now deeply embedded in platforms like Meta, TikTok, and LinkedIn to optimize content. Instead of manually tweaking every detail, you set the rules and let the machine optimize on your behalf.
12:37 – Cheryl:
For example, content optimization now includes predictive targeting that expands your audience based on behavior, along with smart bidding that adjusts budgets in real time. Objective-based delivery optimizes campaigns for your specific goals using continuous feedback.
13:36 – Cheryl:
Regarding platforms, TikTok’s algorithm is far superior in certain areas compared to Meta’s. TikTok monitors where you linger, what you share, and how long you watch, making it very effective at keeping users engaged. Meta is now working to replicate that level of sophistication.
14:37 – Cheryl (answering a question):
Regarding engagement, all platforms measure interactions—comments, shares, likes, video views, and replay frequency—but they weight these signals differently. For instance, a like may be more valuable on Instagram while view duration is critical on TikTok.
15:41 – Cheryl:
Beyond smart bidding, we now have objective-based delivery and native creative assistance built into platforms. These features automatically test creative variations and rotate dynamic creatives based on performance, ensuring the right message is shown to the right audience.
16:43 – Cheryl:
Platform-level creative rotation means that even if you upload multiple creative options, the system dynamically decides who sees which version based on past interactions. This level of automation is relatively new with AI advancements.
17:44 – Cheryl:
Essentially, all the content you see on social is powered by AI through predictive models and real-time data analysis. The key is to provide strong inputs so the machine can perform optimally—think of it as “build better inputs and let the machine do the rest.”
18:42 – Cheryl:
In practice, educating AI properly results in better targeting and ultimately improved conversion rates. Tools like Meta Advantage Plus (or TikTok’s Smart Creative) have shown up to a 32% improvement in cost per purchase by continuously optimizing campaigns.
19:48 – Cheryl:
This leads us to step three: adopting a performance-first mindset. It’s about using AI not only for automation or efficiency but as a driver of performance. Educate the system so it optimizes targeting and creative delivery, ensuring your marketing budget is spent effectively.
20:51 – Cheryl:
When optimized correctly, AI finds high-intent users and scales high-performing ads automatically. Real-time campaign adjustments—be it targeting, bidding, or creative rotation—mean you spend less on underperforming campaigns and focus on what converts.
21:54 – Cheryl:
In other words, performance matters. Instead of manually adjusting budgets, let AI reallocate funds to better-performing ads, improving bottom-line outcomes through efficient targeting and dynamic optimization.
22:54 – Cheryl:
Using AI in practice through tools like Advantage Plus has proven that campaigns optimized by AI can see significant improvements, such as a 32% reduction in cost per purchase. This demonstrates how performance-driven adjustments reduce wasted spend.
23:57 – Audience Question (paraphrased):
What are the implications of A/B testing when algorithms automatically optimize campaigns?
23:57 – Cheryl:
A/B testing still has value when testing distinctly different approaches. I recommend running controlled tests for creatives or strategies that vary significantly, then using dynamic creative tools to optimize based on those findings. It’s all about learning what works best.
24:54 – Lisa (audience comment):
I see AI making advertising easier, yet some clients report declining ROI and less loyal customers from social ads. Are you noticing that as well?
25:55 – Cheryl:
Social has become more competitive due to the overload of content. Sometimes, even with AI optimization, results vary by industry. For clients facing this challenge, I often suggest reducing spend on paid social and focusing more on organic or owned channels. It really depends on the target market and campaign goals.
28:02 – Elbert:
If I may add, this shift forces a higher frequency of relevant messaging. We now challenge clients to continually reflect on what makes their product unique and ensure content remains current. This iterative approach to product-channel fit drives better results.
29:01 – Cheryl:
Exactly. Brands must actively provide insights about their unique selling propositions rather than relying solely on past benefits. This continuous feedback from the market helps refine messaging and boost campaign performance.
32:12 – Audience Question (paraphrased):
Are you saying that novelty matters—that messages must change frequently, or is it more about relevance?
32:12 – Cheryl:
It’s less about novelty and more about relevance. You need to understand your target audience, deliver the appropriate message at the right time, and create a sense of urgency. Marketing fundamentals remain the same, just applied on a faster, more dynamic timeline today.
33:13 – Cheryl:
Imagine going from a single static message to a rapidly changing, data-driven narrative that adapts to your audience’s moment-to-moment needs. It’s about delivering the right message when it counts most.
36:20 – Cheryl:
Step four is monitoring sentiment to influence outcomes. AI-powered listening tools like Brandwatch, Sprout Social, and Talkwalker help detect brand perception in real time. They alert you to spikes in positive or negative sentiment across social and the broader web so you can quickly adjust your messaging.
38:22 – Cheryl:
Step five is to automate the mundane. AI chatbots and automated term detection can handle FAQs and direct messages 24/7, ensuring a faster response while filtering out spam and hate with auto-moderation tools. Smart schedulers also post content at optimal times based on historical data.
40:21 – Cheryl:
For example, Meta’s automation features can trigger specific responses when a keyword is used, such as sending competition details immediately once someone comments a designated word. This creates fast, efficient engagement without manual intervention.
41:28 – Cheryl:
Next, let’s discuss how AI is reshaping content creation in performance marketing. Content must drive action, whether it’s generating leads or increasing sales. AI accelerates ideation and produces multiple versions of copy, headlines, and calls to action—but it always needs human guidance to ensure relevance and emotion.
42:36 – Cheryl:
Effective content rests on three key pillars: relevance, clarity, and urgency. AI can draft content quickly, yet without clear instructions it may pull generic data. The human element refines this content to ensure it resonates with the target audience.
43:43 – Cheryl:
That’s why it’s essential to optimize messaging and personalize content. AI assists in adjusting headlines, calls to action, and even imagery for different audience segments, but the final creative must be vetted by a human to avoid “wonky” results.
44:50 – Cheryl:
Step six is personalizing and enhancing creative content. AI dynamically adjusts headlines, offers, and imagery for each segment. Tools like Adobe Firefly, Canva AI, and PixArt help generate lifestyle images, often removing the need for costly photo shoots, while still keeping brand voice intact.
45:50 – Cheryl:
Dynamic creatives can lead to a 30% improvement in conversion rates and a 22% increase in engagement. For example, a straightforward discount message might be transformed into a more engaging message that combines interpersonal appeal with clear offers, resulting in stronger performance.
46:53 – Cheryl:
AI is also solving creative gaps. For instance, if a client lacks quality lifestyle imagery, AI can enhance basic product photos by improving lighting, depth, and context. This turn-around can significantly boost engagement metrics.
47:54 – Cheryl:
A before-and-after example: one client’s feed went from plain product photos to aspirational lifestyle visuals through AI-generated backgrounds and enhancements. The product remained the same, but its presentation changed dramatically, driving higher engagement.
49:01 – Cheryl:
In practice, AI can also serve as a creative consultant. It analyzes different ad variations and provides feedback—suggesting improvements like stronger personality, urgency, or added social proof. This feedback is then fed into dynamic ad sets for better performance.
50:01 – Cheryl:
For example, we tested two creative options: one with a bold visual and emotional appeal and another with clear product details and trust cues. AI determined that a hybrid approach—combining high-impact visuals with credibility elements—would yield the best results.
51:02 – Cheryl:
In our final step—step seven—AI plus humanization equals maximum ROI. AI excels at data analysis and content generation, while humans provide strategic direction, emotional connection, and brand consistency. Together, they form a powerful partnership that drives both performance and authenticity.
53:11 – Cheryl:
Humanized content wins on social because platforms favor authenticity, and audiences crave a genuine connection. To humanize AI-generated copy, keep it concise, cut the jargon, add real stories, and adjust the tone to reflect your brand’s voice. Always fine-tune your AI prompts to educate the algorithm.
56:19 – Cheryl:
To summarize the seven steps:
1. Understand the AI-driven shift in social platforms.
2. Let platforms do the heavy lifting.
3. Adopt a performance-first mindset.
4. Monitor sentiment in real time.
5. Automate the repetitive tasks.
6. Personalize and enhance creative content.
7. Blend AI with human intelligence to maximize ROI.
57:24 – Audience Question:
Based on your experience with clients, which factor has proven most impactful for creative performance—relevance or urgency?
57:24 – Cheryl:
For creative performance, it’s vital to deliver information that is both relevant and timely. Your content must speak directly to the audience’s needs and benefit them, while also incorporating urgency to prompt immediate action. Audiences respond better when they feel the message is meant specifically for them at that moment.
59:30 – David:
Thank you so much, Cheryl, and thanks to everyone for participating. It’s been a packed session with great insights and global perspectives. I look forward to seeing you all at future AI Insiders events.
0:05 – David:
Hello and welcome to another edition of AI Insiders. I'm David Burkowitz, and although my AI-powered specs aren’t used for this call, I’m excited to have guests from South Africa with us today—especially Cheryl Ingle—to discuss where AI fits within social and content marketing.
1:09 – David:
Cheryl, it’s great to have you. I recently met your colleague in New York and have already learned a lot from your team. For those who are new here, we love these interactive community conversations and look forward to hearing everyone’s thoughts. Please feel free to interrupt if you have any specific questions.
1:25 – Cheryl:
Great to be here. I’m excited to share my experience in social marketing, especially how we’ve used AI to enhance performance.
2:09 – Cheryl:
Today, we’ll discuss using the power of AI to drive results in social media marketing. We’ll explore how platforms like Meta use AI for everything from algorithms to ad development, and how marketers can use it to improve content performance and overall efficiency. By the end of the session, you’ll have seven clear steps for leveraging AI’s strengths without losing the human touch.
3:15 – Cheryl:
Social has changed dramatically. AI now runs the social ecosystem, controlling what content is seen based on engagement signals. It’s not about posting frequently anymore; rather, visibility is determined by how much users interact with your content.
4:18 – Cheryl:
Content delivery has evolved. AI isn’t just changing the amount of content produced but is also influencing the rules for standing out. Today, relevance matters more than quantity because every post competes with a flood of AI-generated content.
5:25 – Cheryl:
The battleground is now quality and relevance. With so many creators—both human and bot—producing content, audiences quickly scroll past anything that doesn’t connect. Platforms reward posts that quickly generate strong engagement rather than merely filling the feed.
6:20 – Cheryl:
Platforms now reward content that engages users fast. Engagement isn’t just about likes; it includes comments, shares, click-throughs, and even the amount of time a post is viewed. Posting just for the sake of quantity can even lead to penalties.
7:24 – Cheryl:
Earlier, social platforms used simple criteria such as recency and engagement to sort content. For example, Facebook’s old EdgeRank algorithm relied on relevance, recency, engagement, and post type. Since 2015, it has shifted to a machine-learning model that now considers over 10,000 factors.
8:30 – Cheryl:
What we see today is data overload. Every piece of data is used to predict content relevance and personalize each user’s feed. What used to be a straightforward formula has become complex, so we must work with the algorithm to perform well on social.
9:28 – Cheryl:
Relevancy is key. The system collects your engagement data, filters it through prediction models, and ranks posts by what it thinks you’ll find valuable. Your feed becomes highly personalized through continuous feedback loops.
10:31 – Cheryl:
Although posting is easy, cutting through the noise is challenging. AI has shifted us from a world of scarcity to one of abundant content, making attention the scarcest resource. The goal is to remain relevant so your post isn’t skipped by the algorithm.
11:32 – Cheryl:
Our response to this change is to let platforms do the heavy lifting. AI is now deeply embedded in platforms like Meta, TikTok, and LinkedIn to optimize content. Instead of manually tweaking every detail, you set the rules and let the machine optimize on your behalf.
12:37 – Cheryl:
For example, content optimization now includes predictive targeting that expands your audience based on behavior, along with smart bidding that adjusts budgets in real time. Objective-based delivery optimizes campaigns for your specific goals using continuous feedback.
13:36 – Cheryl:
Regarding platforms, TikTok’s algorithm is far superior in certain areas compared to Meta’s. TikTok monitors where you linger, what you share, and how long you watch, making it very effective at keeping users engaged. Meta is now working to replicate that level of sophistication.
14:37 – Cheryl (answering a question):
Regarding engagement, all platforms measure interactions—comments, shares, likes, video views, and replay frequency—but they weight these signals differently. For instance, a like may be more valuable on Instagram while view duration is critical on TikTok.
15:41 – Cheryl:
Beyond smart bidding, we now have objective-based delivery and native creative assistance built into platforms. These features automatically test creative variations and rotate dynamic creatives based on performance, ensuring the right message is shown to the right audience.
16:43 – Cheryl:
Platform-level creative rotation means that even if you upload multiple creative options, the system dynamically decides who sees which version based on past interactions. This level of automation is relatively new with AI advancements.
17:44 – Cheryl:
Essentially, all the content you see on social is powered by AI through predictive models and real-time data analysis. The key is to provide strong inputs so the machine can perform optimally—think of it as “build better inputs and let the machine do the rest.”
18:42 – Cheryl:
In practice, educating AI properly results in better targeting and ultimately improved conversion rates. Tools like Meta Advantage Plus (or TikTok’s Smart Creative) have shown up to a 32% improvement in cost per purchase by continuously optimizing campaigns.
19:48 – Cheryl:
This leads us to step three: adopting a performance-first mindset. It’s about using AI not only for automation or efficiency but as a driver of performance. Educate the system so it optimizes targeting and creative delivery, ensuring your marketing budget is spent effectively.
20:51 – Cheryl:
When optimized correctly, AI finds high-intent users and scales high-performing ads automatically. Real-time campaign adjustments—be it targeting, bidding, or creative rotation—mean you spend less on underperforming campaigns and focus on what converts.
21:54 – Cheryl:
In other words, performance matters. Instead of manually adjusting budgets, let AI reallocate funds to better-performing ads, improving bottom-line outcomes through efficient targeting and dynamic optimization.
22:54 – Cheryl:
Using AI in practice through tools like Advantage Plus has proven that campaigns optimized by AI can see significant improvements, such as a 32% reduction in cost per purchase. This demonstrates how performance-driven adjustments reduce wasted spend.
23:57 – Audience Question (paraphrased):
What are the implications of A/B testing when algorithms automatically optimize campaigns?
23:57 – Cheryl:
A/B testing still has value when testing distinctly different approaches. I recommend running controlled tests for creatives or strategies that vary significantly, then using dynamic creative tools to optimize based on those findings. It’s all about learning what works best.
24:54 – Lisa (audience comment):
I see AI making advertising easier, yet some clients report declining ROI and less loyal customers from social ads. Are you noticing that as well?
25:55 – Cheryl:
Social has become more competitive due to the overload of content. Sometimes, even with AI optimization, results vary by industry. For clients facing this challenge, I often suggest reducing spend on paid social and focusing more on organic or owned channels. It really depends on the target market and campaign goals.
28:02 – Elbert:
If I may add, this shift forces a higher frequency of relevant messaging. We now challenge clients to continually reflect on what makes their product unique and ensure content remains current. This iterative approach to product-channel fit drives better results.
29:01 – Cheryl:
Exactly. Brands must actively provide insights about their unique selling propositions rather than relying solely on past benefits. This continuous feedback from the market helps refine messaging and boost campaign performance.
32:12 – Audience Question (paraphrased):
Are you saying that novelty matters—that messages must change frequently, or is it more about relevance?
32:12 – Cheryl:
It’s less about novelty and more about relevance. You need to understand your target audience, deliver the appropriate message at the right time, and create a sense of urgency. Marketing fundamentals remain the same, just applied on a faster, more dynamic timeline today.
33:13 – Cheryl:
Imagine going from a single static message to a rapidly changing, data-driven narrative that adapts to your audience’s moment-to-moment needs. It’s about delivering the right message when it counts most.
36:20 – Cheryl:
Step four is monitoring sentiment to influence outcomes. AI-powered listening tools like Brandwatch, Sprout Social, and Talkwalker help detect brand perception in real time. They alert you to spikes in positive or negative sentiment across social and the broader web so you can quickly adjust your messaging.
38:22 – Cheryl:
Step five is to automate the mundane. AI chatbots and automated term detection can handle FAQs and direct messages 24/7, ensuring a faster response while filtering out spam and hate with auto-moderation tools. Smart schedulers also post content at optimal times based on historical data.
40:21 – Cheryl:
For example, Meta’s automation features can trigger specific responses when a keyword is used, such as sending competition details immediately once someone comments a designated word. This creates fast, efficient engagement without manual intervention.
41:28 – Cheryl:
Next, let’s discuss how AI is reshaping content creation in performance marketing. Content must drive action, whether it’s generating leads or increasing sales. AI accelerates ideation and produces multiple versions of copy, headlines, and calls to action—but it always needs human guidance to ensure relevance and emotion.
42:36 – Cheryl:
Effective content rests on three key pillars: relevance, clarity, and urgency. AI can draft content quickly, yet without clear instructions it may pull generic data. The human element refines this content to ensure it resonates with the target audience.
43:43 – Cheryl:
That’s why it’s essential to optimize messaging and personalize content. AI assists in adjusting headlines, calls to action, and even imagery for different audience segments, but the final creative must be vetted by a human to avoid “wonky” results.
44:50 – Cheryl:
Step six is personalizing and enhancing creative content. AI dynamically adjusts headlines, offers, and imagery for each segment. Tools like Adobe Firefly, Canva AI, and PixArt help generate lifestyle images, often removing the need for costly photo shoots, while still keeping brand voice intact.
45:50 – Cheryl:
Dynamic creatives can lead to a 30% improvement in conversion rates and a 22% increase in engagement. For example, a straightforward discount message might be transformed into a more engaging message that combines interpersonal appeal with clear offers, resulting in stronger performance.
46:53 – Cheryl:
AI is also solving creative gaps. For instance, if a client lacks quality lifestyle imagery, AI can enhance basic product photos by improving lighting, depth, and context. This turn-around can significantly boost engagement metrics.
47:54 – Cheryl:
A before-and-after example: one client’s feed went from plain product photos to aspirational lifestyle visuals through AI-generated backgrounds and enhancements. The product remained the same, but its presentation changed dramatically, driving higher engagement.
49:01 – Cheryl:
In practice, AI can also serve as a creative consultant. It analyzes different ad variations and provides feedback—suggesting improvements like stronger personality, urgency, or added social proof. This feedback is then fed into dynamic ad sets for better performance.
50:01 – Cheryl:
For example, we tested two creative options: one with a bold visual and emotional appeal and another with clear product details and trust cues. AI determined that a hybrid approach—combining high-impact visuals with credibility elements—would yield the best results.
51:02 – Cheryl:
In our final step—step seven—AI plus humanization equals maximum ROI. AI excels at data analysis and content generation, while humans provide strategic direction, emotional connection, and brand consistency. Together, they form a powerful partnership that drives both performance and authenticity.
53:11 – Cheryl:
Humanized content wins on social because platforms favor authenticity, and audiences crave a genuine connection. To humanize AI-generated copy, keep it concise, cut the jargon, add real stories, and adjust the tone to reflect your brand’s voice. Always fine-tune your AI prompts to educate the algorithm.
56:19 – Cheryl:
To summarize the seven steps:
1. Understand the AI-driven shift in social platforms.
2. Let platforms do the heavy lifting.
3. Adopt a performance-first mindset.
4. Monitor sentiment in real time.
5. Automate the repetitive tasks.
6. Personalize and enhance creative content.
7. Blend AI with human intelligence to maximize ROI.
57:24 – Audience Question:
Based on your experience with clients, which factor has proven most impactful for creative performance—relevance or urgency?
57:24 – Cheryl:
For creative performance, it’s vital to deliver information that is both relevant and timely. Your content must speak directly to the audience’s needs and benefit them, while also incorporating urgency to prompt immediate action. Audiences respond better when they feel the message is meant specifically for them at that moment.
59:30 – David:
Thank you so much, Cheryl, and thanks to everyone for participating. It’s been a packed session with great insights and global perspectives. I look forward to seeing you all at future AI Insiders events.