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Planable
Manage your socials as a team
Planable is the best client-facing social media tool we've ever used and we've used a lot.
Creation
fast, AI-powered, platform-perfect
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Planning
clean, visual content planning
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Collaboration
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Approval
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Social Listening
listen, discover, and act
You're managing eight clients. Each has three to five social channels. You post three times a week per channel. That's between 72 and 120 pieces of content per month, just for one person to track, write, review, approve, and schedule. Now add a second client. And a...
Oct 2, 2026
People have had enough of AI slop. LinkedIn shipped a “seems like AI slop” button. Instagram labels AI-generated content. Anthropic is watermarking Claude’s text. The EU AI Act explains some of that. The rest is fatigue: feeds full of posts that all sound the same and say nothing.
The usual fix goes after the writing. Strip the “it’s not X, it’s Y”, lose the em dashes, put a human between the draft and the publish button. That might get rid of the tells, but the bigger problem doesn’t budge.
Content nobody asked for. A brand decides what it wants to say, reverse-engineers a question to hang it on, and hits publish. Polish it all you like, it’s still an answer in search of a question.
Meanwhile, the real questions are sitting in plain sight. Every day your audience asks for advice, weighs options, and complains about what doesn’t work, on Reddit, on LinkedIn, on YouTube, in forums and comment sections.
Those threads don’t stay on social. SE Ranking pulled Google’s top 10 for 100K keywords across 20 niches. In 76.73% of them, at least one result was a social or community site: a Reddit thread, a YouTube video, a Quora answer. SE Visible’s AI search data showed that two in three AI Overviews cited one too. The conversation you’d be listening to is the same one Google and AI answers already pull from.
Listen first, then write. It sounds obvious, but most content calendars run the other way round.
Here’s the rest of SE Ranking’s research, engine by engine and niche by niche; what 12 months of trying taught us at Planable, including the part that didn’t work; and a six-step workflow, in Planable Social Listening, SE Ranking and SE Visible, for turning what you hear into a reply, a post, or an article. If you’re already using the tools, there’s a skill at the end that does the legwork.
A question on Reddit can tell you what your audience needs help with. That same discussion can rank in Google and become a source in an AI answer. Social conversations give you clues about what to write, and they’re also part of what people find when they search.
Across 100,000 keywords covering 20 niches, 76.73% had at least one social or community source in Google’s top 10 organic results. In other words, these platforms appeared among the leading results for more than three out of four searches in the dataset.
SE Visible’s data showed that their presence extended into AI search, too. Roughly two in three Google AI Overviews cited at least one social or community source, as did around one in three AI Mode answers.
Sample sizes: 100,000 queries for AI Overviews and 50,000 each for AI Mode and ChatGPT, covering 20 niches. These percentages measure answers containing at least one social citation, rather than social platforms’ share of all citations.
In plain terms: when Google’s AI gives someone an answer, it points to a Reddit thread, a YouTube video, or someone’s post more often than not: a real brand’s own website is frequently not the source.
But knowing that AI engines cite social content is only the starting point. Which platforms they turn to depends on the engine, the topic, and whether someone is asking about a specific brand.
Reddit had the widest reach in organic search, appearing in the top 10 for 46.28% of keywords. YouTube and Facebook each appeared for around 30%, followed by Quora at 15.79%.
For a social team, this is the reverse of how these platforms usually get framed: not just where you post, but where Google is already finding answers to what your audience is asking.
AI search data showed a different mix. YouTube was the most-cited domain in the AI Overviews dataset, accounting for 16.2% of all citations. Reddit led among social platforms in AI Mode, while Reddit and LinkedIn received the largest social-platform citation shares in ChatGPT.
Shares are calculated from all citations within each engine’s sample.
So, a social platform that stands out in one AI engine may play a much smaller role in another. Before deciding where to focus your content efforts, check which platforms get cited for your topics across the engines you want to appear in.
Social sources weren’t equally prominent in every category. They appeared in Google’s top 10 for 95.34% of searches about relationships and 92.14% of searches about careers and jobs, compared with 32.70% of searches about real estate.
Translate this to your own category before reading the numbers below: a social team in careers or e-commerce is sitting on far more AI-search leverage than one in real estate, just based on how much their audience already turns to social to figure things out.
Within AI answers, individual platforms also became more prominent for certain topics. LinkedIn, for example, appeared in 21.42% of career and jobs AI Overviews, compared with just 3.15% across all topics.
That’s a reason to check your own niche rather than relying only on the averages across all topics. A platform with limited overall coverage can be much more prominent for a particular category.
So, if you’re in the careers space, LinkedIn may matter more than the overall numbers suggest. If you’re in beauty, it’s worth looking at what people are asking on Instagram and which content AI answers cite.
Start with the conversations relevant to your brand, then check which platforms show up when people search for those same topics.
Using SE Visible’s data, we also compared two separate AI Mode datasets: 100,000 branded queries and 100,000 non-branded queries. Social sources appeared in 39.34% of branded-query answers and 48.58% of non-branded-query answers, but the platform mix shifted.
This comparison uses separate datasets from the cross-engine analysis above.
So how’s this actionable for the social media team? Check which way your split leans. If non-branded citations outweigh branded, it means AI tools are already finding social proof for you before someone searches your name, so lean into more of the “does anyone else deal with X” content.
If it’s the other way around, then AI tools back you up once someone asks for you by name, but you’re losing the open competition on the topic itself. So put more content into owning the general question before someone knows to ask for you specifically.
Since LinkedIn appeared across all three AI engines we analyzed, we decided to see whether repurposing our existing blog content there could help it get discovered in AI search.
We built a Claude-powered workflow that finds topics AI models are already citing in our niche, matches them with relevant blog articles, and turns those articles into ready-to-publish drafts in the assigned author’s voice.
As of August, 8 of our 25 published LinkedIn articles were cited in 422 AI answers covering 64 prompts.
Tools comparisons and practical workflow guides were the content getting picked up most often. Three articles led the results:
A few patterns stood out in our results:
Here’s how you’d spot a LinkedIn article used as a source in LLMs, in SE Visible:
There’s also a wider story behind those LinkedIn results. We’ve spent the past 12 months experimenting with social content for AI visibility. Here’s how George Danaila, our content marketing manager, sums up the experience:
“We started with the prompts we wanted to appear for and built content specifically around those questions. We tried YouTube videos, carousels on LinkedIn and Instagram, and even ran our own subreddit. None of those efforts noticeably improved our AI visibility.
What finally showed results was publishing LinkedIn articles through personal profiles, rather than the brand’s account.”
So, if your brand has people with useful expertise, give them space to share it in their own voices. That approach worked for us, though it’s something to test rather than a rule to follow.
“I’d also recommend keeping an eye on the sentiment of conversations about your brand. What do people appreciate enough to recommend? What frustrations keep coming up? Understanding those conversations gives you a better starting point for creating something useful.”
The research can point you in the right direction, but you’ll need to see what works for your own brand. Look at which sources AI tools already cite for the questions your audience asks. Which platforms come up? What kind of content gets picked up, and who’s publishing it? That gives you a few things to try.
You might already have a blog article worth repurposing or someone on your team with useful experience to share. Start with a few pieces and follow what happens: do they get cited, for which questions, and by which engines? Keep listening to the conversations around those topics, too. If people keep asking something your content doesn’t answer, you’ve got a good reason to create something new.
So how do you find those questions and decide which ones are worth building content around? That’s what the workflow below is designed to help with.
In Planable Social Listening, review the brand, competitor, and topic keywords you track. Keyword-based listening finds mentions even when people haven’t tagged your brand, across Facebook, Instagram, LinkedIn, TikTok, X, YouTube, Reddit, and the wider web.
Each keyword group can tell you something different:
Sort mentions by relevance, recency, or engagement to narrow down what you read first.
You can sort by sentiment. Negative mentions are a good place to look for frustrations; positive ones can help you understand what people appreciate enough to recommend. Read the posts themselves, though. The sentiment label alone won’t tell you what happened or whether you have something useful to add.
As you read, look for three types of signals:
Check who’s posting and where. Several posts from one person don’t tell you as much as similar experiences shared by people in separate conversations. One busy thread is worth reading, but you’ll need more evidence before calling it a trend.
Think about how you could answer the question on the platform where you found it. Could you show the process in a short video? Would a checklist help? Does the person just need a reply?
Here are a few ways those conversations could turn into content:
Be as specific as the conversation. If someone is asking how to deal with two clients giving contradictory feedback, a post about “the importance of collaboration” won’t help much. Show how you’d resolve that situation.
And if you can answer someone’s question in a comment, do that. You don’t have to turn every useful conversation into a content brief.
Take the questions you’ve found and look up related queries in SE Ranking. Check search volume, keyword difficulty, related questions, and whether demand is changing.
Then read some of the pages that rank. Notice what kind of content appears: guides, comparisons, templates, or product pages. Check whether they answer the question you started with, including the details people were struggling with.
Low or missing search volume doesn’t automatically rule out a useful social response. A specific question can still deserve an answer, especially when several relevant people are asking it. Search data adds context to that decision.
This research can help both teams:
SE Visible’s data showed that social content can become a source for AI answers. Now take the questions and frustrations you found through social listening and see how AI engines respond to them.
Use SE Visible’s AI-search data to see how often your brand appears in AI answers for the questions you track, how it compares with competitors, and whether visibility differs across AI engines.
Where you can review the answers and sources, read them with the original conversation in mind. Look for advice that leaves the reader with more questions or skips the part they need help with.
An AI answer might suggest “establishing a clear approval process,” for example, without explaining what to do when reviewers disagree or miss a deadline. Your content could walk through those situations.
Note any missing examples, explanations, or evidence you could provide. Those details will help whoever creates the content understand what to add.
Before assigning a new piece, look through your relevant social posts. Use SE Ranking to find website pages that already rank for related searches, and SE Visible to check whether those pages appear in AI answers for the questions you’re tracking.
You may have a guide that answers the question, with an example you could turn into a social post. Or you may only need to add a section to an existing article.
Put the findings into a planning table so the team can see what you’re proposing and why:
Some topics will only need a social response. Others may call for a post and a website update. If you’re unsure, keep the topic on a watch list and note what would make you reconsider it, such as the same question appearing in more independent conversations.
Once you’ve agreed on the next step, write the brief.
For social content, specify the platform, format, question to answer, main point, and examples to include. If you’re linking to an article, explain what the post itself should teach the reader.
For an article or page update, explain who it’s for, what they need help with, which sections to cover, and what evidence to use. Include relevant queries and internal links.
After publishing, check the response during your next review. Follow-up questions may show that something needs a better explanation. Comments describing similar problems may give you examples to cover next.
If you use Planable and SE Ranking with Claude, you can use the Weekly Content Opportunity Radar Skill to carry out much of this research and prepare the briefs.
Note: The automated workflow uses SE Ranking’s MCP connector for organic and AI-search data. The SE Visible checks described above are part of the manual workflow; a dedicated SE Visible MCP connector is coming soon.
The Skill reviews your tracked keywords in Planable, compares the latest seven days of available listening data with the previous seven days, and looks for recurring problems, questions, and growing discussions.
It then checks organic and AI-search data in SE Ranking, reviews relevant content already on your website, and recommends what to do next.
The report starts with a table of up to three recommended opportunities, with no more than one per signal type. If it doesn’t find enough evidence to recommend something in a category, it says so.
Below the table, you can read the conversations and search findings behind each recommendation. The suggested action might be to create something new, expand or refresh existing content, or repurpose it. Topics that need more evidence go on a watch list, with a note explaining when to revisit them.
For recommendations that move forward, the skill prepares a brief for social or website content (or both).
A social brief tells you where to publish, what format to use, who should post, and what to say. It may recommend replying to an existing thread, writing an original post, or doing both. It includes the angle, evidence to use, claims to avoid, and how soon to respond while the conversation is still active.
A website brief explains who the page is for, what it should answer, and which sections to include. It also specifies whether you need a new page or changes to an existing one.
If the recommendation includes both, the briefs explain the order. For example, the social team could answer an active thread first while the content team adds a more detailed explanation to a guide.
The briefs give each team enough context to start creating the content. Drafting and publishing happen separately.
To use the skill:
Requires access to Planable Social Listening and an SE Ranking account, both connected to Claude. Follow the setup instructions for the Planable MCP connector and SE Ranking MCP connector.
Before adding another post or article to the calendar, look at what people are asking. Is the question coming up more than once? Have you answered it already? Would a reply, a social post, or a longer resource help most?
Social listening gives you the question in your audience’s own words. Search data helps you see whether people are looking for the same answer elsewhere. Together, they give you a better reason to create something than an empty slot in the content calendar.
