Detect each visitor's language and show PostSnag in it, from the landing page to the extension to the dashboard, starting with Facebook's biggest non-English markets. The problem Some of Facebook's heaviest users, the exact power users PostSnag is built for, are not in English-speaking countries. They are in Brazil, Indonesia, Mexico, and beyond, where Facebook engagement runs highest. Today PostSnag is English-only on every surface: the landing page, the Chrome extension, and the dashboard. For a marketer in Sao Paulo or Jakarta, that is friction at every step, from reading the pitch to using the tool daily, and it quietly caps PostSnag's reach in the markets where it should be strongest. What we're building Full language support across all three PostSnag surfaces, rolled out in sequence. The framework is built so a new language is a pack we add, not a rebuild. Landing page first: every page detects the visitor's location and language and shows a translated version automatically, with a manual switcher to override. The Chrome extension next: its capture controls and labels in the user's own language. The dashboard last: the full analytics experience translated, so daily use feels native end to end. How it works for you Land on postsnag.com from Brazil and the page is already in Portuguese, with a switcher if you prefer English. Install the extension and its buttons match. Open the dashboard and every screen speaks the same language, so nothing about the product feels foreign. What you get A product that feels built for you, not translated as an afterthought, from the first page through daily use. Automatic language detection, so you never hit a wall of English you have to decode first. A manual switcher, so you are always in control of which language you see. For example A social media manager in Mexico City finds PostSnag, lands on a page already in Spanish, gets the pitch in seconds instead of translating it in her head, signs up, and runs her whole workflow, extension and dashboard, in Spanish. The same journey that used to lose her at step one now converts. What it unlocks Opening PostSnag to non-English markets reaches the people who use Facebook the most, which is exactly the audience the whole product is built to serve. Once the translation framework exists, every new country is a language pack away instead of an engineering project. Who it's for Marketers, creators, and agencies in high-Facebook-usage markets like Brazil, Indonesia, and Mexico who want PostSnag in their own language, and anyone who would rather work in their native language than in English.

PostSnag about 10 hours ago

A badge on the PostSnag icon when a page you track publishes something new, plus optional email reminders on a cadence you choose, so your captured data never quietly goes stale. The problem Captured data is only as good as the moment it was captured: you scan a competitor today, feel current on them, and three weeks later they've posted a dozen more times with nothing telling you it's time to check back in, so tracking a page quietly turns into "tracked it once, months ago." This gets worse the more pages you track, since each one posts on its own schedule and "when did I last check page six" isn't a question anyone's memory answers reliably. It's not just inconvenience: every timing feature PostSnag builds on top of a captured library gets less accurate the staler the underlying data is. What we're building Two lightweight nudges: a badge on the PostSnag extension icon when a tracked page has posts you haven't captured yet, based on what your own logged-in session already sees, and optional email reminders on a cadence you set per page, so the nudge reaches you even on days you never open Facebook. A badge on the extension icon when a tracked page has new activity, based on what your own session already sees while browsing. Optional email reminders on a schedule you choose, per page, independent of any activity check. Fully privacy-safe: nothing runs against your account while you're away, the badge just reflects what's visible next time you're there. How it works for you Set reminders that match how often each tracked page actually matters, weekly for fast movers, monthly for the rest. If you happen to be browsing Facebook and a tracked page has something new, the icon badge tells you right then, ahead of schedule. What you get No more discovering months later that a tracked page has been sitting on old data the whole time. Per-page control, so a fast-moving competitor gets checked weekly while a quiet account gets checked monthly. Sharper downstream analytics, since a fresher library means a more accurate overperformance score and trend read. For example You track five competitors: two checked weekly, three on a monthly reminder. One Tuesday you notice the extension badge lit up, a quieter competitor on the monthly schedule just launched a new content format two days ago, well ahead of when your reminder would have caught it, so you adjust your own calendar that same week. What it unlocks This is the loop that keeps everything else honest: snapshot history is only worth as much as how often you re-scan, and the heatmap and overperformance score are only as sharp as the freshest data behind them. The badge and reminders close that gap, so the rest of PostSnag is always reading from data that reflects what a page is doing now. Who it's for Anyone tracking more than a couple of pages regularly, agencies managing watchlists across several clients, and anyone who's been burned by realizing their competitor data was months out of date right when it mattered.

PostSnag about 16 hours ago

Go past basic group capture to the real analytics: top posts, top contributors, and the best times to post inside any Group you belong to. The problem Facebook Groups hold some of the most engaged communities online, but Facebook itself shows admins almost nothing useful: no ranking of top posts, no read on who really drives engagement, no sense of when the group is most active. PostSnag already captures a group's posts as you scroll, more than most people have ever had, but capturing the posts isn't the same as seeing the patterns inside them, so you're still mostly guessing about what makes that specific community move. What we're building The deeper analytics layer for any Group you belong to, built on the group posts PostSnag already captures the same private, client-side way it captures everything else: only what your own logged-in account can already see. Top posts, ranked by engagement and overperformance, so you see what actually lands. Top contributors, measured by the engagement they drive, not how often they post. Best times to post, a day-by-hour read on when the group is paying attention. How it works for you Open a group you belong to and capture as you scroll, exactly like you do on profiles and pages. Your dashboard treats that group as a full analytics view: sortable, filterable, and comparable over time. What you get A clear read on what content wins in this community, so you can post what actually gets traction. The real influencers inside a group, ready for outreach, partnerships, or research. Overperformance scoring calibrated to group size, so a small group's top post gets fair credit. For example You run a 40,000-member group for real estate agents. PostSnag shows short tactical posts overperforming long personal stories by 3x, five members driving a third of all engagement, and Tuesday and Thursday mornings beating every other slot, so you rebuild your posting calendar around it. What it unlocks Groups analytics extends every PostSnag metric into a space almost nothing else can reach: the top-contributor view feeds outreach lists, and snapshot history lets you catch a community trend forming instead of hearing about it after it peaks. Who it's for Group admins who want their community to grow on purpose, marketers hunting for where their audience gathers, and anyone researching a private community they already belong to.

PostSnag about 16 hours ago

Select your best posts, or a competitor's, and PostSnag drafts fresh content that reuses what already worked, written in your voice. The problem You know what works, the post that did 5x normal engagement, the competitor post that clearly struck a nerve, the format that keeps winning, and you still open a blank compose box and stare at it, because knowing what worked and turning that into your next post are two different skills. Competitor research hits the same wall: you screenshot a winning post and it just sits in a folder, because translating someone else's post into your own voice without it reading like a copy takes real time most people don't have, especially if you're writing for more than one account. What we're building A generation tool built directly on your captured data. Select one or more top-performing posts, yours or a page you track, and PostSnag writes new drafts that reuse the underlying pattern, not the words: Pick any post as inspiration, your own history or any profile you've scanned, and the pattern gets reused, not copied. Drafts come back in your voice, calibrated from your own past posts, not a generic AI tone. Mix, regenerate, or borrow a line: combine two winners, generate variations, or start from one opening line. How it works for you You open a post that overperformed, hit Rewrite, choose "in my voice," and get three fresh drafts back in seconds, same underlying structure as the original but about whatever you're posting today. What used to be an hour staring at a blank box is now a few minutes editing something with a proven shape behind it. What you get A running head start on every post instead of a blank compose box. Competitor research that becomes actual content instead of an unused screenshot folder. Drafts that sound like you, calibrated against your own voice, not a generic AI default. For example You track a competitor bakery page and notice their "behind the scenes at 5am" post pulled 5x their usual engagement. You select it, hit Rewrite, and get three drafts back using the same early-morning structure rebuilt around your own shop and voice, and you post one before lunch instead of letting it sit in a folder for a month. What it unlocks This is where PostSnag's analysis turns into output instead of just insight: the overperformance score decides what's worth rewriting from, the hook library supplies proven openers, and the "why this worked" breakdown is what makes the rewrite good instead of a surface-level copy. Who it's for Social managers juggling more than one voice across multiple accounts, solo creators without a copywriter on call, and agencies who want to go from "here's what's working" straight to "here's your next post."

PostSnag about 16 hours ago

Every hook from every post you've ever captured, pulled automatically into one searchable, filterable swipe file. The problem The opening line is the whole game: before anyone reads your second sentence, they've decided whether to keep scrolling based on the first. Almost nobody has a real system for tracking which openers actually work, because building one by hand means copy-pasting into a doc every time you spot something good, a habit that dies within a week. Even a real swipe file becomes a graveyard eventually, you can't sort it by format or filter it to openers that actually drove results, even though the raw material is already sitting inside PostSnag, captured with every post you've scanned, just never surfaced as its own thing. What we're building An automatic hook library that builds itself from data you're already capturing, no new habit required: Every opening line, pulled out automatically, no copy-pasting, filterable by format the moment it's in. Sort by overperformance score, so you see instantly which hooks actually earned their keep. Search across every page you've scanned, your own history and every competitor, in one place. How it works for you After scanning a handful of profiles, you open the hook library and it's already populated with hundreds of opening lines, no setup required. Filter to video posts at 3x overperformance or higher and get a short, ranked list of openers proven in that format. What you get A swipe file that builds itself passively, with nothing to remember to log. Instant filtering by format and overperformance score, so you study only what's proven. Every page you've ever scanned in one searchable place, by keyword or theme. For example You're staring down a Tuesday posting deadline with nothing to say. You filter the hook library to your own top-performing photo posts and notice four of your five best openers start with a number, "3 things," "5 signs," and write today's post the same way. It becomes your best-performing post of the month. What it unlocks The hook library is the raw material for everything PostSnag does with generation and analysis: it's what a rewrite tool pulls from, what the "why this worked" breakdown points back to, and because every hook carries its overperformance score, sorting by what's actually proven is built in from day one. Who it's for Anyone who writes their own posts on a regular cadence: creators, social managers, and copywriters who already think in swipe files and want theirs to finally build itself.

PostSnag about 16 hours ago

Compare up to 5 profiles at once, format mix, posting frequency, engagement rate, and top posts, all lined up side by side and exportable in one click. The problem Competitive research happens one browser tab at a time: you open Profile A, jot down numbers, open Profile B, and by Profile E you've forgotten what A's posting frequency was, with no native way to see the whole field at once. Then comes presenting it: a market scan needs to become a slide or a client email, so on top of comparing everything by hand you're also building the visual from scratch, formatting a table for numbers PostSnag already has. It's exactly the kind of task that should take minutes, not an afternoon of tab-switching and spreadsheet formatting. What we're building A comparison view: pick 2 to 5 profiles you've captured, pages, groups, or competitors, and see them lined up on the metrics that matter, all on the same axis, at a glance: Format mix and posting frequency, side by side for every profile in the comparison. Engagement rate and top posts, the fair apples-to-apples number plus each profile's best performers. One-click export, turn the whole comparison into an image or a PDF, ready for a deck or a client. How it works for you Open the comparison view from any profile and add up to four more you've already captured, your own page, direct competitors, whoever belongs in the picture. PostSnag lines them up on one screen so you're reading real differences at a glance instead of flipping between tabs, and you can export the whole view the moment you're done. What you get The entire competitive field in one view, instead of a dozen tabs and a fading memory. Metrics aligned on the same axis, so real differences jump out with no mental math. A ready-to-share export, so competitive research becomes an actual deliverable. For example An agency onboarding a new fitness client compares the client's page against four competitors. The view shows one competitor posting three times the volume at half the engagement rate, while the highest-engagement competitor barely posts but every post is video, so the agency builds the new client's content plan around the video-first approach in the first onboarding call instead of the third. What it unlocks This is where every individual profile snapshot PostSnag captures turns into an actual competitive intelligence view, reading from the same overperformance score that ranks top posts everywhere else, so the "top posts" column always shows genuine breakouts, not just the biggest audience. Who it's for Agencies and strategists sizing up an entire competitive field at once, and anyone who needs the "here's the landscape" slide built fast instead of from scratch.

PostSnag about 16 hours ago

Re-scan a page you already track and PostSnag flags any post running far above that page's normal, right when the scan finishes, not days later. The problem You keep a shortlist of pages you actually care about, but "regularly" checking in quietly turns into "whenever you remember," and by the time you open a page again you're scrolling through a wall of posts trying to eyeball which one did something unusual. By the time you notice a real breakout, on your own or because someone mentions it, the moment has usually passed: the hook is stale and whatever trend it rode has moved on. Facebook won't tell you a post is doing five times what a page usually gets, and nobody does that math by hand for every page they track, so real breakouts slide by unnoticed. What we're building An alert that runs the moment you re-scan a page, built on the same baseline that powers the overperformance score. PostSnag compares each freshly captured post against that page's own trailing average, live, and anything that clears the bar gets flagged immediately instead of buried in a batch of new posts. It only ever runs off a scan you choose to do yourself, never a background process watching pages while you're not looking: A breakout badge on the specific post, calculated from that page's own trailing average, the same honest baseline the overperformance score uses. Triggered only by a scan you initiate yourself, never a background check. Works across your whole tracked list at once, not just the page you happen to be looking at. How it works for you You re-scan your weekly shortlist and one page posted something genuinely running hot. As PostSnag pulls in new posts, it scores each against that page's baseline in real time, and the moment the scan wraps you land on a summary with the breakout called out at the top, multiplier and all, one click from the post's detail view. What you get No more scanning a fresh batch by eye hoping you notice what matters. PostSnag tells you. You catch a breakout while it's still current, in time to actually act on it. Zero background noise: alerts only ever appear off a scan you actually ran. For example You track a dozen pages in the home fitness niche and re-scan every Monday. This week, PostSnag flags one post sitting at 6.1x its usual engagement, a simple before-and-after reel with one specific line doing all the work, and you have that insight on Monday instead of a month from now. What it unlocks Breakout Alerts turns re-scanning from a maintenance chore into something worth doing on a schedule, running on the same baseline as the overperformance score so the two features reinforce each other, and it lays the groundwork for things like a weekly digest or a new-post badge. Who it's for Anyone tracking a shortlist of pages on purpose: competitive researchers, agencies watching client and rival accounts, and brand managers who want to catch a genuine hit while there's still time to react.

PostSnag about 16 hours ago

See exactly how any page compares to similar pages, built entirely from encrypted, opt-in, aggregate data, so no individual page's numbers are ever exposed. The problem A number by itself doesn't mean anything: a page at 2.1 percent engagement could be crushing it or barely getting by, and engagement swings so much by niche, size, and content type that a generic "average engagement rate" from a random blog post is close to useless. This gets worse the moment someone else relies on your read: a marketer telling a boss "engagement is up" needs to answer "compared to what, and is that good," and nobody has ever handed you a clean, current answer specific to your kind of page. What we're building A benchmarking layer that compares any page you've captured against a peer set of similar pages, matched by size and category, and gives you a plain answer: pages like this average 1.2 percent engagement, you're at 2.1 percent, top 18 percent. It's built entirely from PostSnag's own users, and only from users who explicitly opt in: every contribution is encrypted, and the only thing that ever comes out the other side is an aggregate pattern, never any individual page's data: Peer groups matched by size tier and category, so a small page never sits against a huge one, shown as a percentile, not just an average. Built only from data users choose to contribute, encrypted end to end, surfaced only as aggregate patterns, never individual numbers. Gets more precise as more people opt in, with tighter, more specific peer groups over time. How it works for you Open any profile and the benchmark sits right alongside its own stats, no extra step required: you see the page's engagement rate next to a plain-language read of where it lands against similar pages. Opting your own captured data into the shared pool is a one-time toggle, and your numbers are never shown to anyone individually, ever, in exchange. What you get An honest answer to "is this actually good," specific to a page's real size and niche. A percentile you can say out loud in a meeting, backed by real peer data. Total privacy on your own data: encrypted, aggregate only, opt-in, never exposed individually. For example A day care franchise owner sees their page at 1.4 percent engagement and assumes the worst; Industry Benchmarks shows similar community pages average 1.1 percent, putting them in the top 24 percent. An agency swaps "engagement was up this month" for "you moved from the top 30 percent of your peer group to the top 15 percent this quarter," a line that actually means something to a client. What it unlocks Industry Benchmarks is the outward-facing half of a complete performance picture: the overperformance score tells you how a post did against a page's own history, this tells you how the page stacks up against everyone like it, and together they're the context that makes a white-label report or client deck land harder. Who it's for Marketers and agencies who report numbers to a client or a boss, page owners

PostSnag about 16 hours ago

A live status indicator that confirms capture is healthy right now, and a public changelog that shows exactly what shipped and when, so you're never left guessing. The problem PostSnag lives downstream of a platform that changes without warning. Facebook redesigns a layout or shifts how a stat displays, and a tool reading that page can quietly break with no error message, just an export that looks normal until the numbers are a little too low. A tool that fails loudly gets fixed the same day; one that keeps running on incomplete data can stay broken for a week, and by then you may have already handed a client a report built on numbers that were never right. A tool that goes quiet with no visible updates starts to feel abandoned even when it isn't, which is often enough to make people stop trusting it. What we're building Two always-visible signals: a live capture-health indicator confirming PostSnag's capture is working right now, so a quiet Facebook change shows up as a clear status change instead of silently corrupted data, and a public, dated changelog logging exactly what shipped and when. Neither promises perfection, no tool reading a platform client-side can, but you'll never be left to find out the hard way. Live capture-health indicator, visible anytime, confirming capture is working the way it should. A clear flag the moment something shifts, instead of a quiet discovery weeks later. A public, dated changelog: every shipped fix and feature logged in one place. How it works for you Check the status before you lean on a scan for something that matters: a clean read means the data reflects what's actually on the page. Whenever something in the dashboard looks different, the changelog has a plain, dated answer for whether it's a bug or a shipped change. What you get Confidence that the data you're capturing today is actually accurate, confirmed rather than assumed. An early warning the moment a Facebook change affects capture, instead of a silent gap discovered weeks later. Visible proof that PostSnag is actively maintained, not a tool you're just hoping still works. For example Facebook quietly changes how it displays reaction counts on a post layout. The capture-health indicator flags the shift before you've pulled a single affected scan into a client deck, and the changelog already shows the fix logged with a date and a plain description. What it unlocks Trust in the underlying capture is what every other PostSnag feature depends on: the overperformance score, snapshot history, and AI breakdowns are only as good as the data feeding them. The changelog does the same job for the product as a whole, turning "is this still being worked on" into something you can just go look at. Who it's for Anyone using PostSnag for something that actually matters, a client report, a real business decision, a pitch, and anyone who's been burned before by a tool that quietly stopped working.

PostSnag about 16 hours ago

Scroll any Facebook profile, page, or group like you normally would, and PostSnag quietly turns every post you pass into structured, saved data. The problem Facebook gives you infinite scroll, not a spreadsheet: no searchable captions, no sorting by engagement, no export, nothing to filter or compare. Studying a competitor's post history means opening a dozen tabs and logging dates and captions by hand, so most people just go with a gut feeling instead. Tools that promise to automate this usually run a fake account behind the scenes, real risk just to see what's already on your own screen. What you actually want is simple: look at what you can already see, and keep it. What's live today The PostSnag extension captures posts the moment you scroll past them, on any Facebook profile, page, or group you can already access. No separate mode, no waiting: you browse, and PostSnag builds the record in the background. Everything runs client-side, inside your own logged-in session, with no server-side capture and no fake account involved. Post type: video, photo, text, or link Engagement numbers as shown on the post The full caption The post date How it works for you Open a profile, page, or group with the extension active and start scrolling; PostSnag reads each post as it loads and adds it to your capture, no clicking or manual logging required. When you're done, send that capture into your dashboard, where it becomes something you can actually sort through. What you get A full, structured record of any profile, page, or group's posts, built just by browsing normally. Zero added risk to your account, since nothing is automated and nothing acts on your behalf. Coverage that extends into groups, a space almost no other tool can see into at all. For example Before pitching a local business, you open their Facebook page and scroll back a few months the way you'd browse out of curiosity. By the time you've finished your coffee, PostSnag has captured every post from that stretch: what they posted, how often, and how it performed. What it unlocks This is the layer everything else in PostSnag sits on top of: every sort, filter, bookmark, and export starts as data that came from this exact moment, you scrolling, PostSnag quietly keeping what you saw. Who it's for Anyone who needs to understand a Facebook profile, page, or group beyond a quick scroll: marketers researching competitors, agencies prepping pitches, community managers, and creators studying their own history.

PostSnag about 16 hours ago

Download the original video and audio off any post you have captured, and export your captured Group data straight out of PostSnag, with broader export on the way. The problem Data you can't take with you isn't really yours. Research that lives only inside one dashboard means every deck, report, and client email gets built around manual copy-paste, exactly the work capturing data was supposed to save you from. Media is its own headache too: right-click-save doesn't work on Facebook video, and pulling just the audio was never straightforward. What's live today PostSnag lets you take your data and media with you: download the original video and audio, as a standalone MP3, from any post you've captured, on any profile, page, or group. Data export is live starting with Groups, with broader coverage on the way. Download the original video from any captured post. Pull just the audio as a standalone MP3, no separate conversion tool needed. Export your captured Group data today, wider coverage coming. How it works for you Open a post in your dashboard and download the video or MP3 directly, no screen recording or third-party downloader needed. Export your captured Group data into a file you can open and hand off anywhere. What you get The original video file from any post you've captured, not a screen recording. A clean MP3 pulled straight from the audio, ready for a transcript or reference. Captured Group data you can export and take with you today, no dashboard required. For example You find a post inside a tracked group where the video format clearly outperformed everything around it. Download the video to study the edit, pull the MP3 for the phrasing, and export the group's data alongside it, ready for a client presentation. What it unlocks Export and media download make PostSnag a research tool, not a walled garden. Your posts and their media are usable the moment you need them, and as export grows beyond Groups, that freedom extends to everything you capture. Who it's for Anyone who needs their Facebook research to leave the dashboard: agencies building client reports, creators pulling reference clips, and marketers who need the numbers in a spreadsheet or deck.

PostSnag about 16 hours ago

PostSnag tracks who a page tags and mentions across its posts, then turns that pattern into a clear map of its real partners and collaborators. The problem Watch any active page for a while and you'll notice it keeps tagging the same handful of accounts: a sponsor, a run of guest experts, a page it constantly cross-promotes with. That pattern is an honest signal of who a page actually works with, but it's scattered across dozens or hundreds of posts with nothing pulling it together. Today the only option is scrolling through a page's history yourself and tallying tags by hand, an approach that falls apart the moment you need to compare three or four pages at once, so most of this information, real sponsorships, real recurring collaborators, just sits there unused. What we're building PostSnag captures the accounts a page tags and mentions as part of the posts you're already capturing, then rolls it all up into a dedicated collaboration graph: a ranked, visual picture of who a page actually shows up next to, over and over. Every tag and mention captured alongside the post it appeared in. A ranked list of the accounts a page mentions most, with frequency and recency. A visual map of a page's most frequent connections, obvious at a glance. How it works for you Capture a page the way you always do, and a collaboration view is waiting in your dashboard: a ranked list of who gets tagged most, plus a graph radiating out from the page to its top connections. Click into any tagged account to see exactly which posts they appeared in. What you get A page's real network laid out clearly, instead of scattered across hundreds of captions. A ready-made list of who a page already trusts, perfect for warm outreach. The same view across multiple pages, so you can line up your network against a competitor's. For example A creator-marketing agency scouting partners for a skincare client pulls up the collaboration graph on three beauty pages: one tags the same two ingredient brands in nearly every other post, an instant shortlist instead of a week of manual scrolling. A local nonprofit runs the same check on a regional news page and finds nine tags in the past year, worth a direct pitch. What it unlocks Tagged-Account Insights adds a dimension nothing else in PostSnag covers: not what a page posts, but who it's connected to. It pairs naturally with side-by-side comparison, and across enough pages in one niche, the graph reveals the real web of who works with whom. Who it's for Agencies and marketers doing partnership or influencer outreach, and brand managers sizing up how competitors structure their sponsorships.

PostSnag about 17 hours ago

A day-by-hour grid built entirely from a page's own captured post history, showing exactly when its posts actually perform best, no generic advice involved. The problem Generic "best time to post" advice is an average across millions of unrelated accounts in every niche and timezone, and it says nothing about the one page you actually run or track. Finding a page's real best time means going through its own post history hour by hour, exactly the kind of tedious analysis that never actually gets done, so most people default to the listicle or whatever time felt convenient. The cost is real: a strong post published into a dead hour underperforms a mediocre post in a hot one, and because nothing separates the two, teams blame the content instead of the clock. What we're building A heatmap for every profile, page, or group you've captured: seven columns for days, twenty-four rows for hours, each cell colored by real engagement and overperformance using the same math PostSnag already applies to individual posts. Seven days across, twenty-four hours down: the full week at a glance. Each cell colored by real engagement and overperformance, so hot slots and dead zones are visible instantly. Built entirely from posts you've already captured, no separate scan required, and it sharpens with every capture. How it works for you Open a profile you've captured and switch to the heatmap view: PostSnag has already sorted every post by day and hour, so there's nothing to configure. Hover any cell for the exact numbers behind it, average engagement, post count, and how it compares to baseline. What you get A visual answer to when a page should post, built from its actual history, not generic advice. The same read on competitor pages, so you know when their audience is actually paying attention. Timing removed as an excuse: you can finally tell whether an underperforming post was the content or the send time. For example A regional retailer had been posting daily around noon because "lunchtime" is the advice everywhere. Their heatmap shows Sunday evenings between 7 and 9pm are the actual hottest window, running 2.5x their weekday-noon average, so they shift two posts a week into it and watch engagement climb within a month. What it unlocks The heatmap reads from the same overperformance score and captured history that power the rest of PostSnag, sharpening as your snapshot history deepens. It's a natural companion to scan-time alerts, since knowing when a page is about to enter its hot window is exactly when you want fresh data in hand. Who it's for Social media managers building a posting calendar around real evidence, agencies who need a defensible answer for a client, and anyone tracking competitors who wants to know when those audiences are actually paying attention.

PostSnag about 17 hours ago

A short weekly email built from what's already in your PostSnag library: your best post, your biggest overperformer, one real insight, and what's worth a fresh scan this week. The problem PostSnag only pays off if you actually look at it, and life gets busy enough that "I'll check the dashboard later" turns into weeks of not checking anything, while your library keeps growing with genuinely great posts sitting undiscovered. Nothing tells you which tracked profiles are actually stale and worth a fresh scan versus which ones you can leave alone, so you either re-check everything on a schedule that ignores how often each page posts, or you don't re-check anything until you happen to think of it. What we're building A short weekly email built entirely from what's already sitting in your PostSnag library, no new data collection, just a smarter surface for what you've already captured: Your best post of the week, the highest-scoring post you personally captured in the last seven days. Your biggest overperformer, the strongest post in your library, resurfaced in case you missed it. One real insight, a pattern pulled from your own captured history, not filler. A re-scan nudge, flagging which tracked profiles are likely stale based on their normal posting rhythm. How it works for you Once a week, a short email lands in your inbox: your best post, your library's strongest overall post, one real insight, and which profiles are probably overdue for a re-scan. Nothing requires logging in first; one click takes you into the dashboard if something's worth a closer look. What you get The work you already did, browsing, capturing, scanning, actually reaches you instead of sitting unread in your library. A genuine standout post gets a second chance to be seen, even if you missed it the week you captured it. A clear, cadence-based nudge on which profiles are actually worth re-scanning. For example You captured a competitor's page three weeks ago and moved on. That week's digest resurfaces a post from that capture sitting at 6.8x the page's normal engagement, and flags that the page is now eleven days past its usual five-day posting rhythm, so you queue a re-scan before lunch. What it unlocks The digest makes sure the work you already put into PostSnag doesn't go to waste, built entirely from your existing library and capture history. It's the difference between a tool that only works when you remember it and one that keeps working in the background of your inbox. Who it's for Anyone tracking more than a couple of profiles who doesn't have time to check the dashboard daily: marketers juggling competitors, agency account managers, and solo creators who want to stay sharp without babysitting a dashboard.

PostSnag about 17 hours ago

Export to JSON, Markdown, or XLSX, or skip the file entirely and copy a clean, ready-to-paste block straight into Claude or ChatGPT. The problem If your real analysis tool is an AI chat window, a CSV export is the wrong shape of file: you strip columns, fight the formatting, paste it in, and half the time the AI's first reply is a clarifying question instead of an analysis. That's friction between having the data and getting the answer, on work you already did the hard part of by capturing it. And CSV isn't even the right target for everyone: some people need clean JSON for a script, some want Markdown for a report, some want a real spreadsheet with proper columns, and right now everyone downstream does that translation by hand, every time. What we're building A wider export menu built around how people actually use captured data, plus a direct bridge into AI tools. The point isn't more file types for their own sake, it's matching the export to what actually happens next. JSON export, clean and structured, for scripts and custom tools. Markdown export, formatted tables ready to drop into a doc or report. XLSX export, a real spreadsheet file, not a CSV pretending to be one. A "Copy for Claude or ChatGPT" button that copies a clean, labeled block straight to your clipboard. How it works for you Filter your dashboard down to what matters, then either pick the file format that matches where the data is headed, or hit "Copy for AI" and paste straight into Claude or ChatGPT. Because the data arrives clean and labeled, you get a real answer on the first reply. What you get No more manual reformatting between exporting and actually analyzing. The right file format for the right destination, every time. One click from dashboard to clipboard to AI tool, nothing manual in between. For example You've captured a hundred and fifty posts across six competitor pages. Hit "Copy for AI," paste into Claude, and ask it to group posts by format and identify the top hooks in the top twenty percent by engagement; you get a defensible summary in minutes instead of the hour it used to take wrangling a CSV. What it unlocks AI-first export is the fast, manual version of where PostSnag is headed: a straight line from captured data to an answer, no spreadsheet detour. It sets up every future integration that plugs PostSnag directly into the AI tools people already live in. Who it's for Marketers drafting client reports, agencies building decks under a deadline, and creators wanting a fast first pass at what's working.

PostSnag about 17 hours ago

Views, the full reaction breakdown, engagement rate, and a pinned flag added to every export, plus the ability to export from any profile or your entire All Posts view, not only from Groups. The problem An export should be the moment you take PostSnag data somewhere else, into a report, a spreadsheet, a client deck, but what comes out today is thinner than the dashboard: the reaction total is there but not the breakdown, engagement rate is missing, and pinned posts look identical to everything else. The bigger limit is where you can export from: the option lives only on Groups, so a full export of a profile or your entire All Posts library means digging screen by screen instead of one pull. What we're building A richer export, and more places to trigger one from. Views, the full reaction breakdown, engagement rate, and a pinned flag, added as columns to every export. Export available from any tracked profile or page, not only Groups. Export available from your All Posts view, to pull your entire library in one file. How it works for you Export a profile you've tracked for months and the file includes every metric the dashboard shows: views, the full reaction mix, engagement rate, and a pinned flag. Filter All Posts to exactly the slice you want and export that selection in one pull. What you get Every metric you already see in the dashboard, present in the file itself. Engagement rate calculated for you, not rebuilt by hand in a spreadsheet. A one-pull export from All Posts, so a filtered slice becomes a single file. For example You're building a quarterly report covering four competitor pages: instead of four partial exports and an hour adding view counts and engagement rate by hand, you filter All Posts to those pages and the last ninety days, export once, and the columns are already there. What it unlocks The export is where PostSnag hands off to everything else you do, your spreadsheets, your reporting tools, your client decks, and a richer export means less rebuilding downstream. It also means you're never blocked from getting your own data out in the shape you need. Who it's for Agencies and marketers who live in spreadsheets and reporting decks, and anyone who's exported a file only to spend the next hour rebuilding numbers that should've been there.

PostSnag about 17 hours ago

Every post scored against that page's own normal, so "1,200 likes" becomes "3.4x what this page usually gets." The problem Raw engagement numbers lie constantly: 1,200 likes sounds like a hit until you learn the page averages 4,000, and 300 likes sounds forgettable until you learn the page normally gets 80. Follower size, posting frequency, and which era of growth a post came from all distort the raw count, so two posts with identical likes can be a runaway success on one page and a total dud on another. The only honest read is against that page's own baseline, and nobody keeps that math up by hand, so most people just eyeball the biggest numbers and end up studying a page's most-followed era instead of its best ideas. What we're building An overperformance score on every captured post: a single multiplier that compares it to that page's own recent average. The math disappears, and the answer sits right on the card. A post at 3.4 times the page's typical engagement reads "3.4x"; a flop reads "0.4x." Calculated from the history you've already captured, so it reflects that page's real baseline. The house metric across PostSnag: it ranks Discovery, drives alerts, and grounds AI breakdowns. How it works for you Every post in your dashboard carries the score automatically, no setup required. Sort any profile by overperformance to surface genuine breakouts, or filter to "above 2x" to cut a 500-post history down to the ten worth studying. What you get Instant clarity on what actually worked, audience-size distortion stripped out. A fair way to compare a tiny page and a massive page on the same scale. One consistent number across Discovery, alerts, and AI analysis. For example A competitor posts twenty times a week and most of it is filler. Sort by overperformance score and three posts jump out at 5x, 4.2x, and 3.8x while everything else sits near 1x, the pattern worth studying, found in ten seconds instead of an afternoon of scrolling. What it unlocks The overperformance score is the backbone of PostSnag's smartest features: it ranks Discovery, powers breakout alerts, and grounds the AI breakdowns. Build this one number well, and everything downstream gets sharper for free. Who it's for Creators reverse-engineering their own best posts, marketers tracking a shortlist of competitors, and agencies proving to a client why a post mattered.

PostSnag about 24 hours ago

Engagement calculated against follower count on every post and every profile, so a 5,000-follower page and a 5-million-follower page finally land on the same scale. The problem Raw engagement numbers are close to meaningless across profiles: a page with 5,000 followers pulling 400 likes is doing something impressive, while a page with two million followers pulling the same 400 likes barely got noticed by its own audience, yet sort by raw likes and the giant account buries the small account's best post every time. PostSnag already captures likes, comments, shares, and video plays well, but doesn't put those numbers in context against audience size, so today that means pulling a follower count from one place and doing the division yourself. Without a standardized rate you can't honestly answer who has the best content in a niche, since raw totals just point to the biggest audience, not the most compelling content. What we're building An engagement rate on every post and every profile PostSnag has captured, calculated as total engagement against follower count, one formula applied everywhere, so a rate on a 5,000-follower page means the same thing as one on a 5-million-follower page. The raw numbers stay exactly where they are; this is a second number doing the normalizing work you'd otherwise do by hand. Engagement rate on every individual post, shown right alongside the raw counts. A profile-level engagement rate, rolled up from captured posts. One consistent formula across every profile, so a rate never shifts meaning. How it works for you Every post you've captured shows its engagement rate next to the raw counts, and every profile carries a rate too, visible from your list of tracked profiles. Switch your sort to engagement rate and the ranking reorders around what actually matters. What you get A fair, apples-to-apples comparison between a small page and a massive one, every time. Engagement rate on every post, right next to the raw numbers, with no manual math. A sort option that reorders any list by engagement relative to audience, not raw totals. For example Two fitness pages post nearly identical workout videos the same day: Page A, with 400,000 followers, pulls 3,200 likes for a 0.8 percent rate, while Page B, with 12,000 followers, pulls 900 likes for a 7.5 percent rate. Sorted by raw likes, Page A wins by a mile; sorted by engagement rate, Page B is engaging its audience at nearly ten times the rate. What it unlocks Engagement rate becomes the common ground the rest of PostSnag's analytics build on: overperformance tells you a post beat that page's own history, engagement rate tells you how that audience stacks up against everyone else's. It also sharpens Discovery, letting a small, genuinely engaged account surface next to a giant instead of getting buried. Who it's for Anyone comparing accounts of different sizes: marketers benchmarking a client against competitors, creators sizing up whether their small audience is quietly outperforming bigger names, and agencies vetting partners on more than follower count.

PostSnag about 24 hours ago

A clear badge on every pinned post, plus a filter to isolate them, so you always know exactly what a page chose to put front and center. The problem A pinned post isn't like the others on a page: out of everything it's ever published, it's the one post the owner deliberately chose to plant at the top for every visitor to see first, the closest thing Facebook gives a page to a direct statement of what it wants you to see. Once a profile lands in your PostSnag dashboard, that signal disappears: the pinned post looks exactly like the hundreds around it, so knowing what a page currently has pinned means leaving PostSnag and checking manually, profile by profile. That gets expensive across twenty tracked profiles, and pins change, so miss the window and there's no record it ever happened. What we're building A clear, visible badge on any post that's currently pinned, shown the moment you open a profile, paired with a dedicated filter that isolates pinned posts across your entire library at once. Both read off data PostSnag is already capturing when you scan a profile. A visible badge on the post card and in the full post detail view. A dedicated filter to isolate pinned posts, layered with your existing filters. Captured automatically as part of the scan you're already running, no extra step. How it works for you Open any profile and the pinned post, if it has one, carries the badge right on the card. Switch on the pinned filter across your whole library and every tracked profile's featured post lines up together. What you get Instant visibility into what a page is currently featuring, with no trip to Facebook. A read on editorial intent, not just performance: what a page wants to be known for. Faster competitive research: skim what an entire niche is choosing to lead with at once. For example Researching ten home renovation contractor pages, you flip on the pinned filter and see seven of the ten are using their pin for a lead-capture offer, a free quote form or a guide, rather than a portfolio piece. That's invisible scrolling regular feeds one page at a time. What it unlocks The pinned badge plugs into how you already read a profile, and paired with snapshot history, a pin that changes over time becomes its own trend. Because the badge shows what a page believes is its best post while overperformance shows what actually performed best, running both together surfaces a real gap. Who it's for Marketers and agencies profiling competitors, researchers studying how a niche presents itself, and anyone who wants to know what a page is prioritizing without opening Facebook.

PostSnag about 24 hours ago

Two new sort and filter axes, view count and reaction type, so the most-watched or most-loved post in a library of thousands surfaces in seconds. The problem You've captured thousands of posts across the profiles you track, and somewhere in there is the most-watched video a page ever posted, or the post that pulled the most genuine love rather than the most engagement, but the only way to find it today is to scroll and eyeball. Sorting exists, but it's built around likes, comments, and date, not views or reaction type, so a question like "what did this page's most-watched video ever do" has no fast answer. It's a sorting gap, not a data gap. What we're building Two new axes to sort and filter across your saved posts, whether you're looking at one profile or your entire All Posts view. Sort any set of posts by view count, highest or lowest, to find a page's most-watched video. Filter and sort by reaction type to surface the most-loved posts, not just highest-total. Both work everywhere you already sort, from one profile to your whole library. How it works for you Open a profile you've tracked for months, sort by views, and its best-performing video is the first thing you see. Switch to reactions, pick "love," filter by date or format, and you've got a ranked list in two clicks. What you get A page's single most-watched post found in seconds, no matter how large the library. The ability to separate real positive sentiment from posts that just pulled a big number. Filters that stack: reaction type, date, format, and profile combine into one specific question. For example Studying a competitor's video strategy over a year, you sort by views and find their top result buried on page eleven by date, a video that pulled four times the views of anything else they posted that year. What it unlocks This is what turns captured data into something you actually use day to day, since view counts and reactions are only as useful as your ability to slice by them. It compounds with everything else PostSnag tracks, letting you stack filters into specific questions. Who it's for Anyone sitting on a large tracked library who needs an answer fast: researchers comparing competitors at scale, agencies pulling highlights on a deadline, and creators studying their own history.

PostSnag about 24 hours ago