Ask the popular scheduling studies the same question and you get four different answers: Buffer says Sunday morning, Hootsuite says Thursday morning, Sprout Social says weekday afternoons, Later says 5 a.m. Most of them rank hours by engagement rates or blended scores. We think the only number a posting-time decision is really about is reach, so this study ranks every hour of the week by one thing: the views a post published in that hour goes on to collect.

Below are the full curves: median views by hour and weekday, the odds of a big hit by hour, the best and worst slots of the week, and how crowded each hour is. All hours are UTC; shift them by your audience's offset.

Key takeaways

• TikTok pays for evenings. The median post published 16:00 to 21:00 UTC collects 12,400 to 12,600 views, against 7,100 to 7,700 in the 05:00 to 07:00 trough, a gap of up to 77%. The odds of clearing 100,000 views follow the same curve, rising from about 1 in 6 in the early morning to better than 1 in 5 in the evening.
• Instagram pays for afternoons and Sundays. The median post published 14:00 to 17:00 UTC roughly doubles the views of the 08:00 to 09:00 trough (5,470 vs 2,633 at the extremes). Sunday posts run about a third above the weekday plateau, and Sunday afternoon is the single best window of the week.
• The "dead hours" are not where you think. Instagram's worst window is mid-morning, not midnight; overnight posts outperform 08:00 to 09:00 posts comfortably. On TikTok, midnight UTC is a strong slot, and the true dead zone is 04:00 to 08:00.

What did we measure, and why views?

Nearly 1 million public TikTok and Instagram posts tracked by buzzabout, split almost evenly between the two platforms, each reduced to the two facts that matter for this question: when it was published, and how many views it went on to collect. Posts too recent for views to have settled were excluded.

Why views and not engagement rate? Because reach is what a posting-time decision is supposed to buy. Engagement rate tells you how the audience that arrived reacted; views tell you how many arrived. A study about when to post should measure the arriving.

Everything below is medians and percentiles, never averages: view counts are heavy-tailed, and a handful of viral outliers will drag an average anywhere. The median answers the honest question, "what does the typical post published at this hour actually get?"

What is the best time to post on TikTok?

Evenings, clearly. Median views climb all afternoon, peak at 20:00 UTC, and hold a high plateau from 16:00 through midnight. The trough is the early morning: a post published at 06:00 collects a median 7,121 views against 12,600 at 20:00.

type: line
title: TikTok median views by publish hour (thousands, UTC)
labels: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23
values: 10.7, 9.1, 7.9, 7.4, 8.1, 7.6, 7.1, 7.7, 8.7, 8.7, 9.7, 10.6, 9.6, 9.3, 9.4, 10.9, 12.4, 12.5, 12.5, 12.0, 12.6, 11.5, 11.3, 10.8

The same shape holds at the top of the distribution, which is where marketers actually live. The share of posts that go on to clear 100,000 views rises from 16.4% at 06:00 to 21.3% at 21:00, roughly one extra big hit for every twenty posts, just from the publishing slot.

type: line
title: TikTok: share of posts clearing 100k views, by publish hour (%, UTC)
labels: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23
values: 20.7, 19.0, 18.5, 17.4, 17.8, 16.8, 16.4, 16.6, 17.1, 17.3, 18.2, 19.0, 17.9, 18.0, 18.6, 19.7, 20.9, 20.6, 20.7, 21.0, 21.1, 21.3, 20.6, 20.7

Two details worth noticing. Midnight UTC is not a dead hour: the median midnight post collects 10,700 views, above the daily average, and its big-hit odds (20.7%) match the evening. And the curve's message is a band, not a magic minute: everything from 16:00 to midnight performs within a few percent of the peak.

The best and worst slots of the week, from the full day-by-hour grid:

Note what is missing from the top of that table: weekends. On TikTok the day of the week barely moves the needle; the medians sit in a flat 10,300 to 10,600 band all week, and the strongest slots are weekday evenings.

type: columns
title: TikTok median views by weekday (thousands): the day barely matters
Mon: 10.6
Tue: 10.4
Wed: 10.5
Thu: 10.6
Fri: 10.3
Sat: 10.3
Sun: 10.4

What is the best time to post on Instagram?

Mid-afternoon, and Sunday. Instagram's hourly curve is steeper than TikTok's: the median post published at 16:00 UTC collects 5,470 views, more than double the 2,633 of the 08:00 trough. The productive band runs from about 13:00 to midnight.

type: line
title: Instagram median views by publish hour (thousands, UTC)
labels: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23
values: 4.3, 3.9, 3.7, 3.5, 3.2, 3.2, 3.2, 2.9, 2.6, 2.8, 3.3, 4.0, 3.9, 4.2, 4.6, 4.8, 5.5, 5.2, 5.1, 5.0, 5.0, 4.8, 4.8, 4.7

Big-hit odds tell the same story with more contrast: 8.3% of posts published at 09:00 go on to clear 100,000 views, against 13.1% at 16:00, a better than 50% improvement in the odds from the slot alone.

type: line
title: Instagram: share of posts clearing 100k views, by publish hour (%, UTC)
labels: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23
values: 11.9, 11.2, 10.8, 10.8, 10.5, 10.6, 9.8, 8.9, 8.5, 8.3, 9.7, 11.1, 10.7, 11.3, 12.1, 12.7, 13.1, 12.7, 12.6, 12.6, 12.7, 12.5, 12.4, 12.6

Unlike TikTok, the calendar matters here. Sunday's median (5,526 views) runs about 38% above Friday's (4,000), Saturday takes a smaller bump, and the weekday plateau is flat.

type: columns
title: Instagram median views by weekday (thousands)
Mon: 4.1
Tue: 4.1
Wed: 4.0
Thu: 4.0
Fri: 4.0
Sat: 4.7
Sun: 5.5

Put the two together and you get the week's crown: Sunday afternoon. The single best slot in the entire grid is Sunday 16:00 UTC at a median 7,866 views, with Sunday 14:00 to 18:00 filling the whole top five, nearly four times the worst slots of the week (weekday 07:00 to 09:00, medians around 2,000 to 2,400).

And the counterintuitive one: Instagram's dead zone is the mid-morning, not the night. A post published at 03:00 UTC (median 3,492 views) comfortably outperforms one published at 08:00 (2,633).

Do peak hours mean more competition?

Yes, but the crowd and the views do not peak together, and that gap is usable. Posting supply peaks in the mid-afternoon: around 15:00 to 17:00 UTC, roughly 7% of the day's posts drop every hour. After 20:00 the field thins fast, while the view curves above stay at or near their highs into midnight.

type: line
title: Share of all posts published by hour, TikTok (%, UTC)
labels: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23
values: 4.0, 3.6, 3.1, 2.5, 2.0, 1.8, 1.9, 2.2, 2.5, 2.9, 3.2, 3.5, 4.2, 4.8, 5.5, 6.4, 6.8, 6.7, 6.3, 6.0, 5.7, 5.5, 4.8, 4.3

type: line
title: Share of all posts published by hour, Instagram (%, UTC)
labels: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23
values: 3.0, 2.6, 2.3, 1.9, 1.8, 2.0, 2.5, 3.0, 3.4, 3.7, 4.1, 4.4, 5.4, 5.8, 6.4, 7.3, 7.6, 6.8, 5.8, 5.0, 4.4, 3.9, 3.6, 3.2

So the late evening (20:00 to 23:00 UTC) is the value corner on both platforms: views hold near peak while the hourly flood of new posts drops by a third or more. The early morning is the opposite trap: almost nobody posts at 05:00, and the posts that do land there collect the least views of the day. Low competition is not an edge when the audience is asleep.

Why do the "best time to post" studies disagree?

Line up the most-cited studies and ours:

Three reasons the answers differ. Different datasets: each study measures its own customers or tracked corpus, with its own mix of industries and audience geographies. Different metrics: an hour that wins on engagement rate is not necessarily the hour that wins on views, and most studies rank by rates or blended scores. Different clocks: some report local time, some "time-zone agnostic" scores; we publish plain UTC curves and let you shift them, which is more honest than pretending timezone effects away. Whichever table you borrow, including ours, treat it as a hypothesis to test on your own audience, not a law.

So when should you post?

1. On TikTok: publish between 16:00 and 21:00 in your audience's timezone. The band is worth up to 77% more median views than the early morning, and one extra 100k-view hit per ~20 posts. Weekday evenings top the grid; the day itself barely matters.
2. On Instagram: aim for 14:00 to 17:00, and use your Sundays. The afternoon band doubles the morning trough, Sunday adds about a third, and Sunday afternoon is the best window of the week. Never burn a good post at 08:00 on a weekday, it is the worst slot on the platform.
3. Consider the late evening on both platforms. Views hold near peak after 20:00 while the flood of competing posts thins by a third.
4. Treat every best-time table as a starting point, not a guarantee. These are patterns across a large dataset, and your audience is not the average. Run your own research before committing a content calendar to anyone's averages, including ours.
5. Do not let the slot outrank the content. A timing bonus is worth double digits at best; the difference between a post your audience wants and one it scrolls past is worth multiples. Spend accordingly: what you post beats when.

How do you run this test on your own account?

The whole method compresses to an afternoon with your own analytics export.

1. Export post-level data with timestamps and views. TikTok Studio and Instagram's professional dashboard both provide it. Under about 100 posts, any pattern you find is mostly luck.
2. Drop the most recent week. Fresh posts have not finished collecting views and will drag down whatever hours they landed in.
3. Bucket by publish hour and weekday, then compare medians, not averages. One viral outlier will bend an average around its slot; the median ignores it.
4. Check the top end too. Count how often you clear a threshold that matters to you (10k, 100k) per slot; big-hit odds can move even when medians barely do.
5. Ask how big, not whether. If your best and worst slots differ by a few percent, schedule for convenience and spend the effort on researching the pain points your audience talks about.

Frequently asked questions

Does posting time affect the TikTok algorithm?

Not as a ranking input, as far as TikTok has said. Its published explanation of the For You feed lists user interactions, video information, and device or account settings, and does not mention publish time: "User interactions such as the videos you like or share, accounts you follow, comments you post, and content you create" lead the list (How TikTok recommends videos #ForYou). What timing changes is who is scrolling during your first hours of distribution, and the curves above show what that is worth in views.

Is it bad to post at night?

The data says the opposite of the folk wisdom. On TikTok, midnight UTC posts collect a median 10,700 views with evening-grade big-hit odds; the real dead zone is 04:00 to 08:00. On Instagram, overnight posts comfortably beat the mid-morning trough: 03:00 outperforms 08:00 by about a third. The "post in the morning so people see it over the day" rule is the single worst-performing idea in this dataset. Instagram's own ranking explanation lists recency as just one signal among many (feed ranking explained).

Does the best time differ by country or niche?

Almost certainly. Every audience has its own geography and rhythm, which is why our curves are published in plain UTC for you to shift, and why any borrowed table travels badly. If you want to see when your specific niche's conversation actually happens, that is exactly a niche research run.

How often should you post instead of worrying about timing?

This study measured timing, not frequency, so we will not invent a number. The honest frame: frequency competes with content quality for the same production hours, and the timing curves above are worth double digits at best, while knowing what your audience actually responds to is worth multiples. Find a sustainable rate and invest the margin there.

Is there a best time to post on Reddit or YouTube?

We did not test them here. Reddit in particular should behave differently: distribution is driven by community voting inside each subreddit rather than a personalized feed, so timing interacts with each community's active hours. If we extend the study, this article will be updated with the same methodology.

Methodology

Data. Nearly 1 million public TikTok and Instagram posts tracked by buzzabout, split almost evenly between the platforms, extracted in July 2026. Each post contributes two facts: its publish timestamp and the views it collected. Posts too recent for views to have settled were excluded. The dataset enters through the searches and collections buzzabout users track, so it reflects the conversations marketing teams monitor; for a study meant to inform marketing decisions, that is the relevant population.

Statistics. Medians and percentiles throughout, because view counts are heavy-tailed and averages track outliers. Big-hit odds are the share of posts in a slot that go on to clear 100,000 views. Day-by-hour grid slots are reported only where the slot holds a large sample. All hours are UTC, the neutral reference for a global dataset; shift any window in this article by your audience's offset.

What these curves are. Population patterns: they describe the views that posts published at each hour actually collected across the whole dataset. They are the strongest starting hypothesis available at this scale, and they are not a controlled experiment on your account, which is why the article ends with a procedure for running exactly this analysis on your own data.

Want these curves for your own market instead of the global average? buzzabout runs this analysis continuously on the conversations you track, and the /trends network shows what is climbing right now.

Measurement stamp. Based on 287 posts from LinkedIn and Reddit, published July 22, 2025 to July 17, 2026, collected July 20, 2026 with buzzabout across 11 collection runs. 257 posts were about direct mail as a marketing channel; 30 off-topic posts were excluded from every number below. We classified each post's stance by hand and tagged every author by whether they sell direct mail services.

Search "is direct mail dead" today and the ranking pages are written by printers, direct mail agencies, and mail houses. All of them answer no. All of them sell direct mail. We sell social listening, not mail, so we split the conversation by conflict of interest and led with the voices that have nothing to gain.

What do marketers with no stake in direct mail say?

They lean positive, clearly but not unanimously. Of the 257 on-topic posts, 75 came from practitioners with no commercial tie to direct mail: marketers, founders, and business owners who buy channels rather than sell them. Among those 75, 39 said direct mail works, 4 said it is dead, 6 said it depends on execution, and 26 asked questions or shared tactics without taking a position.

type: bars
title: Stance of the 75 no-stake practitioner posts
Works: 39
No position: 26
It depends: 6
Dead: 4

The success stories cluster tightly. Warm audiences, not cold lists. Behavior-triggered sends, not batch-and-blast. High-value or local niches:

"This is the best marketing, ever. I'll LinkedIn fight anyone who disagrees. :) We sent some direct mail to a handful of customers, and it has been knocking it OUT OF THE PARK."

Kyle Lacy, SaaS marketing leader, on customer-gift mailers, LinkedIn, January 16, 2026

"We helped our client spend $1,200 on postcards and make $60,000 back."

Matthew Gal, agency marketer, on a win-back campaign to 10,000+ churned customers, LinkedIn, June 17, 2026

"Most people think direct mail is dead. But Alex Hormozi just sent me a fridge magnet that's pure marketing genius"

Daniel Bustamante, copywriter, LinkedIn, July 27, 2025

"Direct mail is once again helping drive our rapid growth."

Eric Breon, founder of Vacasa, now building Fairly, LinkedIn, May 9, 2026

The four "dead" verdicts are just as instructive, because they share a shape too: cold acquisition on a small budget, or acquisition economics that leak. A Pilates studio owner whose $500 campaign "didn't bring in a single client" while Google Maps drove 48% of her clients. A consultant advising a hypothetical $1,000 budget to skip purchased mailing lists entirely. And the most data-heavy negative post in the sample, from UK fundraising:

"The UK has 1.6 million fewer donors than it did in 2019. First time donor retention has fallen to 19%. That means for every 100 new donors a charity acquires, 81 of them will never give again. The acquisition pipeline is not just expensive... it's leaking."

Simon Walker, fundraising practitioner arguing cheaper acquisition routes now beat direct mail, LinkedIn, April 28, 2026

Read together: no-stake practitioners who reported results with warm, targeted, well-designed mail overwhelmingly reported it working. The ones who declared it dead tried it as cheap cold acquisition.

Should you just use email instead of direct mail?

Nobody in this conversation argues that. We flagged every post that explicitly compares direct mail against email or digital ads: 60 posts. 59 of them argue mail outperforms email, 1 says it depends, and zero argue "skip mail, email is enough." The comparison exists in this conversation purely as ammunition for mail.

Two honest qualifiers before you accept that at face value. First, 37 of the 60 comparison posts come from direct mail vendors. Second, people who are happy with email do not write "email vs direct mail" posts; the comparison genre self-selects for mail advocates. The absence of pro-email voices here does not mean email loses, it means the email-satisfied majority is silent in this framing.

The most-repeated evidence is a response-rate gap: direct mail around 4.4% versus roughly 0.12% for email. Unlike most stats circulating on LinkedIn, this one has a traceable source: several posts, like this one from a print franchise, attribute it to the ANA/DMA Response Rate Report. Most posts repeat the numbers without attribution. We did not independently verify the report, and response rate is not ROI: mail costs dollars per piece, email costs fractions of a cent, so a 30x response gap does not automatically make mail the better spend. No post in our sample engaged with that math seriously.

The more interesting practitioner argument is not mail versus email but saturation arbitrage, the same logic that took budgets INTO digital twenty years ago, now running in reverse:

"I was speaking with a legal firm this week that spends around $30,000 a month on Google Ads. For every client they acquire, they are barely covering the cost of acquisition."

Mellissah Smith, marketing agency founder, arguing community-targeted mail beats saturated search ads for that firm, LinkedIn, June 20, 2026

Who is behind the "direct mail works" chorus?

Mostly the industry itself, and the pattern is remarkably consistent. Across all 195 posts arguing direct mail works, 138 (71%) came from authors with a commercial stake: printers, mail houses, DM agencies, mail-automation platforms, postal operators. We classified the dataset in two independent batches, and the vendor share of the optimism came out at exactly 71% in both. The United States Postal Service alone has 4 posts in the sample. Royal Mail's marketing arm is here too.

type: donut
title: Who wrote the 195 "direct mail works" posts
Sells direct mail: 138
Practitioner, no stake: 39
Unclear: 18

The sharper number: of the 160 on-topic posts by direct mail vendors, not one is negative about the channel. Zero. When a population of 160 authors produces no negative takes, you are reading marketing, not measurement. That is not a reason to dismiss the channel; the practitioner data above stands on its own. It is a reason to discount the volume of the cheering.

Is conversation about direct mail growing or declining?

Growing. On-topic posts roughly doubled across the window: 69 in the last five full months of 2025 versus 163 in the first six months of 2026, with a sharp June 2026 spike.

type: line
title: On-topic direct mail posts per month (full months, n=245)
labels: Aug, Sep, Oct, Nov, Dec, Jan, Feb, Mar, Apr, May, Jun
values: 8, 19, 16, 19, 7, 19, 21, 24, 18, 28, 53

Caveats, honestly stated: conversation measures discussion, not spend. Vendors post as category marketing, so part of this curve is advertising. And within the sample sits a post making exactly this distinction:

"Australia Post projects direct mail volume to drop 11.1% in 2025/26 yet direct mail is simultaneously being called a cornerstone channel for 2026. That's not a contradiction. It's a split in the market."

Reacon Group, LinkedIn, June 30, 2026

Talk is rising while aggregate mail volume, at least in Australia's projection, falls. Fewer senders, louder advocates, more sophisticated campaigns is a consistent reading of both curves.

What does the direct mail conversation actually argue about?

The clustering engine grouped 234 of the posts into 7 recurring narratives. The dominant one, 38% of the grouped conversation, is the tactile argument: physical mail commands attention and memory in a way saturated digital feeds cannot.

type: bars
title: Share of 234 clustered posts by narrative
Tactile attention and brand recall: 38
Data-driven targeting and personalization: 17
Campaign economics and ROI: 15
Omnichannel integration: 11
B2B, ABM and strategic gifting: 9
Digital-to-physical attribution tech: 6
Retention and reactivation: 5

"Let's settle this: Direct mail isn't making a comeback. Digital fatigue is."

Mittera (print and marketing company), LinkedIn, March 12, 2026

"Everyone obsesses over cost-per-piece (CPP) in RFPs. Remember that your CAC = CPP / Net Response Rate (NRR). A "cheaper" piece that hurts your response rate raises CAC"

Rich Walker, who runs prescreen direct mail at fintech Aven, LinkedIn, January 20, 2026

A cluster that grew across the window: B2B account-based marketing and strategic gifting (9%), where mail is a door-opener for named accounts rather than a mass channel. Its sharpest critic is a vendor in the same business:

"Controversial take. Sending gifts to someone's home address without asking is creepy."

Ben Smith of gifting platform Reachdesk, LinkedIn, January 23, 2026

Where do LinkedIn and Reddit disagree?

On almost everything. LinkedIn asserts; Reddit asks. Of 233 on-topic LinkedIn posts, 208 take a position (192 of them "works"). Of 24 on-topic Reddit posts, 21 take no position at all: practitioners asking whether mail works for their niche, which vendor to use, or what format converts. Zero Reddit posts call the channel dead; only 3 vouch for it. The Reddit pool stayed small even after seven dedicated collection passes over 12 months, which is itself a finding: direct mail is a LinkedIn conversation and a Reddit question.

The Reddit threads read like a buyer's due-diligence channel:

"I've been seeing mixed opinions lately about cold calling,PPL ,Facebook ads and direct mail for finding motivated sellers, so for people actively wholesaling, what's currently bringing in the best quality leads at the lowest cost?"

u/Great_Juice_4916, r/WholesaleRealestate, May 13, 2026

"Playing with the idea of handwritten notes / cards. Feels different, but also might it just ends up in the bin before it reaches the right person."

u/Bright_Hall_6302, r/sales, July 17, 2026

"Started looking into direct mail recently for one of my businesses and was kind of shocked at how broken every option is or it just feels weird to use."

u/Prestigious331, r/smallbusinessUS, June 20, 2026

The single most data-shaped Reddit post supports "alive but harder":

"We noticed from 2021 on, direct mail campaigns, although still very successful, have reduced in turnover. Pre-2021 our campaigns usually produced 10-15x returns, last year was 6x."

u/TheDapperAgents, who runs 4 real estate teams, r/realtors, January 27, 2026

Who are the loudest voices on direct mail?

We ranked authors by total engagement (likes plus comments plus shares) on their on-topic posts, and split them by stake. First, the practitioners, the table that matters more if you are deciding:

And the vendor side, led by the postal system itself:

Does direct mail still work in 2026? A read for deciders

The honest synthesis: the channel is alive, discussion of it is growing, and the practitioners with nothing to sell lean clearly positive, roughly 10 to 1 among those who took a position. But the conversation's volume is inflated by a vendor chorus that produced zero negative takes in 160 posts, and the on-the-ground mood on Reddit is cautious question-asking, not celebration. If you are deciding whether to fund direct mail, the sample's patterns are more useful than its verdict:

• Where no-stake practitioners reported success: mail to warm audiences (customers, churned customers, known accounts), triggered by behavior; high-LTV or local verticals (real estate, home services, legal, nonprofit); creative that means something to the recipient rather than generic postcards.
• Where they reported failure: one-shot, small-budget cold drops, and acquisition programs whose retention economics leak (the UK fundraising case).
• What the skeptics inside the industry warn about: bad address data quietly eating budgets, and home-address prospecting crossing privacy lines.
• On email versus mail: nobody in 287 posts argued for replacing mail with email, but the comparison genre is mail-advocate-selected and response rate is not ROI. Run your own cost-per-acquisition math; no post in this sample did it for you.

Emotionally the conversation is flat: sentiment analysis reads 89% of the emotional tone as neutral (n=257). Nobody is angry at direct mail in 2026, and nobody is euphoric. It reads like a tool being re-priced, not a movement.

How we measured this

We collected public posts with buzzabout, our own social listening engine, across 11 collection runs on July 20, 2026: sources LinkedIn and Reddit, window July 22, 2025 to July 17, 2026, English only, seeded with three neutral research prompts and over 40 keyword fragments (from "direct mail roi" and "postcard marketing" to "EDDM", "yellow letters", and "direct mail vs email"). Deduplicated, that returned 287 posts: 254 LinkedIn, 33 Reddit. We hand-classified each post's stance (works / dead / mixed / no position / off-topic) and each author's stake (sells direct mail / practitioner / unclear) in two independent batches, flagged explicit email-comparison posts, excluded 30 off-topic posts, and ran narrative clustering over the dataset. Every quote is verbatim, including typos, and linked to its source.

Limitations, plainly. LinkedIn dominates the sample 10 to 1; the aggregate numbers mostly describe LinkedIn. The Reddit pool stayed at 33 collected posts despite seven Reddit-specific collection passes with varied vocabulary; our final three collection runs across both platforms added only 10 net-new posts, so we are confident the accessible pool was exhausted, but search coverage limits may still hide some discussion. Post comments were not available for analysis through our public API, so comment threads (where much of Reddit's actual opinion lives) are not counted. Engagement is a point-in-time snapshot. Stance and stake labels involve judgment calls. And we are a social listening vendor: this article is itself a demonstration of our product, a bias you should price in exactly the way we priced in the printers'.

Want to run this kind of analysis on your own market? That is what buzzabout does. For more of our first-party research, see the best time to post on TikTok and Instagram, measured in views or how a dog accessories brand grew revenue 139%.

Results

Cute dog content rules the web. Our friends from Deviation and their client, BullyBillows, dog accessory brand, discovered how to turn hidden user intent and social search insights into a 139% revenue increase in 3 months.

-**139%**organic revenue achieved -**65%**increase in BullyBillows searches -**195%**increases in BullyBillows + [key term] searches

Client's Review

"buzzabout has become more than just a tool for our agency. It's a research engine, empowering our team to map cultural conversations, uncover rising trends, and spot shifts in user intent long before they surface in traditional search data."

— Ashley Liddell, Co-founder at Deviation

"buzzabout helped us understand what people were actually talking about. And it gave us all these different conversational topics we could lean on to grow BullyBillows on TikTok, Reddit, Instagram, and all these other places."

— Sam Broadhead, Co-founder at Deviation

Challenge

BullyBillows had it all: premium products, a loyal community, and brand ambassadors who genuinely loved promoting them.

On paper, the growth story looked obvious. But it wasn't clicking.

Their TikTok content wasn't surfacing in the right searches.

Their website was buried deep in search results…

And even with stronger SEO alone, the traffic upside wouldn't have matched the true scale their brand deserved.

When Deviation stepped in, they uncovered the core challenge:

Are searches reducing? Or are they migrating? — Ashley Liddell, Co-founder at Deviation

BullyBillows wasn't showing up where people were actually searching.Search wasn't just about Google anymore.

To win in a changing search landscape, BullyBillows needed a system built for the new search universe — one that plugged them directly into the millions of conversations happening daily across TikTok, Reddit, Instagram, and beyond.

Conversations to Conversions

So, how did Deviation help BullyBillows grow?

They started with building a comprehensive intent research. It included full deep dive in conversations happening around the dog industry. Not "discussions" in the articles on Google, but the real person-to-person communication on social media platforms.

And that's where buzzabout.ai came in.

Step 1. It all started with Reddit.

Reddit is the perfect place to discover what people are buzzing about. Thus, before running any campaigns, the Deviation team immersed themselves in the natural flow of conversations.

With buzzabout.ai, they scanned subreddits where dog owners talked about training, accessories, and daily struggles.

The tool helped them:

• analyze posts and comment threads at scale
• detect pains and needs (dangling wires, durability, comfort)
• map gains and wants (better training, safer walks, stylish gear)
• pick up exact audience language and phrasing
• follow user journeys — how one question grew into ten more
• spot competitor mentions and how users reacted to them

With just one search, Deviation team had a crystal-clear picture of key topics that mattered most to the community of dog owners.

Step 2. Build topic clusters

Once the intent signals were clear, the team fed seed keywords into buzzabout.ai.

In under 10 minutes, they generated several reports packed with crucial metrics (it would've taken days to compile manually).

Key metrics their team analyzed:

• total engagements
• engagement rate
• total views & potential reach
• content density
• emotions breakdown
• content type breakdown
• related keywords
• mentions
• audience segments

"Within this conversation around dog harnesses, we've recognized that there's a further opportunity to explore hiking with dogs. It turns out that a lot of the intent around dog harnesses is understanding hiking with dogs."

— Ashley Liddell, Co-founder of Deviation

Instead of surfing 1,000s of posts… they got structured data telling them where to look next.

Step 3. Talk to your audience

The team sat down with these reports and started mapping the big picture:

• Which pains and concerns kept resurfacing?
• What trends are rising? Can we see the similar patterns in several seed keywords?
• Which interests could be linked back to BullyBillows' product line? How do they align with the brand?

At this stage, our AI assistant helped them to structurize raw data from the report.

Inside the app, you are able to chat with your target audience and get the answers to your questions as if you were directly asking a dog owner to elaborate on specific topics.

Step 4. Clusters to intent pillars

Next came clustering. Deviation grouped the motivations into 3–5 intent pillars and ensured there was a clear focus on one goal: pain, gain, want, need.

Each pillar was:

• named and clearly defined
• backed with real evidence (screenshots, quotes, numbers)
• mapped to channels where those conversations were happening

Pro move: tracking language shifts = seeing cultural and intent evolution in real-time

Deviation also used buzzabout.ai to track shifts in language (e.g. dog training → force-free training → positive reinforcement) to make sure they were always a step ahead.

Step 5. Turn insights into content

Finally, those intent pillars were turned into content. Multi-channel campaigns targeted TikTok, Instagram, Reddit, and YouTube.

Their videos became viral on TikTok. One of their videos gained 1M views on Instagram!

They were mentioned in discussions on Reddit (fun fact: BullyBillow's were even noticed in one of the reports in buzzabout.ai – good sign!).

All this came from finding that keyword. These super specific & narrow keywords aren't easy to catch… but once you do, every door opens for you.

Results

-139% organic revenue achieved in 2025 -65% increase in BullyBillows searches -195% increase in BullyBillows + [key term] searches

Key Lessons

1.**Searches aren't reducing, they are probably migrating.**Search now is more than googling. Search now happens everywhere — TikTok, Reddit, YouTube, Instagram, LinkedIn and tens of other social networks. The more platforms you cover, the better data you get.

2.**The true intent lives beyond Google.**You'll never find a true intent by googling. Typing dog training into search engine gives you too broad results. But on TikTok SEO, the real intent might show up as positive reinforcement or force-free training. buzzabout.ai uncovers these hidden & niched-down terms within minutes.

3.**Notice how language changes and catch insights.**Marketers often ignore how small wording changes shape big intent. And Deviation team knew that's where the gold is. They went deep into conversations with buzzabout.ai and watched how users express their pains and needs.

buzzabout.ai is your fastest way from conversations to conversions. Want the same success? Start using buzzabout.ai to extract valuable marketing insights from social media.