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Varinder Bansal ๐Ÿ‡ฎ๐Ÿ‡ณ engagement report

@vbomkara - 457K followers on X

Measured over 21 original posts from a 30-day window, last computed on October 27, 2026.

Engagement

Middle of its size range
Per follower
0.08%
of 457K followers
Per impression
1.12%
32K views on a typical post
Reach
7.11%
of its followers see a post
Typical post
365
interactions (median)
Saved
0.08%
26 bookmarks on a typical post
Posting rate
2.3/day
active 40% of days
Peak time
08:00 UTC
Monday

A typical post picks up 365 interactions against 457K followers, an engagement rate of 0.08%. Measured over 21 original posts, its engagement rate beats 67% of 21,185 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 32K times each, and 1.12% of those impressions turn into an interaction. That is about 7.10% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.3 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 08:00 UTC, and Monday is the busiest day of the week. Of the 21 posts sampled, 33% carry an image or video and 10% link out. The account's strongest tracked post pulled 5.2K interactions, about 14x its own typical post. Recurring topics include #cnbc, #india, #indiausties.

Measured over 21 original posts from a 30-day window, last computed on October 27, 2026. Recurring tags: #cnbc, #india, #indiausties.

Compared with accounts its own size

Varinder Bansal ๐Ÿ‡ฎ๐Ÿ‡ณ's engagement rate beats 67% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 10 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.

On engagement per impression rather than per follower it beats 50% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.

Where this sits in the catalog

At 0.08%, Varinder Bansal ๐Ÿ‡ฎ๐Ÿ‡ณ sits above the 25th percentile of the 212,567 accounts in this comparison. That places it in the below the median band, which runs 0.025% to 0.146%.

p100.004%
p250.025%
p50 (median)0.146%
p750.696%
p902.61%
p9982.7%
Engagement rate as a share of followers, across the 212,567 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,364 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.004%
25th percentile0.025%
50th percentile0.146%
75th percentile0.696%
90th percentile2.61%
99th percentile82.7%

This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built

Posting timing

This account posts most often around 08:00 UTC, and Monday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 08:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 08:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%89K
01:00 UTC-2%90K
02:00 UTC-3%88K
03:00 UTC-4%94K
04:00 UTC-5%76K
05:00 UTC-4%75K
06:00 UTC-5%86K
07:00 UTC-5%93K
08:00 UTC-4%108K
09:00 UTC-4%124K
10:00 UTC-3%129K
11:00 UTC-3%141K
12:00 UTC-3%154K
13:00 UTC-3%167K
14:00 UTC-4%173K
15:00 UTC-2%176K
16:00 UTC-3%171K
17:00 UTC-3%159K
18:00 UTC-2%149K
19:00 UTC-2%141K
20:00 UTC-1%131K
21:00 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Monday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Monday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Formats this account uses

Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video33% of posts+111%+108% to +115%34K
Outbound link10% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 33% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
  • 10% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
  • Its average post runs 429 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.

These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.

Best tweets

  • Oct 26, 202614x their median

    Senior officials from Iran, Pakistan, Tรผrkiye and Saudi Arabia have begun a four-way meeting in Tehran, hosted by Iranโ€™s Supreme National Security Council Secretary Mohsen Rezaei. Participants include Pakistanโ€™s Army Chief Asim Munir, Saudi Defense Minister Khalid bin Salman and Turkish Intelligence Chief Ibrahim Kalin.

    4.0K8271551971.3M viewsView on X
  • Oct 19, 20263.8x their median

    #CNBC-TV18Exclusive | 'No Guarantee FIIs Will Return...No One Taxes FIIs As We Do' Vallabh Bhanshali Of Enam Group, To CNBC-TV18 -Govt must re-look at taxation of FIIs to attract foreign capital -LTCG should never have been there, look at the damage it has done @ShereenBhan #VallabhBhanshali #FII #ForeignInvestment #CNBCTV18Market

    9892707544161K viewsView on X
  • Oct 26, 20263.4x their median

    JUST IN: Centre is considering a cut in the 12.5% LTCG tax on Equities ahead of Budget FY28 https://t.co/5OwJ57VQXh

    9749310465155K viewsView on X
  • Sep 2, 20262.6x their median

    1. It is not appropriate to compare GDP data across various series. Since the GDP rebasing, GDP data for Q1 (June quarter) FY26 has been estimated at 75L crores (or 80 trillion), vs. 81 lakh crores (Rs. 81T). This gives us a real growth rate of ~ 7.8 % . It would be incorrect to compare the GDP number generated by the 2011-12 series with that of the 2022-23 series. This would be comparing Apples to Oranges. 2. โ For instance, letโ€™s compare the first advance estimates (FAE) of FY26. Under the 2011-12 series, the GDP number was Rs. 201 lakh crores. However, under the new series, this number (the second advance estimates) is Rs. 322 lakh crores. No one is claiming that the economy grew by 60% ! This is the problem when we compare the old series to the new one. 3. โ Even if we look at nominal prices, then estimates for FY26 were 357 lakh crores under the old methodology, and Rs. 345 lakh crores under the new methodology. This does not mean the economy has contracted in nominal terms; it merely reflects the updated methodology. 4. โ This needless controversy is reminiscent of 2015, when the 2011-12 series was released, and growth estimates were questioned. The fact remains that base-year changes are necessary to capture the economyโ€™s updated structure and dynamics. Since 2015, digital payments, GST, and digitisation have emerged, producing much more data and providing a far more comprehensive picture of the economy.

    69421049978K viewsView on X
  • Sep 2, 20262.5x their median

    TAKE A BOW RBI! ๐Ÿ‡ฎ๐Ÿ‡ณ India hits a massive $136 Billion in forex inflows under FCNR, ECB, and overseas foreign currency borrowing as of August 31, 2026.FCNR deposits alone stand at a staggering $127 billion! ๐Ÿš€๐Ÿ’ฐ #RBI #Economy #Forex #India #Finance

    711911072172K viewsView on X
  • Oct 26, 20261.8x their median

    You can make only one guess for this- which is the emerging market in the world where foreign investors are most( absolute number 1) overweight? Hint: It's country's ETF is currently down 27 pct in thin trading in NYC.

    55126845149K viewsView on X
  • Oct 21, 20261.7x their median

    There is a fair chance that recent outperformance of mid-caps and small caps may hurt the investors much more than the large caps now.

    5451358671K viewsView on X
  • Oct 27, 20261.7x their median

    "I have never in my career seen this quantum of underperformance in such a short period. It has destroyed careers and blown up funds. There are numerous funds that have destroyed 10-yr track records in the last 24 months by simply being overweight India." writes Mr Akash Prakash. https://t.co/E7El8GZQwF

    47792222580K viewsView on X
  • Sep 22, 20261.6x their median

    Most people are either great investors or great founders. Very few have the genius to excel at both and scale a company to an IPO & in such a short time. Exceptional leadership in action. Congratulations @SunilBSinghania sir ๐Ÿซก https://t.co/4tlawYS2wR

    5661718145K viewsView on X
  • Aug 12, 20261.6x their median

    In investing, doing nothing is also a decision. And often, it is the hardest one. Markets constantly tempt us to act. A stock falls โ€” should I sell?โ€จIt rises sharply โ€” should I chase it?โ€จSomeone else is making money โ€” what am I missing? FOMO feeling โ€จThe news changes โ€” should I change my portfolio? But activity and progress are not the same thing. Over time, Iโ€™ve realised that some of the best investment decisions were not brilliant buys or perfectly timed exits. They were simply periods when we had done the work, understood what we owned, and had the patience not to interfere with compounding. Of course, doing nothing should never mean ignoring facts. When the business changes, management integrity/governance is questioned, capital allocation deteriorates, or the original thesis breaks โ€” act decisively. But when only the price changes while the thesis remains intact โ€” patience can be a competitive advantage. Investing is a strange profession. We are paid to make decisions, yet sometimes the best decision is no decision at all. This is why the process matters so much. Research gives you conviction. Risk management keeps you alive. And patience allows compounding to do its work. #Investing #LongTermInvesting #InvestmentPhilosophy #Compounding #RiskManagement #IKIGAI

    48876111364K viewsView on X

Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.

Recurring topics

#cnbc#india#indiausties#tehran#us

The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.

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Reading these numbers

A typical post picks up 365 interactions against 457K followers, an engagement rate of 0.08%. Measured over 21 original posts, its engagement rate beats 67% of 21,185 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 32K times each, and 1.12% of those impressions turn into an interaction. That is about 7.10% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.3 posts a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 08:00 UTC, and Monday is the busiest day of the week. Of the 21 posts sampled, 33% carry an image or video and 10% link out. The account's strongest tracked post pulled 5.2K interactions, about 14x its own typical post. Recurring topics include #cnbc, #india, #indiausties.

What is Varinder Bansal ๐Ÿ‡ฎ๐Ÿ‡ณ's engagement rate on X?
Varinder Bansal ๐Ÿ‡ฎ๐Ÿ‡ณ (@vbomkara) has an engagement rate of 0.08%, based on the median interactions across 21 original posts from the last 30 days against 456,800 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.08%, Varinder Bansal ๐Ÿ‡ฎ๐Ÿ‡ณ sits above the 25th percentile of the 212,567 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
Does @vbomkara have real engagement?
Its engagement rate beats 67% of the tracked X accounts closest to it in follower count (21,185 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
When does @vbomkara post?
Most posts go out around 08:00 UTC, and Monday is its busiest day, at roughly 2.3 posts per day across the measured window.

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