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Strategy engagement report

@MicroStrategy - 303K followers on X

Measured over 28 original posts from a 30-day window, last computed on September 5, 2026.

Engagement

Middle of its size range
Per follower
0.013%
of 303K followers
Per impression
0.398%
9.8K views on a typical post
Reach
3.23%
of its followers see a post
Typical post
39
interactions (median)
Saved
0.005%
0 bookmarks on a typical post
Posting rate
1.07/day
active 67% of days
Peak time
12:00 UTC
Monday

A typical post picks up 39 interactions against 303K followers, an engagement rate of 0.013%. Measured over 28 original posts, its engagement rate beats 29% of 6,493 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 9.8K times each, and 0.398% of those impressions turn into an interaction. That is about 3.23% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.1 post a day over the last 30 days, with activity on roughly 67% of days. Most posts go out around 12:00 UTC, and Monday is the busiest day of the week. Of the 28 posts sampled, 100% carry an image or video and 96% link out. The account's strongest tracked post pulled 88 interactions, about 2.3x its own typical post. Recurring topics include #semanticlayer, #ai, #datastrategy.

Measured over 28 original posts from a 30-day window, last computed on September 5, 2026. Recurring tags: #semanticlayer, #ai, #datastrategy.

Compared with accounts its own size

Strategy's engagement rate beats 29% of the tracked X accounts closest to it in follower count (6,493 accounts, accounts of similar size (decile 7 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 25% 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 0.013%, Strategy sits above the 10th percentile of the 65,864 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.016%.

p100.002%
p250.016%
p50 (median)0.1%
p750.499%
p902.09%
p99120.1%
Engagement rate as a share of followers, across the 65,864 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 57,191 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 percentile0.002%
25th percentile0.016%
50th percentile0.1%
75th percentile0.499%
90th percentile2.09%
99th percentile120.1%

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 12:00 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: 12:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 12:00 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 video100% of posts+111%+108% to +115%34K
Outbound link96% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 100% 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.
  • 96% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
  • Its average post runs 578 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

  • Aug 11, 20262.3x their median

    Hilton moved its complex analytics environment to Strategy Cloud, creating a more scalable foundation for its teams across 9,000+ properties and 120+ countries. By moving to the cloud, Hilton can spend less time managing infrastructure and more time improving the analytics experience across its global workforce. Read the full customer story to see how Hilton modernized its analytics environment and built a foundation for what comes next: https://t.co/Ctoji62kFw #CustomerStory #DataAnalytics #CloudAnalytics #EnterpriseAI #StrategyMosaic

    7495011K viewsView on X
  • Jul 29, 20262.2x their median

    As AI adoption accelerates, trusted data and governed business context become the foundation for delivering reliable insights. Franklin Templeton's AI journey started with a unified, governed data foundation. Following the acquisition of Putnam Investments, Franklin Templeton consolidated three separate analytics environments into a single Strategy-powered platform, creating consistent business logic, stronger governance, and a scalable foundation for AI. Read the full customer story: https://t.co/SVF8WCYk8c #CustomerStory #EnterpriseAI #DataGovernance #SemanticLayer #StrategyMosaic

    6886210K viewsView on X
  • Aug 6, 20261.7x their median

    Three out of four banks and financial institutions say inconsistent metric definitions limit their ability to scale AI. That is not just a reporting problem. When AI relies on conflicting business logic, it can generate inconsistent answers, recommend the wrong action and leave decision-makers without a reliable audit trail. The AI Context Gap in Banking, is a report based on a survey of 101 banking and financial services executives and decision-makers conducted by American Banker in April–May 2026. Read the report now and see what is keeping AI in pilot mode and what banks are doing to fix the problem: https://t.co/thNy3d6Zdd #Banking #FinancialServices #EnterpriseAI #DataGovernance #SemanticLayer

    5717011K viewsView on X
  • Aug 10, 20261.6x their median

    Benchmarks such as Spider and PICARD show only 70–80% text‑to‑SQL accuracy, and fall further on complex multi‑table enterprise queries. If AI is going to query your core data, this isn’t good enough. The problem isn’t prompting. It’s architecture. LLMs are guessing join paths from raw schemas. A semantic layer encodes the correct business logic once, so SQL is generated from governed contracts, not inference. Read more to find out why 70–80% accuracy isn’t good enough: https://t.co/PRByzrr0pE #TextToSQL #SemanticLayer #EnterpriseAI #DataGovernance #AIAccuracy

    5545010K viewsView on X
  • Aug 13, 2026

    A universal semantic layer gives every AI interface the same governed definitions, metrics, relationships, and access rules, while keeping execution deterministic. Read now to see why the future of enterprise AI depends on keeping business meaning consistent: https://t.co/1rKCoyN1Eq #EnterpriseAI #SemanticLayer #DataStrategy #AI #StrategyMosaic

    5026010K viewsView on X
  • Aug 4, 2026

    Diageo used Strategy to bring near-real-time insights and self-service analytics to teams around the world, helping them respond faster and create more personalized consumer experiences. Read the full customer story to see how Diageo is building a data foundation for faster, smarter decisions at scale: https://t.co/46WPpgCxW6 #CustomerStory #DataStrategy #EnterpriseAI #DataAnalytics #StrategyMosaic

    4653011K viewsView on X
  • Aug 3, 2026

    Even the strongest models fail without a shared, machine-readable understanding of your business — they guess at what “your top five customers” means instead of following governed definitions. Read “Ontology, Semantics, and Knowledge Graphs: The Context Layer Enterprise AI Is Missing” to find out: • How ontology defines the entities, attributes, and rules that shape your business domain • How semantics and a semantic layer turn ambiguous business terms into consistent, governed meanings • How knowledge graphs connect it all into a network AI can traverse to answer complex, multi-entity questions If AI is going to support real decisions, you can’t rely on model intuition about your data. You need a semantic foundation it can trust: https://t.co/mt2FTsrOot #EnterpriseAI #SemanticLayer #KnowledgeGraphs #DataGovernance #AgenticAI

    4436111K viewsView on X
  • Aug 25, 2026

    Tapestry transformed retail performance with Strategy’s mobile intelligence platform, giving teams across 500+ stores real-time, governed access to the metrics that matter. This led to a $2.2B record revenue year supported by a modern, data-first analytics foundation. Discover how Tapestry is turning data into action at retail speed: https://t.co/OpgN2zwBt3 #RetailAnalytics #DataIntelligence #MobileAnalytics #BusinessIntelligence #StrategySoftware

    4561110.0K viewsView on X
  • Jul 28, 2026

    Join François Dupont for a live webinar exploring how AI agents can move beyond chat interfaces to interact with enterprise systems, trigger workflows, and deliver real business outcomes, all while operating within a governed framework. See what's possible when AI agents are connected to the right foundation, register now: https://t.co/gw2M7X6zYV #AIAgents #EnterpriseAI #MCP #SemanticLayer #StrategyMosaic

    424609.7K viewsView on X
  • Aug 12, 2026

    In this live demo of Strategy Mosaic on August 18, 2026 @ 12:00 PM EST, Ryan Karlan, Associate Sales Engineer at Strategy, will show what changes when AI gets a governed semantic foundation instead of raw database schemas. If your AI is getting the numbers wrong, the problem may not be the model. It may be the context. 👉 Register for the live demo: https://t.co/yUy6EOfgo1 #StrategyMosaic #SemanticLayer #AgenticAI #EnterpriseAI #DataGovernance

    4451110K 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

#semanticlayer#ai#datastrategy#enterpriseai#strategymosaic

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 39 interactions against 303K followers, an engagement rate of 0.013%. Measured over 28 original posts, its engagement rate beats 29% of 6,493 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 9.8K times each, and 0.398% of those impressions turn into an interaction. That is about 3.23% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.1 post a day over the last 30 days, with activity on roughly 67% of days. Most posts go out around 12:00 UTC, and Monday is the busiest day of the week. Of the 28 posts sampled, 100% carry an image or video and 96% link out. The account's strongest tracked post pulled 88 interactions, about 2.3x its own typical post. Recurring topics include #semanticlayer, #ai, #datastrategy.

What is Strategy's engagement rate on X?
Strategy (@MicroStrategy) has an engagement rate of 0.013%, based on the median interactions across 28 original posts from the last 30 days against 303,424 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.013%, Strategy sits above the 10th percentile of the 65,864 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 @MicroStrategy have real engagement?
Its engagement rate beats 29% of the tracked X accounts closest to it in follower count (6,493 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 @MicroStrategy post?
Most posts go out around 12:00 UTC, and Monday is its busiest day, at roughly 1.07 posts per day across the measured window.

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