Strategy engagement report
@MicroStrategy - 303K followers on X
Measured over 14 original posts from a 30-day window, last computed on October 17, 2026.
Engagement
A typical post picks up 33 interactions against 303K followers, an engagement rate of 0.011%. Measured over 14 original posts, its engagement rate beats 25% of 20,444 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 9.0K times each, and 0.368% of those impressions turn into an interaction. That is about 2.96% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.47 posts a day over the last 30 days, though only 43% of days saw any activity at all. Most posts go out around 12:00 UTC, and Friday is the busiest day of the week. Of the 14 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 87 interactions, about 2.6x its own typical post. Recurring topics include #ai, #businessintelligence, #dataanalytics.
Measured over 14 original posts from a 30-day window, last computed on October 17, 2026. Recurring tags: #ai, #businessintelligence, #dataanalytics.
Compared with accounts its own size
Strategy's engagement rate beats 25% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 9 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 21% 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 0.011%, Strategy sits above the 10th percentile of the 204,798 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
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 Friday 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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 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 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
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.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 100% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 100% 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.
- 100% 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 404 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, 20262.6x 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
- Jul 29, 20262.5x 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
- Sep 16, 20262.2x their median
Yesterday, we had a great day at CDAO FSI UK, connecting with data and AI leaders across financial services and insurance to discuss the opportunities and challenges shaping the industry. Nick Barth took the stage to explore what a semantic layer can really do for organizations, and the key questions CDOs should be asking before investing in one. The conversation doesn’t stop here. We’re looking forward to continuing the discussions with everyone we met and exploring these ideas in more detail! #CDAOFSI #Data #AI #SemanticLayer #FinancialServices #Insurance #DataStrategy
- Sep 17, 20262.1x their median
How can federal agencies adopt tokenization without adding complexity to their security and compliance frameworks? As federal agencies explore blockchain and digital asset infrastructure, integrating these capabilities with existing systems can create challenges around compliance, auditability, data accounting, and security. Join Strategy’s Asim Lilani, VP of Value Engineering, and Ian Yorkilous, Area VP of Public Sector, for today’s webinar at 2–3 PM ET / 11 AM–12 PM PT with Carahsoft “Unlock Secure AI: Tokenization Strategies for Federal Agencies.” You’ll learn how Strategy’s Tokenomics Solution can help agencies: 🔹 Align token models with federal mandates and Zero Trust standards 🔹 Streamline asset and data accounting across complex environments 🔹 Integrate tokenized workflows with existing legacy systems and cloud platforms Reserve your spot: https://t.co/63kf5dhLNe #AI #Tokenization #FederalGovernment #DataGovernance #Cybersecurity #PublicSector
- Aug 6, 20262.0x 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
- Aug 10, 20261.9x 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
- Aug 13, 20261.8x their median
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
- Aug 25, 20261.7x their median
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
- Aug 4, 20261.6x their median
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
- Aug 3, 20261.6x their median
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
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
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 33 interactions against 303K followers, an engagement rate of 0.011%. Measured over 14 original posts, its engagement rate beats 25% of 20,444 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 9.0K times each, and 0.368% of those impressions turn into an interaction. That is about 2.96% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.47 posts a day over the last 30 days, though only 43% of days saw any activity at all. Most posts go out around 12:00 UTC, and Friday is the busiest day of the week. Of the 14 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 87 interactions, about 2.6x its own typical post. Recurring topics include #ai, #businessintelligence, #dataanalytics.
- What is Strategy's engagement rate on X?
- Strategy (@MicroStrategy) has an engagement rate of 0.011%, based on the median interactions across 14 original posts from the last 30 days against 302,616 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.011%, Strategy sits above the 10th percentile of the 204,798 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 25% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the bottom quarter for its size 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 Friday is its busiest day, at roughly 0.47 posts per day across the measured window.