Salesforce engagement report
@salesforce - 580K followers on X
Measured over 28 original posts from a 30-day window, last computed on August 26, 2026.
Engagement
A typical post picks up 30 interactions against 580K followers, an engagement rate of 0.005%. Measured over 28 original posts, its engagement rate beats 25% of 3,758 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 10K times each, and 0.292% of those impressions turn into an interaction. That is about 1.77% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.6 posts a day over the last 30 days, with activity on roughly 57% of days. Most posts go out around 19:00 UTC, and Wednesday is the busiest day of the week. Of the 28 posts sampled, 36% carry an image or video, 29% are part of a thread and 32% link out. The account's strongest tracked post pulled 168 interactions, about 5.6x its own typical post.
Measured over 28 original posts from a 30-day window, last computed on August 26, 2026.
Compared with accounts its own size
Salesforce's engagement rate beats 25% of the tracked X accounts closest to it in follower count (3,758 accounts, accounts of similar size (decile 8 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 23% 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 0.005%, Salesforce sits above the 10th percentile of the 36,521 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.012%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.002% |
| 25th percentile | 0.012% |
| 50th percentile | 0.08% |
| 75th percentile | 0.434% |
| 90th percentile | 2.10% |
| 99th percentile | 160.7% |
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 19:00 UTC, and Wednesday 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% | 50K |
| 01:00 UTC | -2% | 51K |
| 02:00 UTC | -3% | 50K |
| 03:00 UTC | -4% | 53K |
| 04:00 UTC | -6% | 43K |
| 05:00 UTC | -4% | 42K |
| 06:00 UTC | -4% | 48K |
| 07:00 UTC | -5% | 52K |
| 08:00 UTC | -4% | 60K |
| 09:00 UTC | -3% | 69K |
| 10:00 UTC | -2% | 72K |
| 11:00 UTC | -3% | 78K |
| 12:00 UTC | -2% | 86K |
| 13:00 UTC | -2% | 94K |
| 14:00 UTC | -4% | 97K |
| 15:00 UTC | -2% | 100K |
| 16:00 UTC | -3% | 97K |
| 17:00 UTC | -2% | 90K |
| 18:00 UTC | -1% | 84K |
| 19:00 UTC | -2% | 79K |
| 20:00 UTC | -1% | 74K |
| 21:00 UTC | -1% | 66K |
| 22:00 UTC | -2% | 57K |
| 23:00 UTC | -2% | 51K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +4% | 230K |
| Monday | 0% | 286K |
| Tuesday | -2% | 276K |
| Wednesday | -1% | 251K |
| Thursday | -1% | 244K |
| Friday | -3% | 252K |
| Saturday | +3% | 227K |
Best tweets
- Jul 27, 20265.6x their median
Building an AI agent is easy. Getting it to work in production is the hard part. The solution? Start simple. Scale fast. 👇 How to switch on a smart customer service agent—without risking your data–explained in under 60s.
- Jul 15, 20264.8x their median
Optimism in the Age of Agentic AI Every generation gets a great leap. This one is ours. Not because technology can do more. Because people can. Welcome to the Agentic Enterprise. Around the world, our customers are unlocking the potential of every employee. Human being. Agent doing. People bring creativity, judgment, relationships, and vision. Agents handle processing, integration, and execution, clearing the way for people to do the work only humans can do. The work that builds trust. The work that creates meaning. The work that brings you closer to every customer. That is the optimism of this moment. Profoundly human. Operationally agentic. Ironically, the more agentic your company, the more human it can become.
- Jul 23, 20264.0x their median
The future won’t be defined by AI. It will be defined by what people can do because of it.
- Jul 24, 20263.7x their median
Most AI agents: great at finishing tasks, terrible at telling you if any of it matters. “Loop engineering” gives an agent a goal and a way to measure progress, so it can plan, evaluate its work, learn, and adjust. When it works, an agent can complete more tasks on its own. But a task isn’t a business outcome. More closed tickets won’t tell you whether you built a better product or sold more of it. The metrics can look great while the result that matters goes unmeasured. The next frontier is aiming those loops at shared business outcomes—with sales, service, and marketing working toward the same goal instead of optimizing in separate corners. That only works if you can measure the outcome. And most companies already can. Years of pipeline stages, service levels, and lead definitions are sitting in their systems. You don’t need a new scoreboard. The business already is one. Your agents just need to learn against it.
- Aug 3, 20263.1x their median
Claude and ChatGPT can now securely access your Salesforce data 💪 We’re changing how you interact with your sales pipeline When your CRM goes headless: ↳ Instant Answers: Ask Claude for your top Q2 opportunities and pull live pipeline insights directly into your workflow ↳ Built-In Governance: No rebuilding security from scratch. Claude only sees what you have permission to see ↳ Enterprise-Grade Trust: Powered by the exact same sharing model that has protected your customer data—and kept interns out of board-level decks—for 25 years
- Jul 21, 20263.1x their median
Last week’s internet obsession: loop engineering. Now: graphs. @madhavtt made the case for the shift: instead of one agent looping, specialized agents route work to the right place. With Atlas, Agentforce orchestrates thousands of actions across the enterprise. https://t.co/MAisKAIVNf
- Jul 16, 20262.5x their median
Doctor’s orders. 🩺 https://t.co/KP6FAmSQZG
- Jul 27, 20261.8x their median
Unpack how AI Agents can transform the unboxing experience with real-world deployment lessons from @SharkNinja.
- Aug 11, 20261.8x their median
Everyone has opinions on AI agents. We have the data. Here are 5 numbers you need to know from the new Salesforce Agentic Enterprise Index. 🧵
- Aug 11, 20261.6x their median
95% of field service orgs are using AI. 66% say their mobile worker turnover went up over the last two years. New Salesforce research surveyed 2,317 field service leaders across 9 countries. The findings pull in two directions at once. 85% plan to spend even more on AI over the next two years. Companies using it for scheduling and dispatch already see 57% higher revenue per job and 57% higher worker productivity. But when leaders were asked why turnover keeps climbing, one answer beat every other: not enough training when new tech shows up. It compounds from there. 61% say their field techs don't have access to the customer data they need on site. So even the techs who got trained on the AI tools show up without the context to act on what those tools are telling them. Only 16% of these companies run field and back-office systems on one platform. The rest is patched together across mobile apps, GPS trackers, spreadsheets, some still on paper logs. And when these leaders pick an AI vendor, cost isn't top of the list. Transparency into how the AI decides, data security, and quality of support are. The AI is scaling faster than the people using it. If you run field ops: is your turnover problem actually a training problem wearing a different name? Curious what you're seeing.
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.
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Reading these numbers
A typical post picks up 30 interactions against 580K followers, an engagement rate of 0.005%. Measured over 28 original posts, its engagement rate beats 25% of 3,758 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 10K times each, and 0.292% of those impressions turn into an interaction. That is about 1.77% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.6 posts a day over the last 30 days, with activity on roughly 57% of days. Most posts go out around 19:00 UTC, and Wednesday is the busiest day of the week. Of the 28 posts sampled, 36% carry an image or video, 29% are part of a thread and 32% link out. The account's strongest tracked post pulled 168 interactions, about 5.6x its own typical post.
- What is Salesforce's engagement rate on X?
- Salesforce (@salesforce) has an engagement rate of 0.005%, based on the median interactions across 28 original posts from the last 30 days against 579,884 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.005%, Salesforce sits above the 10th percentile of the 36,521 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 @salesforce have real engagement?
- Its engagement rate beats 25% of the tracked X accounts closest to it in follower count (3,758 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 @salesforce post?
- Most posts go out around 19:00 UTC, and Wednesday is its busiest day, at roughly 1.63 posts per day across the measured window.