20 Business Processes You Can Automate With One Slack Message
Key Takeaways
- Every example includes the exact Slack prompt you can copy and paste. No abstract categories, no "imagine if." Twenty real business process automation examples, each triggered by a single message.
- Each example names the specific tools involved. Stripe, HubSpot, Apollo, Meta Ads, Google Sheets, PostHog, Linear, and more. You see exactly what connects to what.
- The manual version of each process takes 20-90 minutes. The automated version takes one message. The comparison table at the end breaks down all 20 side by side.
- Organized by department so you can skip straight to your pain. Sales, marketing, operations, finance, and HR each get four examples with real scenarios.
- You don't need all 20. You need one. The one that made you think "I literally did that yesterday and hated every minute of it."
Your head of operations spent Tuesday morning copying revenue numbers from Stripe into a Google Sheet, switching to HubSpot to check which deals moved stages, then opening Meta Ads to see if the weekend campaigns overspent. By lunch, she had a spreadsheet with 47 cells filled in and a Slack DM from the CEO: "Why don't these numbers match what finance sent yesterday?"
She's not bad at her job. She's doing five jobs at once, and three of them are copying data between tabs.
Most "business process automation examples" articles list categories like "automate your CRM" or "automate your invoices" and leave you to figure out how. This one is different. Every example below shows the exact message you type into Slack, the tools involved, and what comes back.
All 20 work with Viktor, an AI coworker that lives in Slack, connects to 3,000+ integrations, and takes real action across your tools.
Pick your department. Find the process that eats your time. Copy the prompt.
Sales: stop researching what your tools already know
Sales reps spend roughly a third of their working hours on non-selling activities. Data entry, prospect research, CRM hygiene, chasing context that already lives somewhere in your stack. These four business process automation examples give that time back.
1. Research a prospect before cold outreach
You found a company that looks like a fit, but you know nothing about them beyond a landing page.
@Viktor I'm about to reach out to Northvane Systems. Pull their company profile from Apollo -- headcount, funding round, tech stack, and recent news. Check their LinkedIn company page for any posts in the last 30 days. Summarize in a brief I can scan in 2 minutes.
Tools: Apollo, LinkedIn, web search Output: A one-page brief showing 84 employees, Series B ($12M raised in 2024), tech stack includes Salesforce and AWS, and their VP of Engineering just posted about scaling infrastructure challenges. You walk into the outreach with context instead of a cold template.
2. Measure pipeline velocity by rep
The weekly pipeline meeting starts with 15 minutes of everyone pulling up their own deals. Nobody knows the average time a deal spends in each stage, and nobody wants to calculate it manually.
@Viktor Pull all active deals from HubSpot. Calculate average days in each stage (Discovery, Proposal, Negotiation, Closed Won) for Q1 2026. Break it down by deal owner. Flag any rep whose average stage time is 2x the team median. Format as a table.
Tools: HubSpot Output: A table showing each rep's pipeline velocity. One rep's deals sit in Proposal for an average of 22 days while the team median is 9. That's a coaching conversation, not a mystery that surfaces after the quarter closes.
3. Enrich and import a batch of leads
Marketing just handed over a CSV of 85 webinar attendees. Before routing them to reps, someone needs company size, job title, and industry for each contact. Manually, that's half a day of tab-switching.
@Viktor Here's a CSV of webinar attendees (attached). For each contact, use Apollo to find their company size, industry, job title, and LinkedIn URL. Score them: A if company has 50+ employees and contact is director-level or above, B if either condition is met, C for everyone else. Create the scored contacts in HubSpot with the tag "Webinar-March-2026."
Tools: Apollo, HubSpot, CSV processing Output: 85 leads enriched, scored, and sitting in HubSpot ready for rep assignment. The A-tier leads (12 contacts) get routed to senior reps. The rest go into a nurture sequence. What used to take a sales ops person half a day finishes while you make coffee.
4. Draft follow-ups for deals going cold
Five deals in your pipeline haven't seen a reply in over 10 days. You know you should follow up, but writing five personalized emails from scratch keeps getting pushed to "later today."
@Viktor From HubSpot, find all my open deals where the contact hasn't replied to an email in 10+ days. For each one, draft a short follow-up referencing their last conversation and the specific feature or concern they mentioned. Keep each under 100 words. Show me the drafts before sending.
Tools: HubSpot, Gmail (draft review) Output: Five email drafts, each referencing real CRM conversation history. One mentions the API integration the prospect asked about. Another brings up the Q2 budget timeline they shared. You tweak a line in one, approve the rest, and they go out. Nothing sends without your explicit approval.
Marketing: pull the data without opening six dashboards
Marketing teams drown in platform-specific dashboards. Every tool has its own reporting UI, its own date range format, its own CSV export. These four examples bring the data to you instead of making you go hunt for it.
5. Check if your ad budget is pacing correctly
It's mid-month and you have no idea whether your Meta Ads and LinkedIn Ads spend is on track to hit your budget or blow right past it.
@Viktor Pull current month-to-date spend from Meta Ads and LinkedIn Ads. Compare against our monthly budget: $15K for Meta, $8K for LinkedIn. At the current daily run rate, will we finish on target, underspend, or overshoot? Flag any campaign spending more than 120% of its daily average.
Tools: Meta Ads, LinkedIn Ads Output: "Meta Ads: $9,230 spent through March 19 (61% of budget). On pace to finish at $14,550, slightly under. LinkedIn Ads: $6,100 spent (76% of budget). On pace to overshoot by $800. Campaign 'SaaS Decision Makers' is running at 145% of its daily target." You adjust one daily cap. Done before your coffee cools.
6. Scan competitor mentions across the web
Someone on your team mentioned a competitor raised another round. You want to know what the market is saying but don't have time to scroll X, Reddit, and tech blogs for an hour.
@Viktor Search the web and X/Twitter for any mentions of "Acme Software" from the last 7 days. Include news articles, X posts with 50+ likes, and product review threads. Summarize the top 10 mentions sorted by reach. Post the summary in #competitive-intel.
Tools: Web search, X/Twitter Output: A summary posted to your Slack channel with 3 news articles about their fundraise, 4 X posts from customers, two praising their new feature and two complaining about pricing changes, 2 Reddit comparison threads, and a G2 review. You know exactly what the market is saying without opening a single tab.
7. Pull social media engagement numbers
Your founder posts on LinkedIn three times a week and wants to know what's working. Your marketing coordinator spends every Monday morning screenshotting analytics from two different platforms.
@Viktor Pull our LinkedIn company page analytics for the last 7 days: impressions, engagement rate, and top 3 posts by clicks. Also pull X/Twitter analytics for the same period: impressions, profile visits, and top 3 posts by engagement. Compare both platforms week-over-week. Deliver as a summary table.
Tools: LinkedIn, X/Twitter Output: A side-by-side table: LinkedIn impressions up 18% (top post was the product demo video), X engagement flat (top performer was the automation thread). Your founder sees what resonated and doubles down. The Monday morning screenshot ritual disappears.
8. Find which content actually drives signups
You publish blog posts, send email campaigns, and post on social. But you have no idea which specific pieces led to trial signups last month.
@Viktor Pull last month's blog traffic from PostHog: pageviews, unique visitors, and signup conversion rate per post. Cross-reference with Customer.io to see which email campaigns drove the most blog visits. Rank everything by signups attributed, not just raw traffic. Format as a table.
Tools: PostHog, Customer.io Output: A ranked table revealing that your "How to Automate Invoice Processing" post drove 34 signups at a 3.2% conversion rate despite being 6th in raw pageviews. The post with the most traffic? It converted at 0.4%. You now know where to focus your distribution effort, not just your content calendar.
Operations: stop being the human glue between your tools
Operations leaders spend their days bridging systems that don't talk to each other. Data lives in Stripe, tasks live in Linear, customer info lives in HubSpot, and someone has to manually shuttle context between them. These four business process automation examples replace the copy-paste.
9. Reconcile vendor payments against your tracker
Finance asked which vendor invoices are still unpaid. You have a Google Sheet tracking purchase orders and Stripe handles the payments, but matching them means 30 minutes of cross-referencing two screens.
@Viktor Compare the vendor invoices in our "Q1 Vendor Payments" Google Sheet against Stripe payment records. For any invoice marked "Pending" in the Sheet that has a matching Stripe payment, update the status to "Paid" and add the payment date. Flag any invoice past its due date with no matching payment found.
Tools: Google Sheets, Stripe Output: Three invoices updated to "Paid" with dates filled in. Two flagged as overdue with no payment on record. You forward the overdue list to accounts payable. One message instead of a 30-minute spreadsheet audit.
10. Compare inventory counts across two systems
Your Google Sheet says 340 units of your top product. Shopify says 312. Somebody sold 28 units that never got logged, or the Sheet is wrong, or both.
@Viktor Pull current inventory levels from our Shopify store for all active products. Compare against the "Current Stock" column in our "Inventory Tracker" Google Sheet. Flag any product where the counts differ by more than 5 units. Show the Shopify count, Sheet count, and the gap.
Tools: Shopify, Google Sheets Output: Seven products flagged. The biggest gap: your "Pro Starter Kit" shows 340 in the Sheet but 312 in Shopify. Three products have higher Sheet counts (likely unlogged sales), two have higher Shopify counts (likely unlogged returns). You fix the discrepancies before they become a fulfillment problem.
11. Set up a new customer's onboarding in one message
A new customer just signed up on Stripe. Now someone needs to create onboarding tasks, assign team members, and draft a welcome email. Usually this means three tools and 20 minutes of copy-paste.
@Viktor New customer: Rayburn Analytics, Growth plan, $450/mo (just paid on Stripe). Create an onboarding project in Linear with these tasks -- (1) Send welcome email, assigned to Sarah, due today (2) Schedule kickoff call, assigned to Mike, due in 2 days (3) Configure their integrations, assigned to James, due in 5 days (4) 30-day check-in, assigned to Sarah, due in 30 days. Draft the welcome email referencing their Growth plan and linking to our setup docs. Show me everything before creating it.
Tools: Stripe, Linear, Gmail Output: A Linear project with four tasks assigned and dated, plus a welcome email draft that mentions the Growth plan by name and includes the right onboarding links. Review it, approve, and the customer gets a professional onboarding experience. No one toggled between three tabs to set it up.
12. Catch support tickets about to breach SLA
Your team promises a 4-hour response time for paying customers. But nobody monitors the queue in real time, and SLA breaches surface after they've already happened.
@Viktor Check all open tickets in Pylon. Flag any ticket from a paying customer where no first response has been sent and the ticket is older than 3 hours. Show the ticket subject, customer name, plan tier, and time elapsed. Post the list in #support-escalation.
Tools: Pylon, Slack Output: Two tickets flagged: one at 3h 22m (Enterprise customer asking about SSO setup) and one at 3h 48m (Growth customer reporting a sync error). The #support-escalation channel gets the alert. Your team responds before the 4-hour mark. No more after-the-fact "we missed the SLA" postmortems.
Finance: let the numbers check themselves
Finance teams handle the most tedious variety of manual work: comparing numbers across systems to confirm they match. A digit off here, a missing row there, and reconciliation turns into a two-hour detective story. These business process automation examples do the matching for you.
13. Check Stripe revenue against your accounting spreadsheet
End of month. Finance needs to verify that Stripe revenue matches the books. Someone pulls up both screens and starts comparing line by line.
@Viktor Pull all successful Stripe charges for March 2026. Compare the total against the "Revenue" column in our "March Financials" Google Sheet. Flag any Stripe charge over $500 that doesn't have a matching row in the Sheet. Also flag any Sheet row with no corresponding Stripe charge.
Tools: Stripe, Google Sheets Output: Total Stripe revenue: $187,420. Sheet total: $186,870. Difference: $550. Two Stripe charges found with no Sheet match: a $320 mid-month upgrade and a $230 annual renewal on March 29. One Sheet row with no Stripe match ($180, likely a manual entry error). Finance fixes three rows instead of auditing hundreds.
14. Categorize a month of credit card expenses
The company credit card statement has 73 transactions. Someone needs to tag each one before the monthly close. The spreadsheet has been sitting in your inbox for three days.
@Viktor Here's our March credit card statement (attached CSV). Categorize each transaction into: Software, Travel, Marketing, Office Supplies, Meals, or Other. For any charge over $1,000, add a note explaining the likely purpose based on the vendor name. Flag anything unusual: duplicate charges, round-number amounts over $500, or vendors we haven't paid before. Output as a categorized CSV.
Tools: CSV processing, Google Sheets Output: All 73 transactions categorized. Software: 31 ($12,400). Marketing: 8 ($7,200). Two duplicate $49.99 charges to the same SaaS vendor flagged. A $2,500 charge to "Horizon Media" gets a note: "Likely ad placement or media buy -- verify with marketing team." Ninety minutes of bookkeeping compressed to one message and a quick review.
15. Match purchase orders to vendor invoices
You have 40 purchase orders in one spreadsheet and 38 invoices that arrived via email. Matching them means an hour of toggling between Gmail and Sheets.
@Viktor Pull all emails labeled "Vendor Invoices" in Gmail from March 2026. Extract the invoice number, vendor name, amount, and date from each. Match them against our "March POs" Google Sheet by vendor name and amount (allow 2% tolerance for rounding). List any PO with no matching invoice and any invoice with no matching PO.
Tools: Gmail, Google Sheets Output: 36 of 40 POs matched. Two POs have no invoice yet (follow up with those vendors). Two invoices arrived with no matching PO: one is $200 higher than expected (price increase?) and one is from a vendor not in the PO tracker. You know exactly where to look instead of comparing 80 line items by hand.
16. Calculate burn rate and runway for the board
The board wants an updated runway number. Getting there means pulling three months of revenue, matching it against expenses, and doing the math manually.
@Viktor Pull total revenue from Stripe for January, February, and March 2026. Pull total operating expenses from our "2026 Expenses" Google Sheet for the same months. Calculate monthly net burn (expenses minus revenue) for each month, average it, and divide our current cash balance ($840K from the Sheet) by the average to get runway in months. Show the month-by-month breakdown and the final number.
Tools: Stripe, Google Sheets Output: January net burn: $32K. February: $28K. March: $35K. Three-month average: $31,700/mo. At $840K cash, that's 26.5 months of runway. Revenue grew 12% quarter-over-quarter while expenses grew 8%. Your CFO gets a clean, verifiable summary instead of a number someone estimated from memory.
HR: automate the paperwork, keep the people work
HR exists to take care of people, but the job spends a disproportionate amount of time on logistics. Tracking who's out, generating documents, researching candidates, and calculating capacity. These four examples handle the administrative load so HR can focus on the humans.
17. Get a PTO snapshot for the week ahead
It's Monday. You need to know who's out this week and next so you can staff a critical project. Checking Google Calendar for 15 team members one by one takes 10 minutes of clicking and counting.
@Viktor Check Google Calendar for everyone on the "Product Team" calendar group. Who has PTO or Out of Office events this week (March 23-27) and next week (March 30 - April 3)? List each person and the dates they're out. Flag any day where more than 40% of the team is absent. Post in #team-scheduling.
Tools: Google Calendar, Slack Output: Posted to #team-scheduling: "This week: Anna (Wed-Fri), James (Thu). Next week: Anna (Mon), Mike (Mon-Wed), Sarah (Fri). Warning: Next Monday has 3 of 7 team members out (43%). Consider rescheduling sprint planning." You staffed the project in 30 seconds.
18. Brief yourself on a candidate before an interview
You have an interview in an hour with someone you haven't researched beyond skimming their resume at breakfast.
@Viktor I'm interviewing Jordan Rivera for our Senior Engineer role in 1 hour. Pull their LinkedIn profile and GitHub activity for the last 6 months. Check Apollo for their full work history and company details. Summarize in a brief: experience highlights, notable projects, and 3 suggested interview questions based on their background.
Tools: Apollo, LinkedIn, GitHub Output: Jordan has 7 years of experience, currently at a Series C fintech. Their GitHub shows 340 contributions in the past 6 months, mostly to an open-source Kubernetes tooling project. They published a blog post about migrating from monolith to microservices. Suggested questions target architecture decisions, data consistency strategies, and lessons learned. You walk into the interview informed, not improvising.
19. Generate a new hire document package
A new employee starts Monday. You need an offer letter, an equipment request, and a first-week schedule. Creating these from templates means an hour of copy-paste-customize across three different documents.
@Viktor New hire starting Monday: Priya Sharma, Product Designer, $95K salary, reports to Lisa Chen, start date March 30. Generate: (1) Offer letter PDF with these details and our standard terms (2) Equipment request listing MacBook Pro 16", external monitor, and Figma license (3) First-week schedule with onboarding sessions Day 1, team introductions Day 2, and first project briefing Day 3. Show me drafts before finalizing.
Tools: PDF generation, Google Sheets (equipment tracking) Output: Three documents ready: a formatted offer letter PDF, a pre-filled equipment request, and a Day 1-3 schedule. You adjust the Day 3 briefing time from 10 AM to 2 PM, approve, and the entire package is ready to send. An hour of template wrangling turned into one message and a quick review.
20. See who has bandwidth and who's overloaded
A new project needs an owner, but you don't know who has capacity. Checking everyone's task count means opening Linear and clicking through profiles one at a time.
@Viktor Pull all open and in-progress tasks from Linear for the Product team. Group by assignee. For each person, show total open tasks, tasks due this week, and any overdue items. Cross-reference with Google Calendar to flag anyone with more than 6 hours of meetings today. Rank the team from most available to most loaded.
Tools: Linear, Google Calendar Output: "Most available: James (4 open tasks, 0 overdue, 2h meetings today). Most loaded: Sarah (11 open tasks, 3 overdue, 7h meetings today)." The new project goes to James. The conversation about Sarah's workload happens now, not after she burns out.
All 20 business process automation examples compared
| # | Process | Manual time | With Viktor | Tools |
|---|---|---|---|---|
| 1 | Cold prospect research | 25-40 min | ~90 sec | Apollo, LinkedIn, web |
| 2 | Pipeline velocity by rep | 30-45 min | ~60 sec | HubSpot |
| 3 | Batch lead enrichment (85 leads) | 3-4 hours | ~3 min | Apollo, HubSpot |
| 4 | Follow-up emails for cold deals | 45-60 min | ~2 min | HubSpot, Gmail |
| 5 | Ad budget pacing check | 20-30 min | ~60 sec | Meta Ads, LinkedIn Ads |
| 6 | Competitor mention scan | 45-60 min | ~2 min | Web, X/Twitter |
| 7 | Social media analytics pull | 20-30 min | ~90 sec | LinkedIn, X/Twitter |
| 8 | Content attribution analysis | 60-90 min | ~2 min | PostHog, Customer.io |
| 9 | Vendor payment reconciliation | 30-45 min | ~90 sec | Stripe, Google Sheets |
| 10 | Inventory count comparison | 30-45 min | ~2 min | Shopify, Google Sheets |
| 11 | Customer onboarding setup | 20-30 min | ~90 sec | Stripe, Linear, Gmail |
| 12 | SLA breach monitoring | Ongoing | ~30 sec | Pylon, Slack |
| 13 | Revenue reconciliation | 1-2 hours | ~2 min | Stripe, Google Sheets |
| 14 | Expense categorization (73 items) | 60-90 min | ~2 min | CSV, Google Sheets |
| 15 | PO-to-invoice matching | 45-60 min | ~2 min | Gmail, Google Sheets |
| 16 | Burn rate and runway | 30-45 min | ~60 sec | Stripe, Google Sheets |
| 17 | PTO snapshot | 10-15 min | ~30 sec | Google Calendar, Slack |
| 18 | Candidate research | 20-30 min | ~90 sec | Apollo, LinkedIn, GitHub |
| 19 | New hire document package | 45-60 min | ~3 min | PDF generation, Sheets |
| 20 | Team capacity report | 20-30 min | ~60 sec | Linear, Google Calendar |
If your team does even half of these weekly, that's 10-15 hours of manual work replaced by Slack messages and a few minutes of reviewing outputs.
Where to start with business process automation
Pick one. The example above that made you think "I did that yesterday."
Copy the prompt. Swap in your real tool names, team names, and thresholds. Send it.
If the output saves you time, try a second one the next day. If it keeps working, set it up as a recurring cron so it runs without you ever typing the message again.
The teams that get the most out of business process automation don't automate 20 things on day one. They automate one thing. They verify it works. And they let the pattern repeat naturally once they see how much time comes back.
Viktor is an AI coworker that works this way by design. You describe the task in Slack, it connects to your tools via OAuth, and it delivers the result for your review. No workflow builder, no drag-and-drop canvas, no 15-step Zap. One message, real output.
Frequently Asked Questions
What is business process automation? Business process automation means using software to handle repeatable tasks that otherwise require manual effort. Data entry, report generation, cross-system reconciliation, document creation. The modern approach connects to your existing tools via APIs and runs multi-step workflows from a single trigger, like a Slack message to an AI coworker.
What are the best business process automation examples for small teams? For teams of 10-50 people, start with processes that eat time without requiring judgment. Lead enrichment from a CSV, expense categorization, vendor payment reconciliation, and customer onboarding checklists are all high-volume copy-paste tasks that automation handles well. Weekly reporting is another strong starting point if your team pulls from multiple platforms.
Do I need technical skills to set up these automations? No. You describe the task in plain English in Slack. Viktor connects to your tools through one-click OAuth and handles the data pulling, matching, and formatting. If you can explain the task to a colleague in a message, you can automate it. Every output gets reviewed before any action executes.
How is this different from Zapier or Make? Zapier and Make use a trigger-action model: "When X happens in Tool A, do Y in Tool B." Each step is preconfigured. Viktor is an AI coworker that handles multi-step, multi-tool workflows described in natural language. Instead of building a 15-step automation flow, you type one message that says "pull from these four tools, compare the data, and format the result." The AI determines the steps. You review the output.
Can Viktor handle workflows that involve more than two tools? Yes. Viktor connects to 3,000+ integrations and can read from and write to multiple tools in a single workflow. The investor update example pulls from Stripe, HubSpot, Google Ads, Meta Ads, and PostHog in one message. There's no cap on how many tools a single prompt can touch.
Is it safe to give an AI access to tools like Stripe or HubSpot? Viktor connects via standard OAuth, the same authorization flow you use for any SaaS integration. Your passwords and API keys are never exposed to the AI. Every action that writes or modifies data goes through review-first by default: Viktor shows you exactly what it plans to do, and nothing executes until you approve. You decide which workflows earn enough trust to run without review.
Viktor is an AI coworker that lives in Slack, connects to 3,000+ integrations, and does real work across every department. Add Viktor to your workspace -- free to start →