Why Automations Matter
Your Value Framework provides standardized use cases that work across many deals. But the most effective business cases speak directly to each buyer’s unique situation. Without Automations:- Generic use case names like “Reduce Manual Data Entry”
- Standard descriptions that don’t reference buyer-specific context
- Time spent manually rewriting content for each deal
- Context-aware names like “Eliminate Manual Reporting for Finance Team”
- Descriptions that reference your buyer’s specific challenges
- Tailored content in seconds, not hours
Automations analyze your deal context—discovery notes, call transcripts, CRM data—to generate suggestions that sound like you wrote them specifically for this buyer.
Accessing Automations
Automations live in the Copilot panel, your AI assistant within every business case.Open the Copilot panel
Look for the Copilot icon on the right side of your business case. Click it to open the Copilot panel.
Navigate to Automations
In the Copilot panel, select “Automations” from the menu. You’ll see available automation options.
Customize Use Cases
The Customize Use Cases automation rewrites your use case names and descriptions to match your specific buyer’s context.How It Works
When you run this automation:- AI analyzes your deal context – Discovery notes, call transcripts, stakeholder information, industry, and company details
- Generates tailored suggestions – AI rewrites each use case name and description to resonate with this specific buyer
- You review and accept – Navigate through suggestions, accepting the ones that improve your business case
- Changes apply instantly – Accepted suggestions update your business case immediately
Running the Automation
Open Automations in Copilot
In your business case, open the Copilot panel and navigate to “Automations”.
Click 'Customize Use Cases'
Select the “Customize Use Cases” card. AI begins analyzing your deal context and generating suggestions.
Wait for suggestions to generate
AI generates customized names and descriptions for each use case in your business case. This typically takes 10-30 seconds depending on the number of use cases.You’ll see a spinner while suggestions are being generated, and a counter showing how many suggestions are ready.
Reviewing Suggestions
Once suggestions are generated, you’ll see:- Suggestion counter – Number of pending name and description suggestions
- Navigation arrows – Move between use cases to review each suggestion
- Accept All button – Apply all suggestions at once
- Cancel option – Discard all suggestions and return to the automations menu
Navigating Through Suggestions
Use the arrow buttons to move between use cases. As you navigate:- The business case automatically scrolls to highlight the current use case
- You can see the original name/description alongside the AI suggestion
- The interface shows which use case you’re reviewing and how many remain
Accepting Suggestions
You have two ways to accept suggestions: Accept All – Click “Accept All” to apply every suggestion at once. This is fast and works well when AI suggestions are consistently good. Accept Individually – Navigate to each use case and accept or reject suggestions one by one. Each accepted suggestion updates the business case immediately.Accepting a suggestion permanently replaces the original text. If you want to keep the original, reject the suggestion and move to the next one.
Canceling the Automation
If you decide not to use any suggestions:- Click “Cancel Automation” at the top of the panel
- All pending suggestions are discarded
- Your business case remains unchanged
- You return to the main Automations menu
Understanding the Suggestions
What Makes a Good SuggestionAI-generated suggestions improve your business case when they:
- Reference specific buyer context – “Reduce time spent on quarterly compliance reports” instead of “Reduce manual reporting time”
- Match buyer language – Use terms your buyer used in discovery calls
- Align with stakeholder priorities – Emphasize aspects that matter to the buying team
- Stay accurate – Maintain the underlying value calculation while improving clarity
Not every suggestion will be perfect. Review carefully for:
- Accuracy – Does the suggestion correctly describe what this use case calculates?
- Relevance – Does it align with what you learned in discovery?
- Tone – Does it match how your buyer talks about their challenges?
- Specificity – Is it appropriately specific without overpromising?
Examples of Customization
Original Use Case Name:“Improve Sales Team Efficiency” AI-Customized Name (for a healthcare deal):
“Reduce Time Spent on Patient Data Entry for Clinical Staff”
Original Description:
“Our solution automates repetitive tasks, allowing your team to focus on high-value activities.” AI-Customized Description:
“By automating patient data entry across your 15 clinics, your clinical staff can redirect 8 hours per week toward direct patient care, improving both efficiency and patient satisfaction.”
Notice how the customized version references specific buyer details (15 clinics, clinical staff, patient care) that make the value story more concrete and compelling.
Best Practices
Add deal context before running automations
Add deal context before running automations
The automation uses your discovery notes, call transcripts, and deal details to generate suggestions. The more context you provide, the better your suggestions will be.
Review suggestions carefully
Review suggestions carefully
AI suggestions are good starting points, but you know your buyer best. Don’t blindly accept everything—verify that suggestions align with your understanding of the deal.
Run automations after discovery, not before
Run automations after discovery, not before
Wait until you have substantive deal context from discovery calls. Running automations without context produces generic suggestions that won’t improve your business case.
Use 'Accept All' when appropriate
Use 'Accept All' when appropriate
If you’re seeing consistently good suggestions, use “Accept All” to save time. But spot-check a few first to build confidence in the quality.
Re-run automations as context evolves
Re-run automations as context evolves
If you learn new information about your buyer’s priorities or challenges, run the automation again. Fresh context produces fresh suggestions.
Combine automation with manual editing
Combine automation with manual editing
Automations handle the heavy lifting, but you can still manually refine use case content afterward. Use both for the best results.
Suggest Input Values
Input Scout uses AI-powered research to automatically find publicly available data for your use case inputs. Instead of manually researching metrics like company revenue, employee counts, or industry salary benchmarks, let AI search the internet and populate your business case.Input Scout only works with metrics that are publicly available online—company financials, headcount data, salary benchmarks, and profitability margins.
How It Works
- Inputs are automatically categorized – When you save a calculation in the Value Framework, AI analyzes each input to determine if it represents publicly researchable data
- Input Scout runs automatically – When use cases are added to a business case, Input Scout searches for values for eligible inputs
- Results are scored by confidence – Each result receives a confidence score (1-3) based on source reliability
- High-confidence values auto-apply – Results with confidence ≥2 are automatically recorded in your business case, with a note added to the input explaining where the data came from
What Inputs Can Be Researched?
Input Scout classifies inputs based on whether the data is publicly available online. The following categories are eligible:| Category | What It Includes | Examples |
|---|---|---|
| Headcount | Employee counts, team sizes, workforce data | ”# of employees”, “Sales team size”, “Engineering headcount” |
| Revenue | Annual/quarterly revenue, total sales, revenue by segment | ”Annual revenue”, “Q4 revenue”, “Revenue by region” |
| Salary & Compensation | Wages, FTE costs, fully-loaded costs, labor costs | ”Hourly wage”, “Cost per FTE”, “Software engineer salary” |
| Margins | Profitability metrics like gross, operating, or net margin | ”Gross margin”, “Operating margin”, “EBITDA margin” |
Automatic Input Classification
Inputs are automatically classified when you save a calculation in the Value Framework. AI analyzes each input’s name, description, and unit to determine if it falls into a researchable category. ✅ Enabled (can be researched):- Factual company metrics disclosed in SEC filings, press releases, or LinkedIn
- Industry salary benchmarks available on Glassdoor, Levels.fyi, or Bureau of Labor Statistics
- Standard financial ratios reported in annual reports
- Estimates specific to the buyer’s situation (“potential cost savings”)
- Behavioral or adoption metrics (”% of employees using X tool”)
- Future projections or hypothetical scenarios
Running Manually
While Input Scout runs automatically when use cases are added, you can also trigger it manually:Open Automations in Copilot
In your business case, open the Copilot panel and navigate to “Automations”.
Click 'Suggest Input Values'
Select the “Suggest Input Values” card. AI begins researching your eligible inputs.
Wait for research to complete
Input Scout searches across multiple public sources. This typically takes 10-30 seconds.
Understanding Results
Inputs Added (High Confidence) Values with confidence ≥2 are automatically recorded, and a note is added to the input explaining the source. Sources include:- SEC filings and annual reports
- LinkedIn company profiles
- Levels.fyi, Glassdoor, LinkedIn Salaries
- Company press releases and investor presentations
Resetting Values
Click “Reset” on any high-confidence result to restore the previous value. Low-confidence results were not applied, so there’s nothing to reset.Coming Soon: Additional Automations
We’re continuing to expand automations. Here’s what’s coming:AI CFO Review
Get AI-powered feedback on your business case from a finance perspective. This automation will identify potential weak spots, suggest areas for stronger justification, and help you prepare for CFO-level scrutiny.Discovery Call Analysis
Automatically extract key insights from call transcripts and discovery notes to populate your business case context. This automation will identify pain points, stakeholder priorities, and value drivers mentioned in conversations.Troubleshooting
Customize Use Cases
Suggestions aren't relevant to my deal
Suggestions aren't relevant to my deal
This usually means AI doesn’t have enough deal context. Add more discovery notes, stakeholder information, or call transcript summaries to your business case, then run the automation again.
No suggestions were generated
No suggestions were generated
Check that you have visible use cases in your business case. If all use cases are hidden, the automation has nothing to customize. Unhide use cases and try again.
Automation is taking a long time
Automation is taking a long time
Generation time depends on the number of use cases and the complexity of your deal context. Most complete in 10-30 seconds. If it exceeds a minute, refresh your browser and try again.
I accepted a suggestion I didn't mean to
I accepted a suggestion I didn't mean to
You can manually edit the use case name or description to revert it or make adjustments. Click into the use case and update the text as needed.
Suggest Input Values
No inputs are found for suggestions
No inputs are found for suggestions
Input Scout only supports publicly researchable metrics (headcount, revenue, salary, margins). Check that your inputs fall into these categories. Internal estimates like “potential revenue uplift” cannot be researched.
Results show industry averages instead of company data
Results show industry averages instead of company data
The company might be private or have limited public disclosure. The explanation will note when company-specific data wasn’t available. Consider this a starting point for your own research.
Values seem incorrect
Values seem incorrect
Check the source in the explanation. If the data is outdated or from an unreliable source, click Reset to restore the previous value and enter it manually.
Automation is taking a long time
Automation is taking a long time
Research time depends on the number of eligible inputs. Most complete in 10-30 seconds. If it exceeds a minute, refresh your browser and try again.
With automations, you can deliver buyer-specific business cases without spending hours customizing content manually. Let AI handle the tailoring so you can focus on conversations that matter.