sales-skills/sales-aviso

Aviso AI Platform Help

Step 1 — Gather context

If references/learnings.md exists, read it first for accumulated platform knowledge.

1. What do you need help with?

   • A) Setting up Aviso or connecting CRM (Salesforce, HubSpot, Dynamics 365)
   • B) Revenue forecasting (models, accuracy, AI vs adjusted vs sales forecast)
   • C) Conversation intelligence (transcription, sentiment, emotion analysis, coaching)
   • D) MIKI AI agent or GTM Agent Studio workflows
   • E) Pipeline inspection, deal acceleration, or deal health scoring
   • F) Relationship intelligence (Aviso Graph, org charts, engagement tracking)
   • G) Integrations (CRM writeback, data warehouse, conferencing, engagement tools)
   • H) Pricing or plan evaluation
   • I) Troubleshooting (dashboards, sync, scoring, forecast confusion)

2. Which CRM are you connecting?

   • A) Salesforce
   • B) HubSpot
   • C) Microsoft Dynamics 365
   • D) Other (Freshworks, Oracle, SAP, Zoho, Pipedrive)
   • E) Not sure / evaluating

Skip-ahead rule: if the user's prompt already contains enough context, skip to Step 2.

Step 2 — Route or answer directly

| Problem domain | Route to | |---|---| | Comparing Aviso to other note-takers or CI tools | /sales-note-taker {user's question} | | Comparing Aviso to other revenue forecasting tools | /sales-forecast {user's question} | | Reviewing a specific call for coaching feedback | /sales-call-review {user's question} | | Building a coaching program using Aviso data | /sales-coaching {user's question} | | General CRM-to-tool integration patterns | /sales-integration {user's question} | | HubSpot-specific configuration | /sales-hubspot {user's question} | | Salesforce-specific configuration | /sales-salesforce {user's question} |

When routing, provide the exact command.

Step 3 — Aviso platform reference

Read references/platform-guide.md for the full platform reference — modules, pricing, integrations, data architecture, known issues.

Answer the user's question using only the relevant section. Don't dump the full reference.

Step 4 — Actionable guidance

You no longer need the platform guide — focus on the user's specific situation.

Setup priority: Connect primary CRM first (Salesforce or Dynamics 365 is best-supported), then configure forecasting hierarchies, then enable conversation intelligence on conferencing tools (Zoom/Teams), then set up MIKI workflows.

Forecast selection: Use "AI Forecast" as the primary prediction (100+ variable model). "Sales Forecast" reflects manager judgment. "Adjusted Forecast" is the manual override. When they disagree, investigate the gap — AI may see signals managers don't, or managers may have context AI lacks.

Evaluation tip: Aviso is enterprise-only with custom pricing (~$1,000/user/yr). Request a pilot with historical data to validate the 98% accuracy claim against your actual pipeline. Insist on seeing accuracy metrics on YOUR data, not benchmarks.

If you discover a gotcha, workaround, or tip not covered in references/learnings.md, append it there.

Gotchas

Best-effort from research — review these, especially items about plan-gated features and integration gotchas that may be outdated.

• No public API documentation. Aviso Connect exists as an integration layer but has no public developer docs, endpoints, or auth specs. You cannot build custom integrations without engaging Aviso's team.
• Three forecast types cause confusion. AI Forecast, Sales Forecast, and Adjusted Forecast serve different purposes — users frequently report not understanding which to trust. AI Forecast is the model's prediction; Sales Forecast is the manager's call; Adjusted Forecast is the manual override.
• Dashboard customizations may revert. Multiple G2 reviewers report losing custom dashboard configurations after updates or reloads. Save/export configurations if possible.
• Deal scoring lacks transparency. The AI model considers 100+ variables but doesn't fully explain why a deal is scored high or low. This frustrates reps who disagree with the score.
• Integration requires dev work. Setting up CRM sync and data pipelines is not a self-service drag-and-drop — expect to involve your technical team or Aviso's implementation support.
• Enterprise pricing only (~$1,000/user/yr). No free tier, no self-serve. SMB teams will be priced out. Request multi-year discount and pilot period.

Related skills

• /sales-note-taker — Comparing Aviso's conversation intelligence to dedicated note-takers (Fathom, Gong, Fireflies, etc.)
• /sales-forecast — Revenue forecasting strategy across platforms (Clari, Gong Forecast, Salesforce, Aviso)
• /sales-call-review — Review a specific call for coaching feedback and scoring
• /sales-coaching — Build coaching programs that consume call data
• /sales-gong — Gong platform help (primary competitor for CI + deal intelligence)
• /sales-clari-copilot — Clari Copilot platform help (primary competitor for forecasting)
• /sales-integration — General CRM/tool integration patterns (Zapier, webhooks, iPaaS)
• /sales-do — Not sure which skill to use? The router matches any sales objective to the right skill. Install: npx skills add sales-skills/sales --skill sales-do

Examples

Example 1: Choosing between Aviso and Clari for forecasting

User says: "Should I pick Aviso or Clari for revenue forecasting? I'm on Salesforce with a 50-person sales team." Skill does:

1. Frames the key difference: Aviso is AI-native forecasting analyzing 100+ variables with claimed 98% accuracy; Clari focuses on structured forecast rollups, commit management, and executive visibility
2. Notes both are enterprise-priced (~$1,000/user/yr), so cost isn't the tiebreaker
3. Recommends Aviso if: complex revenue models (consumption-based, splits/overlays, multi-product), willingness to trust AI predictions, need for multi-CRM consolidation
4. Recommends Clari if: structured forecast governance, strong exec reporting, simpler pipeline models, larger existing Clari ecosystem Result: Clear decision framework based on forecasting complexity and governance needs.

Example 2: CRM writeback not updating Salesforce fields

User says: "Aviso isn't writing deal updates back to Salesforce after meetings. What's wrong?" Skill does:

1. Checks that CRM Writeback is enabled in Aviso settings and Salesforce integration is connected
2. Verifies field mapping — Aviso needs to know which Salesforce fields to update
3. Checks Salesforce permissions — the connected user needs write access to opportunity fields
4. Notes that writeback may have a delay (Aviso processes data before writing)
5. Suggests checking Aviso's sync logs for error messages Result: Specific CRM writeback troubleshooting steps.

Example 3: Piping Aviso data into a data warehouse

User says: "Can I get Aviso forecasting data into Snowflake for my BI team?" Skill does:

1. Notes that Aviso has no public API — direct programmatic access isn't available
2. Checks if Aviso supports native warehouse connectors (Snowflake, Redshift, BigQuery are listed as integrations)
3. Recommends engaging Aviso's implementation team to set up a data export pipeline
4. Suggests Aviso Connect (their integration layer) as the mechanism, but notes it requires Aviso's team to configure
5. As a fallback, CRM writeback → Salesforce → Snowflake pipeline if direct integration isn't available Result: Practical data pipeline options despite no public API.

Troubleshooting

Forecast types are confusing — which one should I trust?

Symptom: Three different forecast numbers (AI Forecast, Sales Forecast, Adjusted Forecast) and unclear which is the "real" one. Cause: Aviso provides multiple forecast views: AI Forecast is the model's prediction based on 100+ signals, Sales Forecast is the manager's judgment call, and Adjusted Forecast is the manual override. Solution: Use AI Forecast as the baseline prediction. Compare it against Sales Forecast to find disagreements — investigate those deals specifically. Use Adjusted Forecast only for executive-level overrides with documented reasoning. Over time, track which forecast type was most accurate to calibrate trust.

Dashboard customizations resetting after changes

Symptom: Custom dashboard layouts, filters, or views revert to defaults. Cause: Known issue reported by multiple users — dashboard state may not persist reliably across sessions or after platform updates. Solution: Document your dashboard configurations externally (screenshots, config notes). After customizing, verify the changes persist by logging out and back in. Report persistent issues to Aviso support — this is a known pain point they may have fixed in recent releases.

Steep learning curve for new users

Symptom: Team struggles to adopt Aviso despite investment — features feel overwhelming. Cause: Aviso covers 10+ modules (forecasting, CI, relationship intelligence, engagement, CS) and the breadth can paralyze new users. Solution: Phase the rollout: start with forecasting only (the primary differentiator), add conversation intelligence in month 2, then relationship intelligence and MIKI agents in month 3. Assign a power user per team to become the internal champion. Request Aviso's onboarding playbook and insist on live training sessions, not just docs.