7 Key Features to Look for in a Revenue Intelligence Platform

Do you struggle with disconnected data that hurts your pipeline forecast accuracy?

Manual spreadsheets and feelings used to work, but can your team grow with them?

The short answer - definitely not!

Missing revenue targets costs money. That is why a revenue intelligence platform fixes this for modern sales teams.

Understanding Revenue Intelligence

What is Revenue Intelligence?

Revenue Intelligence functions as a move from static data storage to dynamic data interpretation. In this sense, it’s not just a software category. Revenue intelligence platforms use artificial intelligence to capture, synthesize, and study unstructured data like emails, calendar invites, and calls.

Unlike Customer Relationship Management systems, which often act as systems of record relying on manual entry, Revenue Intelligence platforms ingest the logs of digital work to build a factual record independent of human bias.

This allows businesses to change from relying on lagging indicators to managing leading indicators ahead of time.

The Importance of Revenue Intelligence for Businesses

1. Solving the Data Problem: Businesses today possess more data than ever. Yet revenue outlooks remain unclear due to separation and human error.
   
2. Financial Necessity: In an environment of capital scarcity and efficiency checks, precise revenue prediction is now a financial requirement, not a luxury
   
3. Overcoming Human Error: Traditional judgmental analysis forecasting results in less than 20 percent of businesses achieving forecast accuracy above 75 percent.
   
4. Removing Silos: Revenue Intelligence platforms break down data silos by capturing activity data. They apply machine learning to find patterns invisible to the human eye. They often reach forecast accuracy rates higher than 95 percent.

Key Features of a Revenue Intelligence Platform

1. Data Connection Functions

A strong platform acts as a main hub. It connects strategy to execution by linking across the entire tech stack. 

Look for revenue intelligence platforms that link naturally with Outlook and Gmail. They should live exactly where the representatives live to capture data smoothly.

• Zero Touch Philosophy: Select tools that automatically collect contact and activity data to fill the Customer Relationship Management system without representative help. This can lower manual entry by up to 85 percent.
  
• Historical Repair: High-level platforms can fill Customer Relationship Management data from the past. They fix historical gaps from Day 1. This acts as a fix for businesses with poor data hygiene.

2. High-Level Analytics and Reporting

Reliable revenue intelligence platforms use time series data models to snap historical data at regular intervals. This allows leaders to see exactly how deals change over time. For this, functions like Flow Inspection allow leaders to find pipeline leaks. They identify slipped deals with great detail.

• Explainable AI: Seek out White Box analytics. Examples include WinScore technology. This gives specific reasons like Stalled Legal Review to back up prediction scores rather than giving a mystery number.
  
• Conversation Intelligence: Connecting with Conversation Intelligence tools is necessary. This analyzes call recordings for concepts like pricing objections. It captures the true Voice of the Customer beyond simple keywords.

3. Sales Forecasting Tools

Revenue intelligence platforms should use AI to give health scores to opportunities. This flags risky deals despite representative optimism by comparing current signals against past win rates.

For matrixed businesses, the platform must handle complex roll-up forecasts. These function independently of strict Customer Relationship Management hierarchies. They allow for split revenue across territories.

• Consumption Forecasting Software as a Service companies with usage-based pricing models need specific tools for consumption forecasting. 
• This can reach high accuracy in predicting usage metrics and pipeline forecasts.

4. Real-Time Market Insights

The revenue intelligence platform must find valuable signals instantly. Examples include a champion stopping email replies or a competitor mention. These would otherwise remain trapped in separate systems.

• Mobile Access: Executives require the ability to check the numbers from anywhere. Mobile applications are often listed as a key difference for executive use.
  
• Contextual Improvement: Top-tier platforms use massive business-to-business databases to improve conversation data. They identify speakers and roles like Economic Buyers, even if they have not met formally.

5. Easy-to-Use Dashboards

Deal Boards give a visual picture of pipeline health based on verified interactions. This helps managers spot risks without digging through spreadsheets.

• Customizable Views: The ability to change views is important. Executives need macro-level pipeline health. Representatives need actionable views for their specific territories.
  
• Usability Balance: Weigh the trade-off between strength and ease of use. Some platforms are easy to use out of the box. Others offer huge customization but need a specific operations team.

6. Customizable Alerts and Notifications

The revenue intelligence platform should close the loop between intelligence and action. It does this by finding risk signals and immediately starting workflows to fix them. Look for systems that act as automated sales managers. 

They send alerts for specific Revenue Leakage events. An example is a demo that ended without a next step scheduled.

• Real guidance: AI assistants can give in call assistance. They show battle cards or discovery prompts in real time when competitors appear in conversation.
  
• Prioritized Workflows: Engines that ingest signals from across the stack help reps. Examples include buyer intent or contract updates. Prioritizing them into a single To Do list helps solve the problem of switching between screens.

7. Collaboration and Communication Tools

Success Plans or Mutual Action Plans create a shared digital workspace. Buyers and sellers can work together on the closing process here. This increases the chance of a close.

• Coaching Playlists: Coaching Playlists allow managers to keep parts of successful calls. This spreads top performer skills and speeds up new hire training.
• Cross-Functional Visibility: A single source of truth lowers trouble between departments. This makes sure that Sales, Marketing, and Customer Success teams see the same reality of the business relationship.

Checking Revenue Intelligence Software

• Stage 1 - The Builder 0 to 10 Million ARR: Concentrate on basic process definition using spreadsheets and light Customer Relationship Management systems. Enterprise Revenue Intelligence is likely too much at this stage.
  
• Stage 2 - The Scaler 10 to 50 Million ARR: Put data capture first. Use automation tools to fix data leaks before spending on expensive forecasting software.
  
• Stage 3 - The Optimizer 50 Million Plus ARR: Concentrate on predictability and rigor. Start heavy-duty forecasting and coaching platforms to run strict forecasting cadences.
  
• Vendor Questions: Ask if AI trains on your private data or generic models. Ask for White Box reasons for scores. Check if the tool needs manual representative entry.

Benefits of Using Revenue Intelligence Tools

Faster Mean Time to Resolution

• Diagnose Without Guesswork: Revenue Intelligence tools allow teams to check pipeline issues visually and instantly. This removes the guesswork from deal reviews.
• Simplified Communication: Access to a factual record cuts down on the back-and-forth messages needed to understand deal status.

Higher Win Rates and Deal Speed

• Measurable Changes: Companies report win rate upgrades of nearly 30 percent. They also see drops in slipped deals by over 30 percent due to better visibility.
• Compressed Cycles: Sales cycles can drop by 33 percent by finding and copying the winning behaviors of top performers.

Better Forecast Accuracy

• Precision Forecasting: Moving to data-based pipeline forecasting can lift accuracy to 98 percent. This is higher than the industry average.
• Planned Growth: High accuracy allows for better resource distribution. It prevents the financial changes associated with surprise misses.

Higher Productivity and Speed

• Freeing Representatives: Automating data capture can save 90 percent of the time previously spent on manual forecast roll-ups.
• Ending Data Entry: Some businesses have lowered manual data entry by 85 percent. This frees up thousands of hours for selling activities.

Choosing Thunai for Revenue Intelligence

Stop letting separate data drain your sales team's speed. In the age of AI, flying blind makes no sense.

Thunai speeds up revenue predictability by uniting your data and insights. This frees your agents for complex deal closing that lifts revenue. With Thunai revenue intelligence, you get:

• Data-Based Pipeline Forecasts: Move beyond spreadsheets with predictive models. They analyze real-time signals to give you a forecast you can trust.
  
• Automated Data Capture: Stop tedious Customer Relationship Management updates. Automatically ingest emails, calls, and meetings. This keeps your deal health accurate without manual work.
  
• Thunai Brain: One spot for all answers. Supply your revenue team with instant insights for pipeline risks and chances from a single knowledge source.
  
• Real-Time Smart Suggestions: Get live tips for representatives facing tough objections or stalled deals. Guide them instantly to the right next steps.

Ready to see your forecast accuracy go up? Try Thunai for free and see the change in your revenue operations!

FAQs on Revenue Intelligence Platforms

What is the difference between Customer Relationship Management and Revenue Intelligence?

Customer Relationship Management is a system of record that relies on manual data entry to store customer information. Revenue Intelligence is a system of reality that automatically captures data from emails, calls, and calendars to give dynamic insights.

How long does it take to see returns from a Revenue Intelligence platform?

Many enterprise revenue intelligence platforms deliver value quickly. For instance, Clari customers often see a payback period of under six months. They see significant returns over three years.

Can revenue intelligence tools help if my Customer Relationship Management data is messy?

Yes, but with conditions. Forecasting layers need clean data. However, data automation platforms function specifically to fix data hygiene issues. They automatically capture and map missing contacts and activities.

Do these revenue intelligence platforms replace sales managers?

No. Revenue intelligence platforms support managers and sales executives. By automating the data collection and basic forecasting, managers can spend less time on administration. They spend more time on high-value coaching.

Is Revenue Intelligence only for large enterprises?

While originally built for enterprises, the market is moving. Smaller businesses between 10 and 50 million ARR benefit immensely from data automation tools. They build a solid foundation for growth before growing to complex forecasting.