What is revenue intelligence?
Revenue intelligence uses automation and machine learning algorithms to extract insights from sales calls, CRMs, and other sales data sources in the form of essential sales metrics such as:
Forecasted sales revenue
Revenue intelligence democratizes insight generation by simplifying sales intelligence for all. It scours through your sales data at the click of a button to present actionable, data-centric sales insights in real-time.
As a result, your sales team can use revenue intelligence to meet their sales goals and win more deals.
What is the difference between revenue intelligence and conversation intelligence?
Conversation intelligence is an AI-powered technology that automatically records, transcribes, and analyzes audio and video interactions between sales agents and customers. You can derive real-time, actionable insights from your sales conversations with real-time sales data and metrics.
Revenue intelligence is mostly about deal intelligence and insights on closing more deals to get more revenue.
Meanwhile, conversation intelligence offers insights into the performance of your sales team. With conversation intelligence, your sales team can:
Get clear insights from customer calls on their pain points, objections, and more
Understand what a customer is thinking and how to deliver a better experience
Know which pitches and call scripts are working
Revenue intelligence gets a lot better when you pair it with customer intelligence. That’s because Revenue intelligence thrives on data. Conversation intelligence provides that data.
How effective is cold calling?
Revenue intelligence aims to help you understand how to close deals and generate revenues with real-time conversation intelligence data.
It gathers data from multiple teams — including sales, marketing, and support — and integrates that data into a single source of truth.
This eliminates silos and integrates data from sales and marketing tools, providing sales teams with accurate, reliable data in real-time.
What are the benefits of revenue intelligence?
While each call recording software comes with several compelling features, here are the five key features of an effective call recording software:
1. Discover the reason behind lost sales
The best way to figure out the reason for lost sales is from the lens of a third person. One way to do so is to have your sales managers go through hours of call recordings or scouring through call transcripts.
However, a revenue intelligence platform lets you directly jump onto the desired part of the conversation by navigating across the call using keywords. Sales reps can use these insights to improve their performance and ensure revenue enablement, whereas sales leaders can rely on them for sales coaching and mentoring.
Moreover, sales leaders also get end-to-end, real-time visibility of all the deals and pipeline health, in addition to rep performance.
2. Develop more accurate revenue forecasts
The accuracy of forecasts depends on the quality and relevance of your sales data. With growing volumes of data, your odds of finding a needle in a haystack are better than extracting critical insights from trillions of data sets.
With a machine-learning powered revenue intelligence platform, you can easily find crucial sales metrics such as:
Most important leads or deals and their ticket value
Revenue that individual sales reps generate and their average deal size
A comparison of team performance against goals
Deal pipeline health
3. Use real-time sales data, rather than intuition, to make better decisions
The USP of revenue intelligence is accurate, reliable sales data. So, your sales team gets a birds-eye view of how the deals are progressing and which ones need more attention. They can also monitor the pipeline closely and fix any issues before it’s too late.
Sales teams can also adopt a data-driven approach to improving sales performance. They can spot winning patterns to fine-tune their call scripts and pitches. They can set more informed benchmarks for the reps and help them crush their sales goals.
4. Ensure more effective sales coaching programs
The sales process is complex and has dozens of customer touchpoints that change quickly.
When combined with conversation intelligence, revenue intelligence acts as a central platform for compiling all sales and marketing data to glean insights into a rep’s process or approach to sales calls.
It also lets you find these insights quickly without listening to entire call recordings. So, sales managers can coach reps on the fly and provide immediate feedback, which is essential to the learning process.
Moreover, sales reps can access their past calls, game tapes with the best sales pitches, essential call metrics, and feedback from sales managers to learn what customers care about and improve themselves.
5. Boost collaboration across the organization
Different teams can have different blind spots when extracting value from your data in the best way possible.
Your marketing team might consider a different approach for your campaigns. Your sales team might have a different idea of what their prospects want, and your product team could be on some other tangent. In such a scenario, they must contact each other to be up to speed on everything from the status of potential leads to customer feedback.
Since revenue intelligence software brings together essential customer data from CRMs, marketing tools, communication apps, and more, it acts as a single source of truth, which provides all teams complete visibility into all customer-related data and the actions taken by other teams to close more deals. So, teams stop working in silos and instead, share data freely to collaborate better and work toward common business goals.
What are the challenges companies face in implementing revenue intelligence?
Implementing revenue intelligence can be tricky without efficient processes to compile and manage data. Here are the three most common challenges sales organizations face:
1. Siloed data
Getting a complete picture of each customer requires putting together the data from various sales and marketing tools. Often, teams tend to store data in silos and don’t share that data with the rest of the organization.
In other cases, some team members don’t enter all the deal-related data on CRMs. As a result, it’s impossible to build a single source of truth with incomplete, siloed data.
2. Manual data entry processes
Some sales teams still rely on entering deal-related data manually, spending hours each week. Unfortunately, manual data entry processes are labor-intensive and error-prone. Inconsistent, inaccurate data will affect the insights from revenue intelligence and lead to poor decision-making.
3. Lack of transparency on customer-centric interactions
Siloed, incomplete, bad quality data makes it harder to understand and track customer interactions, deal stages, and the overall pipeline health. When teams work in silos, it can also be harder to collaborate without friction or communication breakdowns.
How to implement revenue intelligence
Achieving revenue intelligence is a three-step process that starts with getting the right data:
An excellent place to start is mapping where the business data comes from and assessing its quality and relevance in improving your overall performance.
The next step is to adopt a conversation intelligence tool that can help you gather sales data and use it to uncover your customer's pain points, discover their sales objections, and pinpoint the variables that lead to a sale.
Robust conversation intelligence provides you with high-quality, real-time sales insights for revenue enablement software.
Having identified the data assets and sources, the next step is to establish your revenue intelligence goal and metrics.
This is crucial as it helps you identify the data sets you must track and monitor to arrive at the metrics mentioned above.
Breaking down data and team silos requires getting all of them — sales, marketing, customer success and product — on the same page and building a culture of data.
It’s a good idea to demonstrate the importance and value of revenue intelligence and how to use revenue intelligence metrics to improve their performance and productivity.
It’s also important to bear in mind that cultural changes take time and adequate reinforcement to bear fruit.