Artificial intelligence is quickly taking on a more important role in any organization’s tech stack.
And in sales, the need for automation is particularly pressing. AI directly tackles the top issues reps—as well as managers and executives—face every day, from long sales cycles to complex buying journeys.
Still, AI in sales isn’t a magic bullet.
It’s one part of a strategy that also requires a comprehensive, connected (and clean) data ecosystem, a strong coaching and training program, and a big-picture business strategy based on proven best practices and human experience.
Below, I’ll explain how AI can be used to increase sales revenue and why it should be a top priority for any sales organization.
What is AI in sales?
Artificial intelligence (AI) is a broad area of computer science focused on developing intelligent machines able to perform tasks traditionally done by humans.
AI is an interdisciplinary science spanning several applications and approaches, though recent advancements in areas like deep learning, machine learning, and natural language processing are transforming how we work.
When it comes to sales, AI is put to use to sort through the heaps of data generated by the sales process. It can be used to evaluate customer sentiment in communications, look for trends that lead to wins and losses in deal cycles, and other tasks that would take too much time for people to complete.
As a result, AI produces reliable insights that help sales teams tackle the biggest challenges in modern sales—long sales cycles, rising buyer expectations, massive data sets, etc.
What is sales revenue?
Since we’re looking at AI in the context of revenue, let’s also define “sales revenue” before moving any further. Sales revenue is defined as income generated from the sale of products or services.
It’s often used to define the “size” of an organization and is usually reported for a standard period of time: months, quarters, or years.
How to calculate sales revenue
Sales revenue depends on two things: price and quantity. You can calculate revenue using this simple formula:
Revenue = Units Sold x Average Price.
Sales revenue vs. profit
Sales revenue represents the total amount of income generated from products or services.
Profit is the amount of income left over after calculating all debts, expenses, additional income streams (think investments), and operational costs.
What can AI do for sales revenue?
The short answer is artificial intelligence can do a lot for sales.
While the idea of artificial intelligence and machine learning has long been linked to feelings of anxiety or a fear of being replaced by machines, the reality is, AI is a lifeline for salespeople that enables them to build more valuable relationships with buyers and in turn, close more deals.
Here’s a quick look at some of the key benefits AI brings to the sales funnel:
- Improve pipeline visibility. AI helps sales teams gain absolute visibility into pipeline, deals, and team activity. Using this data, algorithms can nudge sellers toward wins with step-by-step recommendations.
- Personalize the purchasing experience. Personalization has redefined the purchasing experience at every level and is now a critical part of the buying process. With AI and machine learning, reps can provide a customized experience, manage buyer-specific objections with ease, and respond to changes in real-time.
- Automate & control the sales process. AI helps reps navigate the sales process and avoid making mistakes that can cost them the deal. Sales leaders can implement playbooks based on proven best practices, then automate reminders to ensure reps follow a unified process.
- Eliminate uncertainty. AI enables users to make decisions based on data and brings more certainty to the sales process. AI can help you understand whether a deal is at risk and why, and provides signals that can help reps avoid the actions (or inactions) that cause deals to go cold.
Is AI replacing reps?
AI isn’t out to replace reps.
There’s a clear division between AI and human strengths.
AI is great at logic, crunching data, identifying relationships and trends, and natural language processing.
In the context of sales, AI can surface relevant information about a buyer while you’re on a call, or suggest who to call next based on historical data.
Other activities like prospecting and demo-ing are human-driven activities.
While AI isn’t replacing salespeople outright, you will be replaced if you don’t learn how to leverage the intelligence embedded in your sales stack.
That said, AI isn’t as complicated as you might think. In fact, many of the business tools you already use probably have some type of AI baked into the feature suite.
AI and machine learning are becoming more accessible and affordable—and as they become a requirement for doing business, there’s been a big push toward making business intelligence platforms more user-friendly/democratic.
AI in sales has more to do with data than algorithms
While algorithms might get all the attention, the AI revolution is really a story about data.
Artificial intelligence can do some amazing things for your sales force, but there’s a big caveat: your AI software is only as good as the data it receives.
It’s a real “you are what you eat” situation: if you want reliable insights, you need to make sure you’re feeding the algorithms with high-quality, accurate, up-to-date information.
Unfortunately, it’s easier said than done.
According to Gartner, 90% of AI initiatives will fail either due to a lack of data or a lack of data literacy or the proper training.
While many AI sales tools are user-friendly, creating a data environment that allows those tools to “be successful” is a whole other story.
Organizations must focus on creating a strong data foundation to support their data strategy and train their machine learning algorithms so that they get smarter over time.
It’s this step that makes machine learning difficult for a lot of companies.
- Get your CRM in order. The first step toward using AI to boost sales revenue is making sure you’re capturing data the right way. Most organizations use their CRM as the “central” hub for sales activity, so you’ll want to start there.
- Take stock of the entire data ecosystem. Not just what’s in the CRM but also data captured from any channel your customers might make contact with, as well as the tools you use internally. Your data ecosystem depends on your sales process, industry, and a whole host of other factors. But, might include social media channels, marketing automation platforms, and your content repositories.
- Integrate all relevant data sources. Salesforce points out that customer-facing teams operating in informational silos create “jarring” or “impersonal experiences for customers, while also causing communication issues that waste time and prevent core tasks from getting done”. Ensuring total visibility requires sales organizations to break down silos between all customer-facing teams and the tools they use to communicate with buyers.
So, once you’ve mapped out your data environment, you’ll want to then make sure that all the tools you use are integrated and that data flows between them. This ensures that everyone works from a single source of truth.
Once those elements are in place, you can bring in an AI tool to automate the data capture/organization process.
Our Revenue Inbox tool captures complete data related to your deals, prospects, and engagements and sync insights back to the CRM.
Sales forecasting
Sales forecasting is crucial for all sorts of reasons. It supports all big-picture decisions, from budgeting and hiring to developing new product lines.
If you’re still forecasting with spreadsheets, emails, or verbal interactions, you’re making major decisions without knowing the whole story.
While it’ll never be a perfect science, AI enables companies to create more accurate forecasts and plan for many versions of the future.
At the rep level, AI can:
- Identify which leads or opportunities are most likely to close
- Determine which deals or accounts reps should focus on
- Surface new opportunities, such as potential buyers who might be interested in your product or service.
For sales managers and business leaders, AI-powered sales forecasting creates value by providing real-time insights that inform the sales strategy. For example, AI can help sales managers forecast their team’s performance for the quarter.
This, in turn, allows them to customize training and coaching content to individual reps and update sales play based on the numbers.
How AI-powered sales forecasting boosts revenue:
- Real-time intelligence. According to the most recent Salesforce State of Sales report, 88% of high-performing teams say that current economic conditions make it important to anticipate consumer needs. AI enables organizations to keep an eye on the competitive landscape and what’s going on in the market. With real-time insights, organizations can act on emerging opportunities, respond to threats, and meet customer needs as they evolve.
- Better resource allocation. Accurate, AI-driven forecasting makes it easier to allocate internal resources. Sales leaders gain a better understanding of cash flow, rep activity, and factors like seasonality that could impact the organization’s performance.
- Smarter sales coaching. AI enables coaches and managers to identify which deals are on track to close and which are at risk. They’re able to intervene, helping individuals master the specific skills they need to close deals, which in turn, helps the company hit sales targets.
Guided Selling
According to Gartner, sales reps are considered to have the worst data literacy rates in the organization. Sales hovers around 43%, compared to marketing (49%), finance (53%), and customer service (49%). While reps aren’t that far behind, those numbers aren’t great.
AI-enabled Guided Selling makes data more accessible, it also provides prescriptive advice for how to respond in any situation based on contextual clues.
How Guided Selling increases sales revenue:
Guided Selling platforms use AI to analyze buyer behavior, seller performance, and external forces that might influence a deal. From there, platforms can recommend the best course of action, guiding reps toward the close one step at a time.
In Revenue Grid, you can “program” AI-based Revenue Signals to alert your team to any important changes made to active deals, your pipeline, or the strategy.
The platform’s baked-in AI analyzes actions against other connected data sources to determine which activities produce the best outcomes. Additionally, the algorithm can predict when a deal is about to drop out of the funnel or stall out. From there, it offers real-time alerts with recommendations for how to turn things around before it’s too late.
Automate workflows
According to Salesforce, top-performing companies automate repetitive tasks.
AI’s greatest strength is arguably its ability to take on tedious, low-value, or error-prone manual tasks. In sales, AI supports productivity by eliminating time-consuming tasks like data entry and analyzing and interpreting data analytics.
For instance, it can be used to automatically update records in the CRM or send out alerts when it’s time to follow up with a prospect.
On the sales operations side, automation can be used as a tool for making sure your sales reps “stick to the plan.”
For example, in Revenue Grid, organizations can automate playbooks and known best practices, ensuring that reps follow a specific set of steps.
At each stage in the sales process, reps need a defined set of activities to help them engage buyers. The AI walks reps through the predefined process, but it also sizes up the situation and recommends actions that align with changing circumstances.
How automation can increase sales revenue:
- Helps reps focus on the right activities. By taking over the tasks that eat into precious selling time, reps can focus on activities like relationship building and “sense-making” that provide more value to the buyer and make better use of their human strengths.
- Automatic data capture. Organizations can use automation to capture observable outcomes at each stage of the pipeline. This means that sales leaders can identify what top-performers “get right” and rapidly diagnose problems when something goes wrong. The result? Fewer lost opportunities and more wins.
- Automate follow-up sequences. AI-enabled platforms like Revenue Grid allow users to set rules for automated sequences—calls, social posts, texts—that feel personal. Use persona-specific templates and smart scheduling to plan ahead, while AI adjusts steps if deals take an unexpected turn.
Data analytics
The rapid rise in digital activity means sales teams now work with a ton of data on buyer behavior, content engagement, and product usage habits.
Unfortunately, we’re way beyond the point where humans can interpret the data at their fingertips, much less put it to good use.
AI-enabled analytics drive sales revenue by removing uncertainty from the sales process. Algorithms can surface patterns in buyer behavior, sales performance, and external conditions.
This helps sales leaders determine which tactics are most effective at each touchpoint.
How intelligent analytics boost revenue:
AI analysis increases revenue by helping reps make the most of every interaction they have with buyers.
- Lead and account intelligence. Insights can be used to improve sales pitches, create personalized content, or suggest the best subject lines for follow-up emails based on individual characteristics, market conditions, and proven best practices.
- Drill down into specific opportunities. Reps and managers alike can track deal progress and identify when a prospect is getting serious about buying or going cold. Users can look at each deal’s status and understand what’s driving wins and losses.
- Content personalization. AI can recommend content based on customers’ and prospects’ social feeds, engagement history, or persona.
- Respond to changing needs. According to Forrester’s 2021 Predictions report, 40% of B2B reps said they plan on modifying sales tactics to adapt to a remote selling environment. Analysts predict sellers will continue to seek out more dynamic ways to capture buyers’ attention and respond to new needs and preferences. AI-powered analytics makes it easy for reps to identify changing circumstances and respond without missing a beat. Thus increasing the chances of closing when the buyer flips the script.
Final thoughts
In just a short time, AI has gone from the stuff of science fiction to a critical tool for competing in today’s rapidly evolving business landscape.
With its potential to streamline workflows, personalize solutions, and predict the best actions for closing deals, AI is a powerful weapon for increasing sales revenue and setting the stage for long-term success and a true understanding of your customers.
To learn more about how to leverage your data correctly to scale stronger even with a small budget, check out RevGarage’s upcoming webinar with Mark Roberge and Justin Michael. The topic is using a scientific approach to building a powerful sales team and the agenda is open—you and other attendees can submit questions and get answers directly.
