Top sales executives today are well-paid for a reason: they sell, and they sell well.
However, did you know that the average sales representative spends less than a third of their week actually selling?
The rest of their valuable time is eaten up by planning, forecasting, researching prospects, and sitting in meetings. And while these tasks are important, they do detract from the time reps can spend closing deals.
Fortunately, artificial intelligence (AI) is now changing that. AI can be used to automate repetitive tasks, predict sales, and dramatically lower the amount of time reps spend researching and reaching out to prospects.
Curious what AI could do for your sales organization? Read on to learn what AI can do for sales, how it works, and how you can implement it at your company to help with customer interactions, sales operations and enablement, outreach, and lead prioritization.
Artificial intelligence (AI) is a type of technology that includes processes like machine learning, natural language processing, and deep learning. In AI for sales, these capabilities are used to make sales professionals’ jobs easier — by automating tasks, crunching numbers, surfacing opportunities, and suggesting sales copy.
But how does AI work?
Just like a sales development rep (SDR) might learn to write great cold pitch emails by studying a ton of examples and learning from a mentor, AI tools learn by being fed a tremendous amount of data. The platform then learns from these inputs to create outputs of its own, often detecting patterns that humans might miss — which can lead to the discovery of new opportunities, improved sales communication, and the highlighting of helpful customer data.
But AI and machine learning models don’t just produce new outputs — they’re specifically trained so that they continually improve their results. When these algorithms are being trained, they’re not just fed existing SDR pitches.
They’re also given the results of each of these pitches, along with huge data sets on the customers being pitched, so that they learn which types of content work best. They then tailor the pitches they write based on best results, the type of customer being pitched, the platform used for messaging, and the product being sold.
This same learning model is also used for lead generation and scoring, sales forecasting, and conversational AI.
Of course, SDRs and sales reps may modify their approaches based on their past experiences and the customer persona they’re pitching. But, far too often, these choices are based solely on hunches, which can be wrong. AI apps make decisions based solely on data, which is far more likely to lead to successful results.
Since computers have incredibly strong processing power, they can also churn out these outputs in a matter of seconds compared to your average SDR or sales rep. By completing routine tasks at a phenomenal speed in real time, AI can help salespeople accomplish more in less time.
According to Salesforce’s 2022 State of Sales report, high-performing sales reps are nearly two times more likely to use AI than underperformers.
This shouldn’t be surprising, considering the results reported by leaders that have added AI to their workflows:
And yet, in 2022, only 33% of sales organizations said they use AI. That means that two-thirds of sales teams are leaving time, money, and ultimately sales on the table.
AI technology is a powerful tool for sales teams, and it can help with just about any part of the sales process. With the help of AI, teams can now use data to make smarter decisions about their outreach and communication, sales forecasts, and lead scoring — and these days, AI can even engage in conversation with customers.
Conversational AI replaces humans in live conversations with clients, generally as chatbots.
Conversational AI programs can validate prospects, answer their questions, suggest products, provide updates, and walk new clients through onboarding. They free up sales reps’ and account managers’ time, can work with multiple clients at once, and they’re available to clients around the clock — long after your reps have logged off for the day.
According to a 2021 report by Gartner, 41% of SDR leaders cite messaging as their biggest challenge at work. Many sales teams receive minimal support from marketing and enablement teams, leaving SDRs to craft their own messages to prospects. As any sales rep can tell you, the success of those messages can vary drastically.
Fortunately, thanks to machine learning, AI can help sales reps craft the perfect copy for their prospecting. For example, using Copy.ai’s Sales Cold Email generator, SDRs and sales reps can use AI to craft cold email copy in a matter of seconds. All they have to do is paste in a prospect’s LinkedIn URL and include a couple of sentences on their company’s product:
Copy.ai will then provide them with a personalized email to send the prospect:
Even better: Copy.ai can write entire personalized sequences into your customer relationship management (CRM) and sales automation platforms:
Copy.ai’s LinkedIn InMail generator can do the same for sales reps reaching out to prospects on LinkedIn, providing them with three messaging options to choose from to suit their needs. Need to follow up with a prospect? AI sales technology can draft that message for you, too.
Curious about the impact AI can have on messaging? When JPMorgan Chase used AI to improve their marketing copy, they saw a 450% lift in click-through rates — the type of result that any sales team leader dreams of.
Once again, this is an area where machine learning shines. AI used for sales forecasting uses historical data and typical buying signals to predict a sales team’s future results. This can help sales managers identify:
This type of forecasting can help sales leaders understand where to spend their time, which team members might need additional help, and which customers they should be nurturing.
AI excels at pulling patterns out of large amounts of data — often catching trends that humans might miss. This makes it the perfect fit for scoring leads.
AI-based lead scoring tools will analyze the traits of your existing customers (such as their industries, size, and demographics), look at market trends, and sift through potential leads to help you identify and prioritize strong prospects. This can help SDRs and sales reps understand who they should reach out to first — knowing they’re working with validated data and not just a rogue hunch.
If the myriad use cases for AI in sales sound overwhelming, don’t worry. Most sales teams don’t integrate every AI sales tool into their tech stack all at once. Instead, you can take a methodical approach to decide which area to invest in.
Here’s what we recommend:
Once you’ve decided on a tool to move forward with, it’s time to implement it.
While AI has the potential to improve your sales process dramatically, you’ll get the best results if you implement it correctly.
Did you know that 33% of all SaaS spend goes either underutilized or wasted by companies? Often, this is because teams aren’t sure exactly how to use certain products.
Sidestep this issue by ensuring your teams know exactly when and how they should be using your AI sales tools. Provide training and documentation to ensure employees know where AI fits into their sales cycle and how to use it to maximize their time and results.
While AI may be new to the sales space, it’s quickly transforming what teams today are capable of. AI may not be able to convert a prospect on an hour-long call just yet — but it can take other tasks off your sales reps’ plates, so that they can focus on what they do best.
Ready to superpower your sales team with AI? Give our cold email and LinkedIn InMail generator a try — you can start with 2,000 free words on us.
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