How Do You Start Using Predictive Sales AI?

Use our vendor lists or research articles to identify how technologies like AI / machine learning / data science, IoT, process mining, RPA, synthetic data can transform your business. AI will analyze your sales reps’ actions and leads will be analyzed to suggest the next best action. No one wants to waste time on email setting up a demo, when they could be closing another deal. Though AI applications are numerous, correct prioritization is key to success. Process mining can help sales teams to automatically monitor and manage their sales operations by extracting and analyzing process data from CRM, other relevant IT systems, and documents. Use your Customer Relationship Management platform’s marketing intelligence features to combine the data.

But in order to fully realize the technology’s enormous potential, chief marketing officers must understand the various types of applications—and how they might evolve. Gather and add data from shipping, fulfillment, customer service and technology on what and when products and services are questioned, returned and/or replaced by customers. Then sales leaders can share insights and best practices across the team. This knowledge also helps managers choose new team candidates with similar capabilities consistent with quota-achievers. Sales teams already using AI are dropping call times by as much as 60%-70%, according to the McKinsey study.

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It does, however, help teams automate repetitive tasks, enabling them to prioritize more effectively and close more deals by providing insights into a buyer’s behavior. First, identify the different types of data sets that exist within a company that can be combined to give a more complete picture of the customer base. For example, the sales department obviously has historical purchase data, and the marketing department has website analytics and data from promotional campaigns (e.g., response rates from clients). Combining these data sets can allow an AI algorithm to make better predictions about who is more likely to respond to an offer. The smarter and more integrated AI applications are, the more worries customers may have about privacy, security, and data ownership. Customers may be skittish about apps that capture and share location data without their knowledge or about smart speakers that may be eavesdropping on them.

However, as demonstrated in the scheduling example above, plenty of applications can automate and accelerate business-process execution, thereby increasing productivity, without introducing new value or intelligence. When salespeople hear about the idea of AI for sales training, they often react in one of two ways. Or they’re nervous, hesitant and worried that the ai revolution will take over their jobs.

Prediction: Improve forecast accuracy and anticipate prospects’ behaviors and actions

‌63% of top performers are using automation to determine what actions to take on accounts. Conversational Intelligence — resources that record, transcribe, and analyze phone calls. Research firm MarketsandMarkets predicts the global AI market size will grow from 58.3 How To Use AI In Sales billion in 2021 to a staggering 309 billion by 2026. Understanding which quadrant applications fall into can help marketers plan and sequence the introduction of new uses. You don’t have to wait until Tesla’s self-driving cars go mainstream to enjoy the perks of AI.

Then we’ll look at some top AI use cases you can adopt if you’re a sales rep. And you’ll come away armed with some ideas on how the technology can help you better make quota. Please don’t shy away from scaling it across teams as you eke out small wins. If a particular AI tool doesn’t work well for your team, don’t stop experimenting with other AI tools.

Free Tools

It also allows sales managers to save time where they might have before spent 1-1 coaching a sales rep. Manufacturing company Honeywell uses conversational AI tools in their sales kit to engage customers and coach their sales reps based on reports from calls and meetings. Using AI-enabled sales tools increased not only its customer encounters but also gave an estimated topline benefit of $100 million a year. A sophisticated AI tool creates and delivers highly tailored content for leads based on their profiles and previously viewed content. It can also identify patterns in best-performing promotional content and offer real-time recommendations about messages and channels customers like the most, boosting the chances of sales.

The vast majority of companies using AI or planning to also plan to increase staff. Salesforce State of Sales report, sales leaders expect their AI adoption to grow faster than any other technology. Now that you are ready to use AI to increase sales and boost your bottom line, here are a few AI tools that you can consider.

Data matters first in AI

It’s important to continually monitor what data is driving your AI’s decision-making, both to ensure the data sources are sufficient for driving the predictions and minimize the risk of undesirable bias due to limited data. We don’t teach AI how to solve a problem, we teach AI how to teach itself to solve a problem. This means that the exact method it uses is often unknown, or too complex to understand. One thing that causes people to distrust AI is not understanding how it works, or how it arrives at its answers. If your sales job is largely based on easy-to-answer, back-and-forth conversations, or functional scheduling, expect it to change dramatically — or even go away entirely — within the next two decades.

All these forms of AI assistance will enable sales professionals to get back to doing what they do best — selling — something they currently spend just 34% of their time doing, according to Salesforce. AI can be instrumental in giving reps the tools to say the right thing at the right time. Taste, tact, and timing are crucial parts of relationship building in sales. Knowing what to say and when to say it is what separates the best salespeople from the rest. It involves making a judgment call about what prospects need and want, and understanding enough about their lives to appear at an opportune moment.

How to Sell More by “Selling” Less

They can provide some help to customers during basic interactions, taking customers down a defined decision tree, but they can’t discern customers’ intent, offer customized responses, or learn from interactions over time. This eliminates the guesswork that sales teams have to do when it comes to cross-selling and reduces the risk of annoying existing customers with excessive cross-selling of products and services they’re not interested in. Machine learning software can analyze data from previous interactions with a lead and previous sales with other customers to predict the products and services that will be most attractive to each lead.

While marketing AI holds enormous promise, we urge CMOs to be realistic about its current capabilities. Despite the hype, AI can still accomplish only narrow tasks, not run an entire marketing function or process. Nevertheless, it’s already offering substantial benefits to marketers—and in fact is essential in some marketing activities—and its capabilities are rapidly growing. We believe that AI will ultimately transform marketing, but it’s a journey that will take decades.

• Lowe’s has been experimenting with LoweBot in collaboration with Fellow Robotics since 2016.
• You should use AI to gather insight based on a customer’s preferences.
• AI’s capability to act upon interpreted data also helps automate tasks and workflows, thus enhancing productivity.
• Also, it’s becoming increasingly important that businesses are available to their customers at all times, via multiple channels.
• The customers never knew they needed those products, but before they realize it, they’re already adding additional items to their carts.
• Using computational linguistics, NLP not only strives to understand the language being used, but to interpret the intentions and sentiment behind the words.

AI for sales forecasting can sift through this data, sort it, organize it and put it to action. This way vendors can get to know their customers, their prospects and their market in general by looking at the data they generate. This can do wonders for lead generation, pipeline monitoring, sales forecasting, real-time marketing or communication with customers, just to name a few benefits. Once companies acquire basic AI skills and an abundance of customer and market data, they can start moving from task automation to machine learning.

Dialpad Ai also helps reps understand the sentiment of a call, so that they can decide on the best opportunity to offer a complementary product. The algorithms will score leads and chances of closing, by analyzing customer profiles and previous interactions like email and social media posts. While there will always be a human element to generating leads, AI makes the task easier by helping reps reach out to targeted prospects. It also suggests responses during interactions, again using data to personalize and steer the conversation. Human sales leaders are pretty good at predicting sales numbers and setting goals, but AI can help them do this with greater accuracy.

88% of chief sales officers have already invested in or are considering investing in AI analytics tools and technologies. Align your AI strategy and tools with your overall goals, whether that’s business growth, improving brand awareness, or specific targets like reducing wait times. Based on data , AI works out which actions make the most sense and advises the sales team accordingly. But many sales activities may occur outside your CRM, which means they wouldn’t show up in your CRM data… It’s important to track and measure attribution, so that you can target future efforts in the right places, and AI helps you use big data to attribute results more accurately. You can then see which campaigns and customers are most effective at driving ROI.

We review existing use cases and shed light on potential applications for AI in sales in the future, and make suggestions on what sales leaders should be doing right now to prepare for an AI-powered future. When considering how ai for sales training can help your organisation, the best starting point is to assess the sales training tech you already have. Begin your preparation by conducting an audit of your current sales training tools to get a holistic view of your in-house capacities. That’s because AI is creating practical value for sales teams by giving them superpowers, with several real-world use cases and tools being used today. The biggest benefit of predictive sales AI is that it removes the risk of human error from sales planning.

• This is a step toward moving a deal to the next sales stage or developing a pricing model based on the general preferences of a prospect.
• AI-powered ABM platforms can help you pinpoint where interest in your business is coming from and how your sales and marketing teams can best translate it into deals.
• If that’s a scary thought — or if it takes a dedicated person to manage a system to help prioritize those leads — there’s a better way.
• Imagine the deals you could close if you never missed a single opportunity.
• If a request for a quote comes in, automation can prioritize the lead so the sales team can act on it immediately.
• Don’t expect results in a short time—be realistic about targets while reps are getting to grips with the AI technology.