A sales rep’s productivity is easily measured by how many meaningful conversations they have in any given day. It’s possible to spend half as much time on the phone and still close twice the sales. The challenge lies in knowing what accounts to work on, what to say in your messages and the right times to reach out. It so happens that these topics are ones easily tackled with Artificial Intelligence (AI).
Instead of relying on a spray-and-pray approach, software powered by AI can identify the prospects that are most likely to buy from you and figure out what kind of offer they're most likely to relate to. AI-powered technology can also help you spend valuable time previously spent on repetitive ho-hum work, and let you use those spare moments for activities that actually matter, like making calls to quality prospects and taking care of existing customers.
Today, almost every SaaS company claims they have an AI angle in their sales software or service offering that will help you as a salesperson accomplish your objectives. Don’t fall for the long con; a tool doesn’t become valuable merely by mentioning AI on its product page. Before you implement an expensive AI software, it’s essential that you sit down with your team and discuss the scope of the problem you’re trying to solve with AI. You also have to evaluate your current methods for data collection and, if necessary, adjust them before you start applying AI to the data. With clean data, AI software can make rudimentary decisions based on that data. However, not even the smartest of AI tools can provide great insight into poor data.
The whole point of using AI if you’re in sales is to be more productive and profitable. For that to be possible, you need to:
- trust the recommendations AI gives you, and
- make sure you provide it with quality data.
In this article, we’ll go through how AI can help you spend less time on repetitive tasks that can be automated and more time selling. We’ll also look into how the technology can help you be more pointed and timely in your approach.
AI and Sales: A Match Made in Heaven?
Salespeople have relied on Artificial Intelligence to help them be more productive ever since the mid-90s when the first sophisticated email spam filters were introduced. Nowadays, this type of a technology powers some of the most popular software used by salespeople, often without the majority of users even realizing it.
Sales organizations are not only competing over market share with their competitors. They’re also competing to draw in top talent to their company by making sure their sales process is attractive to them. Opinions are split: according to some, AI is just another buzzword du jour. While that may be true to a certain degree, the fact that AI brings lots of insight to salespeople’s fingertips can’t (and shouldn't’) be neglected or underestimated. AI can identify patterns to determine which leads are most likely to be converted into a deal, and formulate suggested actions which are, based on data, most likely to lead to the best possible outcome. AI can also help you streamline your workday.
Make AI your admin assistant
No one wants to spend time on monotonous and tedious tasks when he or she instead could have been working on an important meeting or been going through a proposal with a potential customer. According to McKinsey Global Institute, 45% of time spent on sales-related activities can be automated by adapting current technologies with AI.
There’s a vast ocean of sales tools on the market that can help you as a salesperson save time by automating many of those crippling basic tasks that you still perform on a daily basis (that being, if you haven’t already adopted AI as your admin assistant).
In our latest ebook The Best Sales Tools and Technologies 2018, we list 100+ tools in 10 different categories that can help you streamline your sales work.
Use AI for lead scoring
Sales reps can learn to sniff out good quality leads over time, but it’s a tough task. Just when you think you have your Ideal Customer Profile all figured out, one new trend or change in the market can put you back at square one. Why not let AI do the job for you?
AI can identify patterns to determine which leads are most likely to be converted into a deal, and formulate suggested actions which are, based on data, most likely to lead to the best possible outcome.
Machine learning identifies patterns to determine which leads are most likely to be converted into a deal. The algorithms can go back and read all your deals that were won and lost in the past and synchronize and analyze all data points. Without you having to do any dirty work, AI can recommend the right lead to approach and suggest the best way for you to do so.
Even though most companies are still figuring out how to get their predictive lead scoring models in place, the frontrunners are already moving from predictive to prescriptive models. The bottom line is, salespeople are not that interested in all those positive and negative attributes in the predictive models. They want to know what to do next to move their cases along the funnel toward a sale.
What data does AI want?
AI doesn’t need a lunch break, but that doesn't mean you don’t have to feed your AI software anything for it to be profitable. As stated above, AI will only provide you with valuable insights if you feed it with clean and relevant data. For AI to identify patterns in quality leads, the right actions for a salesperson trying to close the deal and the right time to reach out, you need data in four different categories:
- Descriptive data – what characterizes your prospects?
- Activity data – what actions have been taken by you and your colleagues? Have you called, sent an email or carried out a face-to-face meeting?
- Contextual data – what were the prevailing conditions at the given time? Was it good or bad weather outside? How was the economic situation?
- Results data – did you close the deal or not? What was the outcome of the activities?
If your CRM system isn’t currently filled with this type of data, you’ll have to look over your methods of data collection before you can make full use of any AI application.
Look into your crystal ball
As AI can help your predict what leads are most likely to convert, the technology can also help you better predict your sales results for any given time period. Regardless of whether you're a sales rep or sales manager, I’m sure you’ve struggled with making realistic sales forecasts.
AI-powered Sales Analytics software allow you to get a granular view, breaking down sales into comprehensible pieces when reviewing what’s working and fixing what isn’t. That means you can get help from this type of tool to predict a forecast and give an honest outlook on the month. Now the overzealous forecasts can be tempered and the sandbagging eliminated.
AI and Humans are Strongest Together
Whether you’re selling lemonade on the corner or software to large corporations, sales is as much of an art form as it is a science. Every sales process is a process, which requires sales prospecting, engaging, showcasing the service or product, negotiating and building strong relationships. Questions and concerns will arise, whether it be about pricing or competitor differentiators.
Whether you’re selling lemonade on the corner or software to large corporations, sales is as much of an art form as it is a science.
The true value of using AI as part of a sales program is the fact that man and machine in a partnership are exponentially more powerful than either of them standing by themselves. Humans need AI to process large amounts of data in real-time. But AI needs humans to then make educated decisions based upon the data that they're provided with. AI might advance so much that it can make these decisions for us in the future. But at this point, it’s far more effective to personally explain a company’s product differentiators and negotiate on pricing in person, using relatable anecdotes and known customer pain points throughout the sales process.
The future of sales and AI is bright
While there’s a long way to go until AI and sales is as common a combination as digital and marketing, it’s the direction we’re heading in. According to Gartner’s annual Hype Cycle (2017), deep learning and machine learning are at what it calls the “peak of inflated expectation,” but on the other hand, only 2-5 years away from mainstream adoption.
The same company is also predicting that the deployment of AI-related technologies will be a vital part of the future of B2B sales organizations, with 30% of all B2B companies employing Artificial Intelligence to augment at least one of their primary sales processes by 2020 - that’s less than two years away.