October 21, 2019
Updated: November 16, 2020

How AI and Machine Learning are Changing Sales Automation

Sales automation software has become an in-demand solution among businesses of all industries and sizes. Sales and Marketing teams are realizing significant advantages thanks to cutting-edge systems that can shorten the sales cycle and automate menial processes that save precious time and capital resources. 

Leading the pack in automation technologies are artificial intelligence (AI) and its more advanced variant, machine learning (ML). Yet some businesses may be hesitant to invest in Marketing automation like AI and ML, either because such tools seem too far out or the workforce is afraid of being replaced. 

Often, companies simply don’t know where to start:

  • Which department should you augment first with AI or ML?
  • Which job functions are most in need of automation?
  • Whose positions are to be most impacted?

What’s more, the upsides of automation tools vary — quantifying them can be difficult at the onset of high-spend tech integration.

Far from creating an entirely robotic sales force, though, ML or AI for sales can empower your sales and marketing staff to achieve more. Beyond the efficiency boost that these tools provide, perhaps the biggest benefit of sales automation is a more knowledgeable sales force . All that time spent organizing CRM data, chasing content or otherwise not selling can instead be put toward more important customer-facing activities.

What is Sales automation?

So what exactly does Sales automation mean in the modern day? At its most basic level, Sales automation is about accelerating and enhancing the Sales process through technology that eliminates or automates back-end labor, thus allowing Sales and Marketing teams to dedicate more time and resources to valuable tasks. In short, with Sales automation tools, your reps will spend more time closing deals and generating revenue than they do prospecting or talking to leads with no real purchasing intent. 

That’s what makes AI for sales so important: its bottom-line impact. A Harvard Business Review survey found 30% of early AI adopters have increased revenue and are 3.5 times more likely to expect notable profit-margin growth.

With the right tools, Sales professionals will:

  • Never forget to follow up with a potential customer and subsequently lose a deal.
  • Never scramble to find or disseminate timely, relevant content that speaks to their unique needs or business challenges.
  • Never make a mistake by contacting the wrong stakeholder or having inaccurate lead information.
  • Never be out of the loop with the near- and long-term sales forecast.

Sales force automation can alleviate your staff of the burden of completing routine workflows, which become mindless and resource-draining over time. Freed by automation tools, Sales and Marketing are unleashed to be productive, creative and, ultimately, successful.

What makes AI and ML top Sales automation strategies?

Artificial intelligence and machine learning may seem like futuristic technologies, but they are very real in today’s business landscape. In fact, many companies have prioritized integrating such sales AI tools. According to Gartner, the number of enterprises implementing AI software grew an astonishing 270% between 2015 and the beginning of 2019.

As companies pursue digital transformations, Gartner notes, AI is not being used to solve complex tasks and replace human workforces, but rather to serve existing Sales and Marketing teams. Automation helps improve preparedness and intelligence to create super-charged Sales and Marketing.

But how does that happen? Let’s examine how AI works in a business sense, first. 

AI as business currency

Artificial intelligence is a computer science that aims to design intelligent software and systems that mirror how humans process and act on information. So, imagine a salesperson who is poring over data points to prospect for leads. In the time it might take him or her to complete one buyer profile, AI-assisted Sales automation software could vet hundreds of customers, if not thousands. 

Alternatively, a user could develop a search profile according to company size, location, revenue opportunity or industry and have the AI automatically populate the sales pipeline.Through this automation of the sales process, reps can more effectively target prospects most likely to buy – and AI helps in that area, as well.

Lead scoring: A use case

A notable example of the value-add nature of AI for sales is its ability to score leads. A salesperson could organize all those leads and still not be sure which to call first, perhaps just going by alphabetical order. Lead scoring through AI can measure the intent of prospects by various signals these potential customers send, whether on social media or through search queries about products and services similar to what you sell. Armed with this knowledge, the sales rep can prioritize accounts showing the most promise. 

The customer and prospect data that’s continuously created, stored, and analyzed via AI can also be converted into comprehensive user personas that evolve over time, either at the consumer or business level. 

So rather than targeting imprecise versions of your target customer — say, enterprise companies in the logistics space — you can drill down into more practical, actionable character traits of ideal customers, like: privately held Midwest enterprise-level companies in the logistics space that have recently seen +20% growth and prefer to work with local vendors. 

With AI, granularity is no longer “the boring fine print”; it’s the goldmine.

This practice is often referred to as behavioral or firmographic segmentation, allowing you to spend more time targeting only high-value, high-spend prospects. Your backend automation tools bring these insights directly to you before you begin your work.

As an AI assistant learns the patterns of your sales organization, as well as the behaviors of prospects, the customer journey grows more detailed and data-driven.

Deep data analysis and insights

Machine learning, while a companion of sorts to an AI system, accomplishes different computations, often analyzing CRM data fed to it. The main benefit of ML is automation software that adapts to how your sales and marketing teams use it.

Consider this: These staff members often have little to no insight into whether customers of certain criteria tend to access the same sales collateral. ML-assisted sales automation tools can track engagement analytics and recommend content to send to prospects that match certain qualities of customers you already have. ML can surface other patterns and trends that help sales teams become more effective, or help marketing develop more relevant content, without having to be explicitly programmed to do so. Leveraging these various applications of predictive analytics for your business is a key competitive advantage.

What this looks like in practice is quite powerful. By uniting your Sales and Marketing efforts into simplified, more strategic workstreams, both departments are constantly in conversation with each other: Your sales reps are empowered to forward along intent-driven Marketing collateral to properly segmented prospects, and your Marketing team better understands the exact questions sales reps commonly hear. So now every new piece of content that’s created is, from the start, highly targeted and useful to multiple departments, and every deal that Sales closes is another data point that can be cycled back into the end-to-end sales process in the future.
Not only are the machines learning, but your staff is too.

What are the benefits of Sales automation?

The benefits of AI and ML reach far and wide across Sales and Marketing. Here are some of those advantages that best demonstrate the importance of Sales automation:

  • Personalization of the customer experience: Personalization is a default expectation nowadays; it must also be a default mindset for Sales and Marketing. Yet this can be difficult to achieve when there’s only so much time in the day. AI/ML-assisted automation tools can rapidly process and organize information so that salespeople can act on it, or go down a suggested content path based on engagement analytics.
  • Accurate data to drive decision-making: Manual methods of prospecting are riddled with potential pitfalls: Write one digit of the phone number wrong and the data salespeople work with is inaccurate. Information sourced from Sales force automation software is typically cleaned and verified so that users possess only accurate, actionable data.
  • Accelerated content and template creation: Closing the deal means signing on the dotted line. However, putting together contracts can be a painstaking process. A Marketing automation solution can generate templates based on documents that you’ve previously uploaded to your CRM, as well as recommend content to create based on gaps in your resource library or engagement analytics. This can condense the ideation phase and ensure Marketing resources are laser-focused on creating optimized content to drive leads further down the Sales funnel.
  • Better Sales force support: Sales managers sometimes need to complete mundane tasks that take up valuable time. Leveraging Sales automation to complete these tasks enables sales managers to deliver better support to Sales staff. Instead of fussing in the CRM platform, a Sales leader can give one-on-one coaching to a rep, or otherwise inspire collaboration with Marketing. Intelligent analytics also helps managers cultivate a high-performing team by mapping the behaviors of top sellers.
  • Streamlined communications: Reps will never need to set another calendar event to send an email or pick up the phone. AI-assisted automation tools help schedule communicate and can automatically push through reminders or follow-ups. Cutting down on the manual requirements of maintaining communications allows reps to further personalize what they do say to the customer.
  • Enhanced Sales intelligence: Machine learning can provide invaluable insight to drive Sales success. Such tools may be able to map customer journeys using historical data, allowing reps to better guide prospects through the Sales funnel and ensure they have precise, timely, relevant content before the lead even knows they’ll ask for it.

How to find Sales automation tools and resources

Organizations that want to invest in artificial intelligence or machine learning can think of Sales automation as part of the larger concept of Sales enablement. The goal of Sales enablement is to ensure reps are continuously provided with the resources and means to sell more efficiently and effectively. Sales force automation software empowers staff by giving them tools that considerably reduce the time they spend on housekeeping tasks. This allows them to dedicate their talents toward refining and personalizing the selling experience, which Sales automation can help with, as well.

It’s increasingly no longer a question of when to invest in AI and ML, but how. Sales organizations weighing such implementations need to look for a Sales automation platform that can deliver all the expected benefits.

With Showpad, you can leverage automation tools to power Sales and Marketing excellence. Take advantage of content and Sales analytics that help you discover what collateral performs best, replicate top seller strategies and automate processes to fuel productivity. Content and coaching recommendations can further identify next steps to take to drive success.

Contact us today to learn more or get a product demo.