The next great technological revolution is at our front door as businesses start to embrace artificial intelligence to filter qualified leads and easily hit their sales goals. Gone are the days of weary travelling sales reps, and short are the days of sales teams guessing about qualified leads.
AI is able to filter your prospects and learn patterns in your sales flow to better prioritize your actions. Your time will be spent more effectively, and your conversations better.
Here’s how AI is changing the sales process for the better.
Big data takes the guesswork out of lead prioritization
Data is replacing intuition as a sales tool.
“In the back of their heads, most sales professionals have some vague idea of who is likely to buy their product,” Gary Gerber writes at the Selling Power blog. “It’s based in part on genuine experience, and part on plain old guesswork. But new AI tools are emerging that can analyze your existing customers’ profiles and derive a highly … well, intelligent set of target customers for you to pursue.”
Not only can AI highlight potential leads, but it can also suggest products and solutions that would interest potential customers and meet their needs.
“Sales professionals make critical decisions every day, deciding which prospects to reach out to, what product and service offerings to highlight, and which communication channels will work best,” Wrik Sen explains at CXO Today.
“Many salespeople make these decisions based on intuition or follow an organizational playbook. [AI] offers a better alternative by making the buyer central to the process, and applying artificial intelligence to the data.”
All of these tools are relatively new, and innovations in data collection, data management, and data literacy will only strengthen their capabilities, Amanda Kahlow writes for Inside Big Data. After all, “over 90% of the world’s data has been created in the last year alone.”
Historically, sales teams have only had a 2D image of their prospects. These new models turn them into multi-dimensional prospects with specific needs and opportunities.
The role of sales managers is starting to evolve
If the role of the salesperson is changing, then the business as a whole will be affected. That means sales team leaders must adapt to newly required skillsets, as well.
“For sales teams to truly be effective, they must have leadership in place that supports the work they do each day.” Steve Olenski writes at Forbes. “Data-driven sales managers will be in high demand as businesses realize the importance of analytics in the sales process. When sales managers arm teams with the tools they need to source workable leads and close those leads efficiently, they see higher levels of success.”
Along with a strong backbone in analytics and data science, development skills will also be in demand within sales departments.
“AI is continuously developing and being refined. As it develops, having access to digital media and coding skills will be a requirement,” Liz Alton writes at Sales and Marketing Daily Advisor. “Even if you’re outside technology development, it’s going to be important to have the technological literacy and skills to navigate the evolving landscape.”
All of this change is actually good news for sales teams that worry about AI making their jobs redundant. The roles aren’t going away; they’re just evolving.
“Forrester made waves with a report that said that 20 percent of B2B sales jobs — 1 million in total — would disappear by 2020,” Chris Bucholtz writes at CMSWire. “Salespeople will need to evolve into subject matter experts — on both their own products and on the methods that those products can be delivered going forward.”
AI reduces mundane tasks and frees time for relationship-building
Ironically, this is all good news for sales teams that aren’t tech-minded. AI can eliminate many human-machine interactions altogether: While the machines identify leads, salespeople will be responsible for applying the human touch.
“For the companies that embrace radical transparency and company-wide adoption, tools like automated data capture and predictive analytics will become the foundation of a new customer-centric culture,” Bullhorn’s Mike Restivo says.
“Responsibility for customer relationships will transcend sales and marketing teams as staff at all levels capture vital information — whether related to new business opportunities or existing relationships — that may otherwise have fallen under the radar.
AI works to sort leads for you, reducing repetitive or mundane tasks.
“The everyday hassle of monitoring the required orders and sorting it out will require regular interaction with the team, which will take away your valuable time that you need to focus on other critical areas of your business,” Patricia Vaz writes at Tweak Your Biz.
Think about how much time your team spends trying to find qualified leads. If your team is like most, that’s a lot of time. But if leads were generated automatically, your team could spend more time closing and working toward your sales goals.
“On average, sales reps spend 80 percent of their time qualifying leads and only 20 percent closing,” Alex Terry writes at CRM Magazine. “Qualifying leads requires advance research and many phone and email hours trying to hone in on a lead that can be turned into a sale. What if this vetting process could be done by a machine that engaged all inbound leads in an amiable, human-like way?”
Marketers will send sales teams better qualified leads
Along with helping sales teams directly, AI also assists marketers in tracking customer interest and moving them into the sales funnel.
“These indicators paint a more holistic picture of a lead’s level of interest, beyond just a form submission typically associated with lead generation content like ebooks.” writes Amy Wood and Helen Arceyut at Unbounce. “And automating lead scoring takes the pressure off marketers having to qualify prospects via long forms, freeing them up to work on other marketing initiatives.”
Think about it this way: Your marketing team collects the ingredients needed to make the sales recipe. If the ingredients are poor, the chef has nothing to work with.
“Chances are, you’re already monitoring leads’ engagement with your ads, emails, and website pages in your marketing automation system,” Jingcong Zhao writes at Socedo. “These are all signals that indicate buying interest and can be incorporated into your lead scoring model. Social media activity represents another opportunity to understand your leads and personalize your messaging.”
By channeling customers deeper into the funnel, the leads handed to sales teams improve even before the AI system starts filtering and identifying them.
“Timing is key in B2B sales situations, and engaging potential buyers at the right time is a big problem for both marketing and sales teams,” Shelley Cernel writes at KnowledgeTree. “Another benefit is the access to immediate data and feedback — brands will be able to literally have ongoing dialogues with their customers and get instant feedback.”
With the ability to adjust quickly to messaging and products, marketers can better tailor their messages and let fewer leads slip away.
Replenishment and upselling options become clearer
A business needs to strike a balance between generating new sales and retaining existing customers in order to continue growing.
AI can help answer questions like “When will this customer buy again?” and “How do they use this product now?” We’re already seeing tech giants utilize big data to make decisions and identify potential increases in demand.
“Uber uses data to provide rides, but it also uses heat maps to analyze patterns and help drivers be in the right place at the right time,” explains Tx Zhuo, managing partner at Karlin Ventures. “If you want to jump into the on-demand game, discern what problems you can solve using data.”
Meanwhile, Amazon uses machine learning to expand beyond replenishment. It’s able to discern buying patterns and anticipate the needs of customers beforehand.
“Machine learning technology also helps Amazon predict and forecast demand, thereby informing supply decisions to prepare for any given increases and wanes,” Luke Turnbull of Principa explains.
“Keeping up to speed with fashion trends and styles is vital in such a competitive and seasonal industry. Retailers can’t afford to ignore the advantages that technology like machine learning brings to the table.”
From a B2B perspective, AI — and machine learning specifically — can monitor industry trends to inform sales teams about potential barriers to buy or opportunities to close a sale.
“For truly game-changing functionality, machine learning would have to be applied to all sales process-relevant data,” Giles House writes at Martech Advisor. “Once that happens, AI could function as an incredibly useful assistant, helping each salesperson make the right decisions, instantly providing the right content and giving on-point upsell and cross-sell suggestions.”
Beyond functioning as a perfect sales assistant, though, AI’s big promise is that it reduces friction for salespeople as they navigate their stacks of sales tools. In turn, this will allow sales reps to spend less time on predictable, repetitive work, and more time building relationships with potential customers.
The future of automation isn’t replacing people, but rather letting them focus on the human element of sales.
Originally posted on SalesforceIQ blog.