Having a hard time boosting your team’s sales for the month? Or are you a business owner who’s considering the use of artificial intelligence in improving your company’s sales? Regardless of your reasons, there’s no denying the extensive impact of AI in the business and marketing industry.

The Role Of Artificial Intelligence In The Workplace

Artificial intelligence (AI) is one of the many products of technological advancements that continue to prove its necessity in human life. Be it in the healthcare industry, education sector, agriculture, business and marketing industry, and in the workplace, AI serves as a beneficial tool in enhancing productivity and quality of work. When it comes to sales, in particular, the use of sales analytics software is said to be beneficial in reducing human error, handling repetitive jobs, and providing digital assistance.

In terms of its use in the workplace, there’s no going around the fact that AI offers tremendous help in managing tasks that are deemed difficult or inconvenient for human employees. Apart from that, it’s also shown to effectively bolster team efficiency and productiveness. While the issue of AI replacing human employees in the workplace is still a debatable topic, you don’t have to worry about these technological tools replacing human workers. Instead, they provide tools to better boost productivity, handle management tasks, and improve sales forecasting.

4 Benefits Of Artificial Intelligence In Sales

Artificial intelligence (AI) isn’t only known to offer convenience and ease in the workplace, it can also be a great help in boosting company lead volumes, improving sales rates, and bolstering overall sales performance. Because of these numerous advantages, sales agents can now channel all their efforts and focus on what matters most—their sales revenue.

Specifically, some of the greatest advantages of AI in terms of company sales include the following:

1. Boosts Customer Experience

AI is crucial in providing sales teams with digital assistance to immediately gain customer insight, better understand customer needs, and manage the customers’ expectations. Such intelligent tools can also be beneficial in building the clients’ trust and loyalty.

In terms of tracking customer experience metrics, AI also helps sales teams effectively monitor customer service and customer satisfaction key performance indicators (KPIs). Artificial Intelligence also makes for an easier process of managing customer activities regarding their product choices, the services they’ve availed of, and their previous engagements with the firm.

As a result, sales teams and representatives can now focus more on improving their sales revenue and promoting personalized interactions with clients. Additionally, AI streamlines and highlights the most productive accounts, which influences sales marketers to prioritize generating leads. With such a complete grasp of the opportunities and their potentials, sales teams are more career-driven and fixated to bolster their sales.

2. Improves Sales Forecasting

Sales forecasting is a crucial part of any business marketing strategy. Not only that, but it’s also an integral part of onboarding processes and the payroll system. Thus, poorly managed sales forecasting can result in the drastic diminishing of a company’s credibility. To avoid such scenarios, leading business industries maximize the use of AIs in increasing sales forecast accuracy and handling pipeline management.

These highly efficient systems pave the way for more opportunities in providing realistic solutions and assisting sales managers to generate and close deals. Such AI-driven insights allow the sales team to tune up their forecasting processes and create little tweaks in their standard work quality to efficiently deliver accurate forecasts.

3. Time-Saving

One of the primary responsibilities of sales teams is to focus on improving their sales revenues and achieving quotas. However, they often have a hard time dealing with time-consuming manual tasks, which significantly decreases their focus on their sales. Generating more leads and handling concerns regarding customer satisfaction scores—one of the key metrics businesses should track—can impede them from accomplishing their responsibilities.

In that aspect, AI serves as a beneficial tool in relieving sales teams of tedious manual work by managing appointments, communication channels, and other fundamental sales activities. Through this alternative, sales teams can effectively focus on selling and establishing good relationships with customers instead of doing manual work. This also makes them more motivated and goal-driven.

4. Enhances Pricing

Aside from helping sales teams promote quality work and boost sales revenue, another notable benefit of AI in the business and marketing industry is its role in the price optimization of items. Particularly, machine-learning technology tracks all sales data, including size, location, and previous deals to come up with a reasonable price.

When it comes to sales marketing, pricing is an integral factor that primarily garners the attention of potential customers and increases the possibilities of closing deals. In that aspect, AI guarantees full protection of corporate margins by incorporating pre-authorized discount limits. Subsequently, optimal pricing boosts customer experience by reducing alternating business negotiations that can slacken the processes and disrupt the smooth flow of business.

Bottom Line

Improving sales revenue and attending to other work responsibilities aren’t as easy as they may seem. While some people can multitask, there’s no guarantee of optimal sales volume for business owners. Hence, the growing need for artificial intelligence. Machine learning technologies can significantly help sales teams in bolstering customer experience, improving sales forecasting, reducing human error, and enhancing pricing.

Through these expert systems, enhancing sales revenue has never been easier.

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In our last article we looked at how productivity is one of the core benefits of a bank gaining control over its data and analysing it more effectively. But once a bank has gained this control and insight, how does it go a step further by augmenting sales teams with AI and machine learning tools that can digest large data sets and alert them to the needs of their clients?

Traditionally, banks have always held an information advantage over their clients – in fact their business models have been specifically designed to leverage the market information to which they have access and transform it into value enhancing insight.

But in recent years, this advantage has been slowly chipped away at as the markets have become increasingly electronic and the buy-side has upped its game in terms of the data to which it has access, and its ability to analyse large amounts of it. As market and price transparency has increased, one of the core competitive advantages of a bank’s sales desk has been eroded.

Against this shifting backdrop, banks are starting to realise the potential power of innovative machine learning and AI tools in helping them to upskill and maintain their competitiveness in the sales arena.  There is a dawning realisation that backward looking BI analysis is not fit for purpose in driving business forward, especially in this era of utilising AI to squeeze every possible efficiency and productivity from the resources at hand.

Some are now starting to deploy these technologies to enable predictive and prescriptive analytics, as well as connecting systems to prompt them as to the next best action for their clients. By absorbing information that might otherwise be missed, AI delivers the analysis to drive new sales engagement with clients and by delivering those insights at the optimum time.

Investment and adoption at scale is expected to increase significantly over the coming years. This comes as no surprise when you consider it has been estimated by McKinsey that AI can potentially unlock $1 trillion of incremental value for banks^[1]. These tools can be thought of as a GPS for the sales desk – those banks without it will struggle to compete against more forward-leaning firms who are empowering their employees with the most advanced digital tools.

The evolving role of the salesperson

According to a recent report from PwC, almost 80% of banking and capital markets CEOs see skills shortages as a threat to their growth prospects.^[2] This is because, quite simply, banks haven’t managed to keep pace with the changing manner in which their clients want to interact with them.

While no one is suggesting robots will completely replace salespeople any time in the near future, there are certain skills that can be enhanced when man and machine work together in tandem. One of the main skills that clients increasingly demand from banks is a more customised and tailored experience, which in turn drives a more intimate and refined relationship.

In addition, as electronification continues to grow, sales teams tend to manage a larger pool of clients across asset classes. Clients expect salespeople to provide a seamless service in multiple asset classes and have a global view of flows across the organisation.

Data therefore needs to be aggregated from across the organisation and made available to salespeople in one consolidated and comprehensive view so they can, for example, alert clients about new investment opportunities as they unfold – no matter the asset class.

Bridging the skills gap

In recent years, a growing number of large investment banks have launched ambitious projects to apply AI and machine learning techniques to previously unexplored data sources, in order to bridge the skills gap and improve how they sell to clients. A recent survey found that 75% of banks with over $100 billion in assets are currently implementing AI strategies.^[3]

Using the right technology, a combination of internal transaction data, external data feeds and unstructured data sources such as newsfeeds, can be standardised and aggregated into one holistic view. AI-powered advisory tools can then be applied to help banks anticipate client activity in order to build inventory for expected demand, identify unique and unforeseen market opportunities, extract timely information from news and websites, and alert sales based on market triggers.

Using AI and machine learning you can, for example, see which customers are likely to defect and move their business elsewhere, and therefore up your defensive measures.  After all, it is much more expensive to acquire a new customer than it is to maintain an existing one. You can also become more responsive and relevant to clients, because you are able to see what customer activity you anticipate on a particular day and then serve that customer with the appropriate inventory.

This technology has been leveraged over the last number of years to improve the service high-street banks deliver to retail customers. However, within investments banks the benefits of these same tools are beneficial to sales desks covering all types of clients including corporates, hedge funds, asset managers, insurers, pension funds, central banks and even internal clients.

Some banks are also exploring the use of natural language generation (NLG). This is a software process that automatically transforms data into a written narrative, making lightning-fast generation of expert business intelligence and reporting a reality in today’s financial markets.

NLG can generate intuitive prose that reads as if it were written by the best quant in the house at the click of a button, equipping sales teams with the collateral they need to offer up the most appropriate trading opportunities to their clients. These reports can even be prepared with enough variance and nuance in language and style to keep the copy fresh and engaging to the reader. This power of NLG is driving enormous time saving benefits across the organisation by taking laborious daily tasks and automating them at the click of a button.

Becoming AI-first

These are just a handful of examples of how AI and machine learning can help sales desks deepen customer relationships, provide personalised insights and recommendations, and, ultimately, turn the profit dial in their favour.

Banks that fail to make AI central to their core strategy and operations—often referred to as becoming “AI-first”—will risk being overtaken by competition and deserted by their customers in the coming years.

The current operating environment is both uncertain and challenging for investment banks, but a carefully planned programme that builds on cutting-edge data analytics and AI technology holds the key to driving growth and delivering the modern, information-driven trading experience that clients demand.

After all, it’s typically during periods of stress where relationships are forged. As a bank, if you’re able to guide a client through the fog of confusion, you will likely have a relationship for life – and AI and machine learning can assist in facilitating this.

But don’t just take our word for it. A client recently told us that since deploying AI technology across the front desk, their sales team had made 20% more calls, had 22% longer conversations with clients, and this had resulted in significantly more volume seen and executed. If you’re a salesperson known to have the best information, the client will call you first. It’s that simple.

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They’re called salespeople, but they spend shockingly little of their time selling. Instead, their days consist of administrative work, manual data entry, looking for potential customers and communicating with those prospects: cold calling, sending emails, scheduling meetings and having conversations — many of which lead to nothing.

This is both time-consuming and expensive for companies. Lost sales productivity and wasted marketing budgets cost organizations $1 trillion dollars a year, according to industry estimates.

Things are starting to shift, however. New tools, including ones that incorporate artificial intelligence (AI) — mostly machine learning and natural language processing — are changing the ways in which salespeople do their day-to-day jobs.

For all the talk about how AI is revolutionizing the business-to-business (B2B) sales process, its biggest advantage is more mundane: It is helping salespeople better manage their time.

AI is a transformative technology. Its power lies in its ability to extract, parse and analyze massive amounts of data almost instantly. In a sales context, AI-enabled tools help B2B marketers gain a more nuanced understanding of their customers’ wants and needs and improve efficiencies like never before.

According to research from McKinsey & Company, organizations that use AI in sales cite an increase in leads and appointments of more than 50per cent, cost reductions of 40–60 percent and call time reductions of 60–70 percent.

Interestingly, the most innovative tools are also the most practical. Today’s AI-powered software does everything from write emails to schedule meetings to detect sales behavior. This helps salespeople identify viable leads and close more deals.

Take, for instance, chatbots. Chatbots use AI to conduct conversations via video, audio or text. Chatbots begin the sales process by asking customers basic questions related to their role, industry and company size.

These low-level questions weed out those who may not meet the minimum qualifications of a company’s prospect profile. No salesperson wants to waste time in a conversation that’s not going anywhere.

Chatbots and lead scoring machine learning tools further improve and enhance the sales process. Lead scoring determines the worthiness of potential customers by attaching values to them based on their interest in a given set of products or services.

Scores not only help salespeople spot potential customers more quickly, they also help salespeople customize their pitches by mapping out an individual prospect’s needs.

That’s not all. Virtual sales assistants and chatbots can arrange meetings and calls, which drastically reduce the amount of back-and-forth scheduling details that often swamp salespeople.

Intelligent predictive engagement tools are another illustration. These AI-powered tools remind salespeople to reach out to prospective customers and even recommend what to say during that follow-up call or email. After all, the key to any follow-up with a client is relevant and meaningful content.

Finally, there’s process automation. Automation, along with predictive analytics, helps identify relationships between pieces of data. This allows salespeople to develop a deeper understanding of customer behavior and helps them forecast future sales more accurately.

Prescriptive analytics, meanwhile, helps salespeople navigate the sales process by uncovering the best path to value for customers, according to a recent research report by Gartner. Put simply, it enables salespeople to adapt and customize their product recommendations based on their customers’ individual needs.

These AI-powered tools are geared at improving sales productivity. They eliminate tedious busywork, such as logging calls or taking notes, and allow salespeople to focus on the essential parts of their job.

Importantly, they empower salespeople to engage with customers who are most apt to buy their products and services.

To be sure, just because these new tools exist does not mean that salespeople will embrace them. Case in point: A large number of customer relationship management (CRM) implementations fail because salespeople do not want to use their time doing data entry. (They, understandably, prefer to spend their time selling.)

However, these data inputs are vital to helping salespeople derive value from CRM by generating the kinds of insights necessary to improve their product’s attractiveness in the market and increase sales. To realize the value of CRM systems, salespeople need to be persuaded that adopting them is worthwhile.

There’s the rub: Given the biggest constraint for salespeople is the availability of “precious selling time,” organizations need to show salespeople that AI implementations can help reallocate their time toward selling. This provides the best opportunity to prevent AI tools from going the way of CRM systems.

But it’s likely that salespeople will need convincing. The value proposition is clear: Adopting AI tools will give them their time back.

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