Accenture, in a recent report, pointed out that up to 90% of B2B executives consider customer experience (CX) as a critical factor in achieving their organizations’ strategic priorities. Another study indicates that 75% of business buyers expect companies to anticipate their needs and send relevant offers, and a large percentage of business buyers would switch vendors, owing to a lack of personalized communication.

Fortunately, with the advent of Artificial Intelligence (AI), businesses can leverage machine learning and predictive intelligence to augment their marketing capabilities and boost their sales. With AI, it is not only possible to streamline the entire sales process, leading to immense time and cost savings but also introduce a high degree of personalization in business communications, leading to improved CX.

According to Gartner, up to 30% of B2B companies will employ some kind of AI technology to augment at least one of their prime sales processes by 2020, while 80% of B2B marketing executives expect AI to revolutionize the industry in the same year.

Well, to be honest, we feel that the AI revolution has already begun, and here’s what you can do to tap into the power of AI for meeting your business objectives:

1. Gathering Sales Intelligence

AI can transform B2B sales and marketing by predicting consumer behavior based on available consumer data and past actions. Using this information, B2B organizations can tailor their products or services to meet the changing needs of customers. 

In B2B Sales AI can be leveraged to track & follow the key happenings & updates of potential companies &  contacts. It is nearly next to impossible for sales teams to track their prospect universe on a daily basis and identify any opportunities for selling at the right time. An AI-powered tool like Clodura.AI can enable sales teams to get real-time updates on their prospect universe so that they act upon the potential opportunities before their competitors do. To gain such real-time & actionable sales intelligence, teams need to analyze a plethora of buying signals which are a herculean task and not feasible to do without AI.

It is also reported that businesses that leverage predictive analytics generate higher customer lifetime value because they have all the requisite information required to satisfy customer expectations. For example, with predictive intelligence, you can forecast the needs and expectations of your customers – which can help you craft a convincing sales pitch, centered around a customer’s immediate requirement – which is bound to increase engagement and, consequently, your conversion rate.

Another way you can use AI to build your business as a B2B brand is through social listening. Yes, social media, which is often given low priority by many B2B brands, is not only a great communication channel and platform for raising brand awareness but also the best place to track what your competition is doing and understand what your audience is looking for. Of course, B2B companies are not mentioned in social media as often as customers may mention B2C brands – however, that does not mean you don’t want to know what people are talking about you.

By investing in a social listening tool, you can keep ‘open ears’ on social media to find any relevant mentions or comments. You may also employ sentiment analysis (an AI-based concept) to categorize all the social media communications about your company according to pre-decided tags and gauge the expectations of your audience.

B2B social listening also makes it easier to keep a tab on your competition. For example, you can monitor industry-specific hashtags to understand what kind of content your competitors are generating and what is clicking with the target audience.

2. Eliminate Repetitive and Monotonous Tasks

Successful businesses are also highly-efficient – and invest in tools and technologies that improve the efficiency of their staff by eliminating monotonous or repetitive tasks. For example, in many B2B organizations, salespersons spend an enormous amount of time doing monotonous tasks like making cold calls or typing emails to prospects. However, AI-based sales tools can automate your marketing campaign efficiency and also qualify your leads to save time for your staff. 

McKinsey Global Institute points out that 45% of regular tasks in any industry may be automated using currently demonstrated technologies. For example, it is possible to set up automated email campaigns using an AI-based sales platform or direct-dial prospects without needing to type or copy phone numbers. One widely quoted example of automation is JP Morgan’s machine learning-based system – COIN – that can complete around 360,000 hours of finance work in just a few seconds and also eliminates human error in reviewing high-level financial documents.

Another example, more relevant to the use of artificial intelligence in sales and marketing in B2B, is the deployment of chatbots for customer service, lead generation, and lead qualification. According to research, chatbots will help businesses across the world save over $8 billion annually by 2022 – by taking over repetitive tasks and reducing the need for hiring large teams in customer-facing positions. The result – reduced costs and lighter workload for employees – leading to a happier and more efficient workforce. 

It is widely believed that chatbots can answer a large percentage of straightforward and repetitive queries and can be trained to qualify leads by using a set of pre-determined questions such as “Are you a business owner?” or “Are you searching for a specific solution?” or “Would you like to know more about [X]?

Based on the answers to the above questions, your AI-based sales platform can categorize the prospects into hot and cold, while also detailing their specific requirements as brought out in the above conversation, making it possible for your salespersons to focus on hot leads with relevant information to capture their interest.

For customer service, chatbots not only enable instant support (24/7) but also filter out support tickets, passing only complicated queries to your sales team, leading to better utilization of time.

3. Sales Automation

Salespersons often rely on simple market research or prospecting methods like BANT or GPCT  to gather what a customer may need and accordingly modify their sales pitch. While this requires a great deal of effort, unfortunately, such an approach is quite experimental, and often not based on real-time data or hard facts – which is an area in which AI has proven to be extremely useful. 

Prescriptive analytics – the third stage of data analytics where AI-based algorithms are used to crunch data and prescribe the best course of action to achieve pre-decided goals – can be used to chart clear call strategies by defining which prospects to call. These suggestions are not random but based on the analysis of thousands of data points, including industry, budget, revenue, and location. Such data analysis can also indicate the type of product or service required by a prospect and the pricing model, which is based on a review of past conversations. Marketers can use prescriptive analytics to determine the most effective communication strategy or offer, based on the position of the customer in the sales funnel and the likelihood to purchase.

Besides sales automation, such technology can also be used for predictive maintenance and seamless after-sales experience. Rolls Royce, the acclaimed engine manufacturer, uses an AI-based platform to continually collect performance data so that it can inform its clients of any upcoming issues and also manage an automated maintenance schedule. 

Cutting a long story short, AI and machine learning can be used to handle time-consuming, critical, yet straightforward tasks like collecting market information or sending out marketing emails. Automation, even at such a basic level, frees up your sales staff, allowing them to concentrate more on their core job – that is, interacting with potential and existing customers.

4. Personalized Communication

We have heard a lot about personalization and customer experience in B2C – but things are not very different in the B2B world. Yes, customer expectations have changed across the board, and businesses in both B2B and B2C must evolve or be left behind by competitors, ready to adopt new technologies, and exceed customer expectations.

As we mentioned at the beginning of this article, 75 percent of all business buyers expect companies to anticipate what they need and make relevant suggestions even before they initiate contact. 

Evidently, personalization is an essential aspect of B2B lead generation. It refers to understanding what your customers require and offering it to them via tailored interactions. To achieve this, you can deploy AI-based sales software to get real-time sales intelligence on your target market.

According to a study, 98% of marketers experienced better customer relationships owing to personalization. 90% of the respondents in the survey also reported a “measurable lift in business results” due to personalization.

In case you are wondering how you can use AI for personalization, here’s a simple example that you may have come across often – Netflix’s recommendation engine. Data indicates that users, on average, spends up to 90 seconds to choose what they want to watch, before giving up on the process. However, Netflix overcomes this challenge by using an AI-enabled recommendation engine that uses both historical and real-time data to send personalized recommendations to users – saving the company billions of dollars through increased customer retention. 

While this example is not specific to B2B, it explains how AI can be used to introduce a high-degree of personalization to achieve business results. For B2B brands, investing in an AI-based sales platform allows them to use millions of data points, like on-site interactions, previous communications, and purchase history to build specific customer personas. By using these personas, you can match customers to the products or services they are most likely to buy, leading to highly relevant and personalized conversations.

5. Analysis of Data-Based Business Decisions

Besides introducing personalization in sales that we shared above, another area in which AI is handy for sales is data analysis. With digitization, most B2B brands are sitting on heaps of data, yet, they aren’t able to unlock the full potential of this data owing to manual data processing, which is labor-intensive, time-consuming, and also prone to human error.

AI-based sales software can crunch massive amounts of data to calculate nearly accurate sales forecasts, predict customer churn ratio, suggest relevant pricing models, and also create cross-selling opportunities that can be acted upon by sales teams for better results.

Besides collecting and analyzing data, AI-based algorithms learn from everyday interactions and historical patterns to generate actionable insights that can empower your sales team to make the right conversations with the right prospects.

6. Increased Lead Quality

Customers are the heartbeat of any business – unfortunately, lead generation is often one of the biggest challenges cited by B2B companies. That being said, we all know that every lead is not equal, and generating quality leads is much more challenging than ensuring a steady stream of visitors to your landing pages. AI can help your sales teams grow the number of high-quality leads through intelligent data analysis, which allows for easier identification of productive accounts.

Modern AI-based tools can scour copious amounts of data for potential customers using multiple set-points and bring actionable insights to your desk, enabling you to focus on what is vital for your business and save immense time for your sales and marketing teams. 

B2B brands can also use AI to identify and acquire prospects that have identical attributes when compared to top-paying customers. Here, you can use your best customer accounts as identification models so that your sales platform can uncover prospects with similar characteristics in other industries, leading to more business and new revenue streams.

As we previously mentioned, it is also possible to use AI-enabled chatbots for lead prospecting and set-up automated email campaigns for lead nurturing. An AI-based sales platform like Clodura can give you access to comprehensive data about millions of companies, direct dials, and real-time data alerts to identify and capture low-hanging fruits in the market. Integrated direct dialer, automated email sequences, verified sales pitches, etc., are some other features that improve the efficiency of your sales team while also improving your conversions through highly tailored and effective communications. 

7. Better Upselling & Cross-selling

Salespeople very often make the mistake of upselling and cross-selling to all their clients – which leads to a lot of wasted time and effort. Instead, it is much wiser to invest in an AI-based sales platform that will help you identify clients who are most likely to buy and when. Sales platforms powered by AI can collect data from multiple sources and apply mathematical formulae to determine which clients are most likely to sign up for more or better solutions – and when. This not only saves precious time but helps you identify low hanging fruits – or obvious opportunities – and convert them to your advantage.

Conclusion

The age of artificial intelligence is upon us. Today, we are increasingly relying on machines to augment human decision-making capacity for better business decisions. And, just like every other aspect of your business, AI has enormous implications for sales and marketing, such as better lead quality, higher client engagement, and improved CX. With AI, your salespersons can make informed decisions, and also get information about data points that will help them personalize conversations for clients to improve the conversion rate. 

If you wish to know how AI can transform your B2B business, get in touch with an expert to learn more about how AI-based sales tools and what they can do for you.

REVENUE ENGINE