AI’s Potential to Help B2B Companies with Revenue Goals

Whether you’re in marketing or sales –– or the business world at large –– ChatGPT has taken over your LinkedIn feeds, Slack groups, and many other conversations. ChatGPT helped AI hit an inflection point with the rise of generative AI, but this shiny object just scratches the surface of what is available today for B2B companies and their sales and marketing teams. 

As more and more AI-powered tools enter the martech landscape, opportunities abound to help B2B companies better achieve their revenue targets. 

However, another trend has kicked off our year.

Many organizations are starting 2023 with fewer resources –– be it because of budget cuts, attrition, or increased responsibilities for team members. 

The good news? Artificial intelligence has the potential to help B2B companies achieve their revenue goals in several ways. And there are tools to help you for virtually every use case. This landscape from Sequoia Capital’s Sonya Huang dates back to October 2022, and since then, the space has exploded:

As promised: here is our @sequoia Gen AI market map V2! Very thankful for the hundreds of folks who wrote in additions and edits.AI people are amazing 🥹 pic.twitter.com/dXyHR9dSvR

— Sonya Huang 🐥 (@sonyatweetybird) October 24, 2022

Consider these use cases:

Automating repetitive tasks

AI-powered automation can take over repetitive tasks such as data entry, crafting emails, appointment scheduling, and customer service inquiries, freeing up employees to focus on more high-value activities. AI tools like SmartWriter.ai and Lavender can be connected to your CRM or LinkedIn to help you craft more personalized emails for your outreach. 

There are so many generative AI tools available, and even technologies such as Grammarly are available to help sales teams in that first critical touch with prospects. 

Exceed.ai can help schedule meetings with prospects identified as qualified—through a multitude of channels. 

Improving customer engagement

AI can be used to personalize interactions with customers, for example, by recommending products or services that align with their interests or needs. This can lead to increased customer satisfaction and loyalty, resulting in repeat business.

Intelligent technologies such as Drift can learn from simple chat conversations and sales process automations, which can help create robust CRM records on customers. This could include pages visited, questions asked, and more. Marketing and sales teams can better align by having visible, actionable data received through conversational AI. 

AI-powered email technologies such as rasa.io and Faveeo are able to customize email sends based not only on known and implied interests from form fills and purchase history, but can also automate subsequent sends based on historical email opens and clicks–without additional list building, data remediation, and workflow building. 

Tools like Uniphore can record and analyze sales calls to determine where a sales representative resonated with a customer or prospect, or conversely, where the deal was lost. Great sales teams will use technologies such as this to continually work to improve their pitch and delivery, and also better understand what customers need.

Conversica has an automated AI sales assistant that conducts conversations with leads, further qualifying them before they talk to a rep.

Identifying new revenue opportunities

AI-powered analytics can be used to identify new revenue opportunities by analyzing patterns in customer behavior and identifying trends in sales data. This can help companies make more informed decisions about which products or services to focus on.

Crayon is a competitive intelligence platform that can act in real time to share data immediately with sales teams, with the ability to detect both anomalies as well as big opportunities.

Optimizing pricing

AI can be used to analyze data on customer behavior, costs, and competitors to help companies optimize their pricing strategies. This can lead to increased revenue without sacrificing profitability.

Tools like Remesh can crowdsource and consolidate customer feedback on product, price, and more.

Enhancing lead generation and sales forecasting

AI models can help companies to identify the best leads and forecast the likelihood of a lead converting into a customer. By doing so, the sales team can prioritize their efforts, focus on high-probability leads and make better revenue predictions.

Data modeling tools such as Squark can predict churn risk and lifetime value with existing customer data. By pinpointing signals more intelligently, sales can be focused on the right customer at the right time. 

Technologies such as Rev can help build your ICP by integrating current processes and systems with external company and industry data to help forecast and prioritize. 

The common thread among all of these benefits is that these tools relieve some of the time sales teams spend drowning in data so they can focus on the actionable information discovered through the data. 

Making happier humans in the loop

We often hear the worries of AI taking our jobs, but without human oversight in these AI outputs, your customers and prospects will not be easily fooled.

An AI tool can scale faster and help us generate emails, catchy subject lines, and more. But even the best-written AI-generated emails still need human oversight to ensure the LinkedIn data it pulled in, or the CRM notes you have are still up-to-date. Even the best data analysis needs a human to look it over to check for inaccuracies or biases in the training set. 

Most importantly, the right AI technology allows more time for us to be more human. It lets us engage with our customers and prospects, make stronger connections, and invest time in creating the right product or service for our audience. 

At the Marketing AI Institute, we talk at length about the future being Marketer + Machine. AI is here, and we as sales teams, marketers, and business leaders can embrace AI and learn how it can augment our work, or we can ignore it and get passed up by competitors. 

What steps can you take today? 

• Think about the tasks you do each day, week, or month. Are they repetitive? Are they data-driven? Are they making a prediction? Document this so you can see some places where AI can help you immediately. 
• Estimate the hours you spend on the tasks you listed above. What’s the biggest opportunity for you to save time? What task has the biggest potential to impact revenue if it could be scaled faster? 
• Visit the Marketing AI Institute website for resources. We have a free Intro to AI class, and then things scale up to a Piloting AI course series, an in-person event (MAICON), a book, our AI Academy for Marketers, and more. There is so much FREE content on the site to help get started. 

It’s important we remember that AI is not a magic solution nor a one-size-fits-all technology. I’ve been in the marketing industry for a few decades now and I’m slowly integrating more intelligent technology into what I’m doing. It’s a slow build for me, but I’ve seen immediate returns on time and scalability in my processes and set aside time each month to reevaluate what I could be doing smarter. 

Identifying the right areas where AI can bring the most value and having a data-driven culture and infrastructure is crucial for the successful implementation of AI.