The Top Sales Trends and Technologies for 2024: Tech Advances Let Sales Teams Thrive in a Difficult Economy

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The economy has been extremely volatile for the past few years. Fears about inflation, which drives up costs, have been rampant. As a result, businesses are leery about the future and are cutting spending, which is not good news for companies trying to sell their products and services to those businesses. Consequently, companies have been hounding their sales software suppliers for tools that drive greater efficiency and increase productivity. Suppliers see generative artificial intelligence, social media, and more seamless omnichannel experiences as the means to achieve that goal.

Businesses have slashed some of their sales team budgets, while at the same time expecting sales teams to bring in more revenue, work more efficiently, and capitalize on every opportunity passed to them by marketing teams that are also seeing their budgets cut. It’s a difficult balancing act as sales departments need to do more with less.

In response, the sales cycle is changing. Deals are taking longer, and customers are more thorough in their evaluations. “Sales software buying priorities shifted toward value and away from vanity,” says Prashanth Krishnaswami, head of market strategy for customer experience (CX) products at Zoho. “More discipline has been introduced, and sales are only approved if they somehow provide clear value to the company.”

This is forcing sales teams to not only work harder but also to work smarter. Right now, plenty of waste is evident. Sales representatives often spend only about a quarter of their time actually selling; the rest is dedicated to administrative tasks, which often are mundane and repetitive.

Generative AI has the potential to bring about significant changes. “We are at the crux of the biggest CX disruption with the AI revolution, especially with the latest developments in generative AI,” noted Jon Aniano, senior vice president of product at Zendesk.

Why? The technology promises to deliver a quantum leap in capabilities. Today’s generative AI models work with much larger volumes of information (hundreds of billions of words) and larger data models (hundreds of billions of parameters) than previous AI systems. They also possess impressive and unprecedented power. As evidence, they can perform very sophisticated functions, like passing the bar exam for lawyers and the advanced sommelier exam for wine tasters.


Corporations can apply such power throughout the sales cycle to streamline their business processes. So it is understandable that salespeople are trying to leverage generative AI for automating manual, time-consuming tasks.

For instance, companies place a premium on sales and marketing content, which drives customer interest and engagement. “Companies now find themselves in a short-term war for engagement,” Krishnaswami says.

Generative AI can dramatically change the content creation process, with the ability to create up to 80 percent of all content that is needed, dramatically cutting down on content generation time.

The tools can be used for many types of sales collateral, including web pages, customer emails, blog posts, e-books, sales brochures, white papers, and more. Generative AI solutions typically come with templates with steps following a logical progression.

In addition, AI speeds up the handling and approval of routine documents. Sales contracts are automatically routed to the proper people and signed electronically. Sales team members no longer have to chase down individuals to complete that work.

Personal sales assistants are emerging and taking on a growing number of tasks as well. They automatically record and transcribe sales calls. “A salesbot can digest a 10,000-word report and personalize the output for specific members of the sales team,” explains Abe Smith, chief of global field operations at Freshworks.


Sales has always been a numbers-driven function, governed by leads, quotas, targets, projections, percentages, probabilities, and more. Nowadays, organizations collect more data points about clients than ever before. They track each customer’s every move from initial website visit until the final purchase and beyond.

However, the data by itself is of no use. Sales personnel need to correlate it and put it into context with other pieces of information. The process clarifies businesses’ challenges and how well they’re meeting their objectives. With such insights, firms understand which steps need to be taken to improve overall sales strategies and individual rep and team performance.

As a result, companies are trying to leverage AI in a myriad of ways, including the following:

  • Customer segmentation based on criteria such as age, gender, location, purchase history, preferences, and behavior.
  • Improving forecasting, predicting sales trends, and anticipating customer demand. Sales teams are getting a fuller picture of the steps clients typically take before making purchases, enabling better inventory management and sales planning.
  • Filling the sales pipeline with predictive analytics that scores leads based on their likelihood to convert, helping sales teams understand trends, recognize opportunities, prioritize their efforts, and maximize the return on their investments.
  • Personalizing product recommendations, with businesses trying to interact more individually and less generically when engaging with potential clients. The tailored approach can improve engagement rates, fostering stronger relationships and potentially increasing conversion rates, according to Gartner.
  • Sentiment analysis, letting companies know customers’ emotions and opinions by how they express themselves in words and text. They use that knowledge to interact with them in more mutually beneficial ways.

With the new tools, salespeople become more efficient. They have more time to build relationships with customers and close more deals since they spend less time on mundane tasks.

And so far, the efforts have been paying off, according to HubSpot. The company’s own research found the following:

  • 83 percent of salespeople say that, as a whole, AI is effective in helping them meet their goals.
  • 81 percent of salespeople say AI helps them save time on manual tasks and be more efficient in their roles.
  • 71 percent of salespeople think AI makes prospecting more effective.
  • Salespeople save more than two hours a day using artificial intelligence.

But generative AI poses its share of challenges and risks as well. While helpful, AI is not a panacea. “Inflated expectations for genAI analytics make it difficult for chief sales officers (CSOs) to build a realistic vision and road map,” Gartner concludes in a recent report.

Companies need to start with the fact that AI is different than traditional applications. While other technologies have very narrow vertical focuses, generative AI is horizontal and, like e-commerce, can be integrated into any type of system or interaction.

But the tools cannot be dropped in and then expected to automatically start working. A lot of upfront work is required before companies can reap any rewards. The deployment process raises both technical and personnel issues. “Enterprises can undergo a steep learning curve in understanding how to leverage AI throughout their organization,” says Angel Vossough, cofounder and CEO of BetterAI, an AI startup that offers consulting, process automation, integration, and data management services.

Further complicating matters is the fact that AI needs lots of data before it can be deployed. Such solutions collect information from other sources and build data models that correlate information or mimic different processes, such as a chatbot responding to a website inquiry. Companies must input a lot of examples of the types of functions that they want to perform before the system can replicate an action. The process is time-consuming and imperfect. Many trial runs fail, and data models have to constantly be fine-tuned.

Compounding the issue is the reality that every organization is unique. Therefore, each company has to connect the AI to its business applications. Sales and customer information is scattered in many systems, including marketing automation, CRM, financial systems, and e-commerce platforms.

After collecting the data, AI solutions build the data models, and often, they automate routine functions. Consequently, they have to determine how to change the way work is distributed throughout an organization. Each organization has already well-known steps in place, and they will have to be altered. Determining how and how much improvement will be realized usually requires time.

In addition, employees often do not react well to change. Many will feel threatened that AI is somehow going to take their jobs. To combat the resistance, management must embrace change and create a culture that encourages innovation and experimentation. They also need to communicate with employees and ensure that AI’s role is to supplement and not replace human interactions.

Furthermore, while the solutions have tremendous potential, they are only able to take on relatively simple tasks currently. So companies need to blend the old with the new. “AI provides more and better engagements with customers, but such interactions still require a human touch,” Vossough says.


Another significant change involves breaking down traditional departmental/application barriers. In the past, each group operated autonomously. Today, more synergy is needed among applications. Companies usually start with melding their marketing and sales solutions. The change creates a more consistent voice and brand image when talking with prospects and clients.

The change also meshes with how sales have been shifting. In the past, the focus was on bringing in new customers. Now, firms want to upsell to current clients. As evidence, 26 percent of sales professionals expect that servicing current customers will take priority over finding new ones, according to HubSpot’s data. This change makes sense, as existing customers make up 72 percent of company revenue on average, with new customers accounting for the remaining 28 percent.

One ripple effect is companies have been trying to use genAI to improve customer service. “One of the most impactful applications is the combination of generative AI-based resolutions with conversational flows,” said Zendesk’s Aniano. “For example, having an agent copilot helps a human agent get to a resolution faster. At Zendesk, we see up to a 20 percent decrease in average handle time and a 15 percent decrease in first response time from teams embracing generative AI this way. In turn, we use those learnings, data, and human feedback to teach our high-performing AI agents, which can automate up to 90 percent of service inquiry volumes.”


Rarely do companies make a sale at first contact with a prospect. In reality, it is a process that requires multiple steps and multiple touchpoints. A third of sales reps say they average two to four interactions with prospects during the sales process, and 26 percent say it takes five to seven interactions, according to HubSpot.

As a result, companies need to provide customers with multiple avenues because they never know how the person will connect with them. As evidence, 73 percent of shoppers engage with multiple channels throughout their shopping experiences, according to MarketSplash.

However, homogenizing such experiences can be difficult. It requires the following:

  • Consistent branding, messaging, and customer experience across all channels, including websites, social media, mobile apps, and physical stores.
  • Inventory management across online and offline channels, so customers understand real-time stock availability regardless of where they shop.
  • Integrating sales capabilities directly into social media platforms, allowing customers to make purchases without leaving the app.
  • Adapting to customer preferences, recognizing that every client is unique and likes to interact in different ways. Companies need to understand what they want and adjust.

In sum, omnichannel sales means creating a seamless customer experience, but time will be needed for companies to put all of the pieces in place.

Sales departments need to ride out economic ebbs and flows. Currently, the picture is daunting, with budgets being trimmed but revenue growth still demanded. To balance the two conflicting drivers, sales teams are trying to streamline workflows with generative AI, break down traditional application and organizational barriers, and increase the number of channels used to engage with customers. The work is hard, complex, and ongoing, but necessary. Ideally, the changes enable companies to survive during the current difficult economic times and thrive once the economy begins to improve. 

Paul Korzeniowski is a freelance writer who specializes in technology. He has been covering CRM issues for more than two decades, is based in Sudbury, Mass., and can be reached at paulkorzen@aol.com or on Twitter at #PaulKorzeniowski.

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