Generative artificial intelligence (AI)—boasting incredible efficiency gains, hyperspeed data analysis, and personalized content generation capabilities at scale—is making its mark on the B2B sales scene. Recent McKinsey research suggests that a fifth of current sales team functions could be automated, with 90% of sales leaders expecting to use generative AI solutions “often” over the next two years.
On the front lines, many sales teams find themselves bogged down with time-consuming, non-revenue-generating tasks that are undermining their ability to close deals. In fact, a 2022 survey found that 74% of respondents spend much of their day on activities that don’t contribute to selling—with 41% of the workday spent on non-revenue-generating activities, such as internal meetings, scheduling calls, and responding to internal emails or Slack messages.
Notably, 81% of sales professionals surveyed estimated they could meet their quotas and generate 38% more revenue with a reduced admin burden. With that estimation in mind, it’s no surprise that the McKinsey data also revealed that the most effective companies are deploying advanced sales tech; organizations that invest in AI are seeing a revenue uplift of 3%-15% and a sales ROI uplift of 10%-20%.
Driving efficiency through the sales cycle
With these benefits in mind, many organizations are adopting generative AI tools in their sales workflow to manage everything from predictive lead generation, transcribing and summarizing sales calls, and personalizing follow-up emails to streamlining the proposal process, optimizing revenue forecasting, and producing customized sales enablement content.
Regardless of how sales teams are using AI-powered technology, the overarching goal is to increase operational efficiency and productivity. With an average of 27 touchpoints in the B2B buying process—often spanning many weeks, months, or even years—companies are aiming to accelerate the deal cycle, moving prospects efficiently through the sales process to optimize revenue opportunities.
With generative AI technology in the sales tech stack (e.g., ChatGPT, generative AI proposal software, Microsoft Copilot), companies can eliminate labor-intensive, low-value tasks from the sales workflow, helping increase productivity to scale growth (without incurring higher labor costs), while freeing up sales reps’ time to focus on revenue-generating activities.
Transforming the proposal workflow to increase deal velocity
While automating the time-consuming process of generating leads, composing cold emails, or summarizing sales calls is a logical labor-saving use for AI tools, transforming the proposal process with generative AI can be a missed opportunity for speeding up the lengthy B2B sales cycle and converting more opportunities into revenue.
Generative AI technology has the ability to analyze vast volumes of data (text, numbers, images, video), problem-solve, and generate content at scale—at a rate that far exceeds human capacity. How do these capabilities translate to an organization’s proposal process and deal cycle?
In simple terms, AI-powered proposal software speeds up and simplifies the proposal process by turbocharging data analysis and automating content generation, management, and storage to help sales teams close more deals, faster. In fact, a recent benchmark survey found that 60% of respondents said proposal management software positively increased their deal velocity.
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The content connection
Creating content (e.g., proposals, pitch decks, sales enablement assets) that resonates with customers is crucial for persuading buyers and transitioning them efficiently to the next stage of the sales journey. But it can be heavy burden for proposal and sales teams tasked with creating high volumes of documents.
Thankfully, when it comes to producing content, generative AI does the heavy lifting, eliminating the time-consuming process of drafting content from scratch. AI-powered proposal software can collate data from a variety of sources—public domain, in-house content (e.g., past customer proposals, marketing collateral, predefined answers), expert content housed in a separate database—find the relevant data points, ensure data security and privacy, and generate original, personalized content based on the analysis and research.
At this point, proposal and sales teams can further customize the draft documents and tailor the tone and voice to the needs of the audience (e.g., prospects vs. existing customers) to create strategic content that drives conversion rates and escalates deal velocity. Plus, generative AI proposal tools can repurpose existing content into different formats (e.g., from product demo to sales presentation) or different use cases for multiple audiences, simplifying the content creation process to increase productivity.
With a more efficient and impactful proposal workflow, team members have more time to focus on high-value strategic activities. In other words, by getting rid of the monotonous, repetitive tasks in the proposal process—researching content, playing email tag with SMEs, manually categorizing content—organizations can empower their business development teams to spend more time on the value-add, customer-facing activities that are critical for strengthening customer relationships and closing deals.
It’s important to note that while familiar AI tools like ChatGPT or Microsoft Copilot are excellent resources for general research and content creation, unlike generative AI proposal tools, they aren’t designed with the specialized content and security needs of proposal teams in mind. With access to either too much or too little content and lacking the ability to seamlessly target domain-specific content sources inside of an organization or ensure data privacy, generalized AI tools are best used outside of the proposal workflow.
Looking ahead
Down the road, embedding generative AI into businesses processes and applications will become standard practice as companies prioritize automated workflows to increase productivity and free up employees’ time to focus on value-added activities. Today, sales leaders can take advantage of an AI-driven proposal workflow to push greater volumes of winning proposals out the door—at a faster rate and with significantly less effort—to accelerate the deal cycle drive boost top-line performance.
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