Marketing Automation Buyer's Guide

The CIO’s Role in Redefining Operational Efficiency

The CIO Role in Redefining Operational Efficiency

The CIO Role in Redefining Operational Efficiency

As part of Solutions Review’s Contributed Content Seriesa collection of contributed articles written by our enterprise tech thought leader community—Bryan Wise, the SVP and CIO at 6sense, explains what the Chief Information Officer (CIO) should be responsible for in their company’s efforts to redefine operational efficiency.

Recently, when I talk with fellow chief information officers (CIOs), the conversation almost always revolves around the same topic: how to improve go-to-market efficiency. Everyone’s being tasked with squeezing more value out of budgets, resources, and tech in order to improve efficiency across their organizations. According to Gartner, 53 percent of digital investments over the past two years have been made with the goal of driving operational excellence. 

A primary goal for many go-to-market–focused CIOs is to optimize efficiency in the entire revenue creation process. CIOs who used to be focused on the order-to-cash portion of the process are now finding themselves peeking under the hood of the earlier stages as well. Now, we’re tasked with finding efficiencies and preventing leakage at the early stages of revenue creation as well. To successfully oversee this lead-to-cash approach, CIOs need to see where inefficiencies are occurring and why. Some main areas of waste that CIOs are in a prime position to help address are: 

  • Lack of focus and prioritization for sellers 
  • Poor alignment between marketing and sales 
  • Too much time spent on non–revenue generating tasks  

Before discussing how to address these problems, let’s examine how the modern buying process has changed and how it’s slowing down conversions throughout the funnel. 

The Modern Buying Journey 

The days of buyers filling out web forms or otherwise identifying themselves to sellers are behind us. Gartner even found that more than 43 percent of B2B customers prefer to complete their entire purchase without ever interacting with a sales rep, with only 3 percent of website visitors even filling out a form. At the same time, buying teams are conducting research across the internet and leaving behind digital signals that could indicate that they’re in the market to buy what your company is selling. These signals provide valuable information about buyer behaviors, priorities, and intent.  

But without insight into these two important sources of information—anonymous activity on your own website and signals about what’s happening on the broader internet—it can be challenging for sellers and marketers to know how to prioritize their time, effort, and budget. It also makes it nearly impossible to know enough about prospective buyers to connect with them in a way that will efficiently lead them to convert into customers.  

Insights Improve Revenue Team Efficiency 

These anonymous signals come in a variety of forms: 

  • Intent data (the digital breadcrumb trail buyers leave behind when researching solutions) 
  • Technographic data (info about a company’s tech ecosystem, including current tech stack, what integrates with it, contract renewals, etc.) 
  • Psychographic data (data from annual reports, social media, etc., that highlights a buyer’s pain points) 
  • Market updates (product launches, leadership turnover, relevant hires, funding updates, acquisitions, etc) 

Combined, these signals provide the foundation sellers and marketers need to be effective in this modern buying environment. Of course, the volume of data generated by countless buying team members across the web is not useful without AI to collect, organize, analyze, and use it to suggest the next-best actions. This combination—lots of current and relevant data plus AI—gives marketers and sellers the insights they need to prioritize, focus, and stop wasting time. It allows them to remove guesswork, opinions, and biases so the revenue team is aligned on which accounts and contacts to prioritize.  

In practice, that can mean marketing focuses on warming up early-stage accounts. At the same time, sellers focus on just a few of the most likely-to-convert accounts on any given day instead of throwing darts at a static list of 500 or more accounts that may or may not be receptive to their outreach.  

Meanwhile, generative AI can handle early outreach to lower-priority accounts and manage the conversation until the time is right to pass them on to sales. And outreach across the board—from marketing, from sales, and from the AI “assistant”—all use consistent messaging that aligns with what the data shows the account is researching.  

Time = Money

Time is the most valuable resource revenue teams have. This approach makes the most of that resource by focusing on in-market, right-fit prospects and helping them provide personalized, contextualized experiences. Research shows that this approach is effective at accelerating the path to revenue. Companies employing this data+AI approach to their go-to-market processes saw on average: 

  • 2x bigger deal sizes 
  • $17k more revenue for every opportunity worked 
  • 123.6 percent less effort required to make $1M 
  • 91.3 percent faster deal velocity 
  • Less than half as many opportunities are required to get to $1M in revenue  

On the flip side, companies that weren’t using this approach had to put in an average of 6.2 more work years to reach $10M in revenue.  


As CIOs are increasingly tasked with improving go-to-market efficiency, staying at the forefront of the rapidly transforming B2B buying process is essential. Customers no longer raise their hands and identify themselves to our marketers and sellers, meaning it’s now essential to listen in to the digital whispers they leave behind as they navigate the anonymous buying journey. 

CIOs need visibility into the earlier stages of revenue creation, making sure no stone is left unturned. By harnessing the power of AI to sift through a sea of data, we can craft more focused and less wasteful strategies. This doesn’t just make marketers’ and sellers’ lives easier; it also improves customer experience. Most importantly, it leads to increased deal sizes, shorter cycle times, and a more efficient path to revenue. 

This is a pivotal moment for CIOs, where data and AI are no longer a nice-to-have in go-to-market operations but instead a necessity. It’s an exciting shift, promising a future where we can innovate to help our businesses connect with customers more efficiently and engagingly while ensuring predictable revenue generation.

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