Common Uses of AI in Sales


We’re going to discuss some of the different ways that you can leverage AI in sales

for improving your processes and workflows. I’m Kristin Keher, founder of Data Moves Me and a data scientist that has been building models since 2010 with experience in the utilities, healthcare and predominantly e-commerce. 

Now let’s take a look at the different uses of AI in sales. AI serves as a multifaceted tool for sales professionals offering immense time-saving benefits in various aspects of the sales process. AI can be used for sales engagement and communication. These tools can assist in running effective meetings and crafting follow-up communications. The focus here is on enhancing direct customer interactions and maintaining engagement throughout the sales cycle. This includes leveraging AI sales assistance for note taking, real-time insights during calls, and generating personalized follow-up emails. Another particularly helpful area is in intelligence and research. These tools gather and analyze data about prospects, market trends and competition. This helps you in preparing for meetings by summarizing relevant information from various sources like social media, blogs and CRM data, the insights into prospects, activities and interests, aids, and creating tailored sales approaches.

The next area is in sales optimization and forecasting tools are available to assist with analyzing and prioritizing sales pipelines and forecasting future sales trends.

The ability to sift through large data sets to identify patterns and provide actionable insights for deal prioritization and engagement level analysis can drastically reduce time compared to a manual effort, and we know this is crucial for strategic planning and decision making in sales. 

The next topic is leveraging AI In cold outreach, AI can help in crafting emails and LinkedIn messages to individual prospects according to their interests. You can even use AI to brainstorm creative ideas for subject lines and cold openers, helping you to engage clients without being a professional copywriter. You’re able to refine the results you get from AI by tweaking your prompt and get more desirable results. 

AI can assist in helping you run more effective meetings. We discussed how AI can summarize essential information about a prospect by leveraging social media blog posts and CRM data so you can prepare before a meeting. AI sales assistance enhances meeting efficiency, allowing you to concentrate fully on your client during the meeting. This is done through AI assistance in note taking, data capture for CRM, realtime guidance and summaries following the meeting to share with those who might not have been able to attend. 

This brings us to follow ups. You can create follow up emails by analyzing conversation contexts, eliminating the hassle of drafting personalized emails from scratch. Automated task creation can help you with how to follow up after a meeting. This has huge benefits in helping with timely and relevant communication. Enhancing customer relationship management pipeline review can also be aided with ai. AI can sift through large data sets and quickly find trends and insights, prioritize your open deals, analyze engagement levels or historical data, and optimize your forecasting accordingly. Prospecting before an event, identify key sponsors for outreach and gather information about speakers. Assist in optimizing your schedule for the conference. By analyzing the agenda and sessions it can recommend the most relevant presentations and workshops to attend. 

But where to start? Try the sales productivity chart. This methodology helps you conduct a productivity audit to better understand the time and impact tied to each of your recurring tasks by ranking time and impact for each task, you can then find top contenders for automation, which would be the tasks you should prioritize first, when searching for an AI solution.

Step one, list out your tasks from email crafting and call prepping to the more mundane tasks like updating the CRM.

Step two: write in the average time spent on each task per week. 

Step three: rank these tasks by impact on deals, which ones nudge the buyer closer to a closed win. 

Step four: create a graph with two axes, time and impact. 

Step five: plot all of these activities on the graph and draw a horizontal red line to represent the benchmark for automation activities. Below this line are prime candidates for automation. While those above require a human touch, now that you know which tasks to prioritize to maximize productivity, you can go ahead and start searching for the AI tools that will help you save time and maximize impact.

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