There are so many ways you can use AI in sales these days, it’s hard to know where to start, especially if you’re a newbie to all of the excitement. So, this article will focus on something almost everyone in the business world uses, knows, and understands how It can be used right now, on every business persons favorite, LinkedIn.

Using AI with LinkedIn selling can enhance your sales and marketing efforts by automating tasks, providing valuable insights, and streamlining processes. As noted in previous articles, to maximize AI’s usefulness it requires a combination of Blended AI* and Augmented AI** to maximize its impact.

10 ways to use Augmented & Blended AI with LinkedIn

1.    Personalized messaging: AI-powered tools can analyze data from LinkedIn profiles and interactions to create personalized messages that resonate with individual prospects, increasing engagement and response rates.

2.    Relationship insights: AI can analyze communication patterns and interactions with prospects to provide valuable relationship insights, such as the best times to reach out or the most effective ways to engage with specific individuals.

3.    Lead generation and prospecting: AI algorithms can help identify and prioritize potential leads based on specific criteria identified in your sales process, such as job titles, industries, or geographic locations, making your prospecting efforts more efficient.

4.    Sales forecasting: AI-driven analytics can analyze historical data, sales patterns, and market trends to provide more accurate sales forecasts, helping you plan and strategize your selling efforts better.

5.    Competitor analysis: AI can gather data on competitors’ activities and strategies on LinkedIn, providing valuable insights to refine your own selling approach and stand out in the market.

6.    Performance tracking and analytics: AI-driven analytics can measure the effectiveness of your LinkedIn selling efforts, tracking key performance indicators (KPIs) like response rates, conversion rates, and engagement metrics. This data allows you to continuously improve your strategies.

7.    Content recommendations: AI can analyze user behavior and preferences to suggest relevant content, such as articles, blog posts, or videos, that align with your prospects’ interests and pain points.

8.    Social listening and sentiment analysis: AI tools can monitor conversations and discussions on LinkedIn to gauge the sentiment around your brand and industry. This information can help you tailor your messaging and identify potential opportunities or challenges.

9.    Automated follow-ups: AI-powered sales automation tools can handle routine follow-up tasks, sending timely messages and reminders to prospects, helping to maintain engagement and nurture leads.

10.Chatbots for instant responses: Implement AI-driven chatbots on your LinkedIn profile to provide instant responses to common questions, qualify leads, and engage with prospects at any time, improving customer experience and response times.

There is no single AI tool (yet) that can accomplish all ten use cases noted on my list and it isn’t necessarily in order of usefulness. Instead, each seller must ascertain what is most important in their sales efforts and then use Blended AI to attack their sales patch in a coordinated and concise manner. Best practices are to pick a vendor that know what is actually working to advise when to use it and when not to, because:

The key isn’t using AI.

The key is using the right AI with your already successful, winning Sales Process and applying the right form of AI at the right stage in the sales process. That is the Winning Ticket!!!

Bottom line

By leveraging Augmented and Blended AI in your LinkedIn selling efforts, you can streamline working sales processes, deliver a significantly more personalized experience for your target audience, and make data-driven decisions (not just gut feelings), ultimately increasing each seller’s success rate by connecting with the best prospects and converting them into valuable customers.

*Blended Artificial Intelligence Is the amalgamation of different artificial intelligence techniques or approaches to achieve more robust and effective solutions. It involves integrating multiple AI models, algorithms, and / or technologies to leverage their respective strengths and compensate for their weaknesses. See Wikipedia:

** Augmented artificial intelligence is a design pattern for a human-centered partnership model of people and artificial intelligence (AI) working together to enhance cognitive performance, including learning, decision making and new experiences.