Many businesses are looking to the promises of AI to aid their lead generation efforts. By leveraging AI, businesses hope to do everything from automating content and communication to predicting and planning pipeline through better use of available data.
For sales teams, AI promises the ability to focus more on connecting personally with customers by off-loading mundane tasks like data entry. This can help sales teams spend more time nurturing relationships and closing deals instead of constantly battling repetitive tasks.
Marketing automation leaders are leaning into this new promise by integrating AI helpers into their platforms. For example:
- Salesforce’s AI tool called Einstein can analyze customer data to predict buying behaviors and recommend which leads could be the most promising ones. It’s algorithm recommends leads based on its ability to predict the likelihood of a lead converting into a sale
- Hubspot’s AI-based lead scoring tool ranks leads based on their potential value to the business. This is calculated from historical data in the system and user interactions
- Drift’s chatbots engage with website visitors in real time. Drift touts its ability to engage customers in conversation outside regular business hours and to analyze interactions and improve follow up by asking the right questions
- IBM’s Watson Personality Insights touts the ability to engage with customers by analyzing and adjusting to the communication styles and personality traits of the person chatting with them.
The integration of Artificial Intelligence (AI) in lead generation will undoubtedly transform how businesses identify and engage with potential customers. Unlike traditional methods, AI algorithms can analyze vast datasets, predict buying behaviors, and automate communication in near-real-time, offering unprecedented efficiency and accuracy.
[AI is] supercharging sales performance by unlocking AI-powered capabilities that were previously impossible like: predicting the likelihood that leads will close, identifying new in-market leads, and automatically scoring prospects based on intent.”
Neil Sahota
Human sales reps, in turn, can become more efficient and effective, utilizing AI as a sales co-pilot, analyzing interactions to identify buying signals, and looking for clues in buyer behavior to optimize sales motions. For example:
- Identifying keywords used by the salesperson that pique more interest and cause the prospect to delve deeper and ask questions.
- Test subject lines and predict likelihood of a response based on historical data from other campaigns.
- Summarize meetings and notes, email the salient points to all participants, and recommend next steps based on what was discussed in the prior meeting.
- Proactively prompt follow-ups based on based on deal history.
- Analyze third party data and recommend potential new leads.
- Track competitors and provide alerts to your inbox about your competitive activity, based on their online footprint.
- Coach sales teams with simulated tasks and prompts to make sure reps are up-to-date and on message
“AI is helping salespeople everywhere crush their quotas. It’s doing that in two big ways.
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