In the digitally driven business climate, sales teams need to always have their fingers on the pulse. Sales intelligence that provides actionable insights on prospects, customers, and market trends has become mission critical. Artificial intelligence (AI) solutions are taking sales intelligence gathering to the next level with automated data aggregation, predictive analytics, and other smart functionalities. Let’s explore 5 ways how AI is advancing sales intelligence
Centralizing Data from Disparate Systems
Sales teams utilize multiple systems housing valuable intelligence – CRM, marketing automation, business databases, web analytics, social media, and more. Manually compiling info is labor-intensive. AI empowers sales tools to integrate data from these systems into a centralized hub featuring clean, updated views of accounts. Rather than toggling between platforms, salespeople gain a 360-degree snapshot to inform conversations and strategy.
Analyzing Buying Signals and Online Dialogue
Insight into how prospects really feel about a company, executive leadership, and market perceptions is difficult for human sales reps to monitor at scale. Leveraging natural language processing and machine learning algorithms, AI sales solutions process vast volumes of online dialogues – social media, review sites, forums, etc. Sentiment analysis determines whether mentions have positive, negative or neutral sentiment. This understanding of external brand perception and buying intent aids lead prioritization and outreach personalization.
Generating Ideal Customer Profiles with Lookalike Modeling
Successful sales intelligence includes prospecting the right-fit accounts with the highest conversion potential. AI looks at data from current high-value customers through firmographics, buying signals, web activity. Then they use machine learning to determine patterns predicting success. These Ideal Customer Profile (ICP) models then identify net-new prospects that mirror attributes of best customers. Sales can align targeting and messaging to accounts exhibiting similar DNA to current book of business.
Scoring Leads Based on Historic Deal Patterns
Manually evaluating every inbound lead to gauge quality and prioritize follow-up is hugely inefficient. AI solutions apply predictive analytics to model the attributes and behaviors that yielded qualified opportunities progressing to closed deals historically. As new leads come in, this intelligence scores them based on similarity to past winners – alerting sales to engage most promising leads first. Reps also gain transparency into what information gaps indicate lower readiness.
Delivering Tailored, Contextual Recommendations
Mass outreach with one-size-fits-all pitches have low relevance and conversion. AI enables coordinating hyper-personalized messaging at scale using NLP to comprehend language data and account context. Understanding buyer stage, previous interactions, role, industry etc. allows AI-guided tools to serve up consistent yet tailored plays for sales reps. These contextual recommendations aid differentiating follow-ups from competitors and boosting connect rates.
The net effect of AI sales solutions is augmenting human intelligence – not replacing it. While AI handles time-consuming tasks like data centralization, pattern recognition, predictive modeling and personalization guidance, the human touch remains vital for relationship building and complex problem solving. AI makes the intel digestion and scaling to maximize results faster so salespeople can spend more time on high-value activities.
If your sales stack isn’t currently leveraging AI, explore intelligent platforms providing an integrated command center, buying signal alerts, ideal profiling, lead prioritization, and contextual next-step recommendations. The insight upgrade unlocks efficiency gains, bigger pipelines from qualified inbound leads, and expanded market share through ICP prospecting – leading to 30%+ revenue growth.
Now is the time to investigate AI sales solutions taking your sales intelligence gathering into the future. Request a consultation to evaluate options matching your tech stack, data infrastructure and business objectives.
