Machine Learning – Prospecting is no longer approached as a purely transactional marketing process. Initially, consumers were primarily concerned with receiving a high-quality product with impeccable service, and nothing more. The market was meant to feed the consumer’s need for instant gratification. Now, the needs of consumers are evolving, and they want to take it a step further.
With the emergence of social media and the investment in artificial intelligence (AI) and machine learning (ML), businesses have the ability to communicate with their consumers individually. This has generated an overwhelming number of opportunities for them to nurture their consumers’ journey in ways that speak to their personal interests and needs. The question is: how can we predict what consumers will need? Let’s explore how leveraging AI and ML can enable you to prospect, personalize your outreach, and ethically engage with donors, diners, travelers and so many more.
Technology has consistently been at the center of our economic growth, where radical change and business value are created and re-created. In 2017, over $15 billion was invested in startups focused on AI. By the end of 2018, that amount was predicted to reach over $58 billion by 2021.
Now that there’s greater investment in AI and ML, not only do these technologies enable us to gain a deeper understanding of our consumers’ preferences, but they also supply us with insights that drive leads to us and the individual markets we’re breaking into. The primary way we’re able to deepen our consumer knowledge through these technologies is by engaging in predictive prospecting.
Predictive prospecting allows you to project who your next best clients may be based on commonalities among your existing clients. When you’re identifying potential consumers, the creation and identification of customer personas (based on bundles of your existing clients’ overlapping interests) will lay the foundation for your subsequent sales efforts.
This article originally appeared on forbes.com To read the full article, click here.
Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously. To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:
- Advanced predictive anomaly detection, Bayesian Classification and other machine learning algorithms
- Raw information handling and analytics speed
- End-to-end business transaction tracking that spans technologies, tiers, and organizations
- Intuitive, easy-to-use data visualizations and dashboards
If you would like to learn more, click here.