When it comes to conducting savvy lead generation, online companies can maintain a competitive edge in the digital marketplace by making use of predictive analytics. Such tech enables one to procure hyper-targeted recommendations based on data culled from a lead’s browsing / shopping history, and other social media behavior.

Segmentation can then be done by using these insights to conduct lead scoring. Insights include shared traits between your customers, and similarly, the shared traits between leads that didn’t convert.

Dramatic advances in Lead Gen technology could revolutionize the lead generation process. All effective lead gen efforts begin with well-executed lead scoring. To avoid wasting time on unqualified leads, marketing teams need to sort their contacts in order to cull the wheat from the chaff. This is a time-consuming, laborious, and extremely imperfect process when performed by humans. That’s why it is tremendously beneficial to automate this process. Once the system has a clear idea of what factors make up the ideal lead, it can automatically score incoming leads, all without having to rely on the outdated point system.

Predictive lead scoring analyzes different data points, such as demographics and behavioral data, taken from previous leads in the database. Salient trends can be identified based on certain actions people take within the sales funnel. At the end of the day, the idea is to lure prospective clients, customers, or investors. This involves figuring out how to engage them, nurture them, and ultimately convert them.

Engineering a streamlined sales funnel entails being able to trace a customer journey across multiple touch-points. Sources from which a system may glean useful information include chat logs, CRM data, and emails. Targeting can be accomplished by discerning salient trends in online activity.

The best platforms are capable of mining massive amounts of customer data, finding hidden patterns and gleaning key insights into online activity. The idea is to comb the internet for anything with existing customer lists that can be used as an effective point of departure for first contact. The trick is to automate this laborious process, doing it faster and more thoroughly, while honing in on viable targets. They are able to develop lead profiles based on specified data points—social media habits, most visited websites, etc. Using a platform like LeadMachine.AI, a company can then harvest all relevant data and parse it.

Tracking online behavior is only the beginning. When it comes to staying ahead of the curve in lead gen, it is helpful to be aware of other useful tech solutions. Digital assistants can engage in real-time conversations with each lead; so can be used to gather necessary contact information, then assess the interest of the lead.

Interactive chatbots are capable of having natural-seeming, captivating conversations— steering online prospects through the sales funnel—from initial contact to final conversions. Using NLP (natural language processing), a well-equipped SaaS can parse these massive data-sets; and discern consumer intent detection in real-time.

NLP technology enables a virtual assistant to understand and respond to customers. The chatbot can thereby keep the conversation going by detecting customer intent, likely sentiments, and thus anticipate questions. It is thus able to provide the right information whenever needed. A smart system can then provide realtime advanced analytics to benchmark, monitor, and optimize campaigns. It is thus able to determine whether or not any given lead is likely to translate into a sale. All this is vital if one wants to boost conversion rates.

Chatbots are thus one of the prime ways to automate the lead gen process. When a website avails itself of a chatbot, it can furnish customers with vital information whenever they need it, without any human intervention. It is important to be able to conduct engaging conversations across a wide variety of channels.

During the course of a conversation, a system capable of NLP can perform a seamless handoff from bots to human agents. Any needed transition to a human is executed seamlessly; as visitors are given the option of chatting with a customer service representative in the event that the virtual assistant is unable to resolve a problem or adequately address a query.

The most sophisticated chatbots have a behavior engine, a dialog manager, and are capable of NLP. Moreover, a human chat agent can get real-time suggestions from a chatbot. With such software, you can seamlessly integrate a bot with other platforms to acquire leads through conversational interactions. Automating the lead gen process is not just about identifying qualified leads; it’s about saving both time and money.