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3 min read

3 Key Ways to Use A.I. for Lead Generation

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What do marketers think will be the biggest trend of 2018? According to a BrightEdge survey, artificial intelligence continues to rank high on the list, trailing closely behind consumer personalization.

But unlike other tech trends that fizzle out over the years, it’s safe to say artificial intelligence (A.I.) and machine learning aren’t a passing fad. The tech’s already worked its way into nearly all aspects of modern business, including advertising and marketing. So, it’s no surprise that advancements in A.I. could revolutionize the lead generation process.

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Artificial Intelligence for Lead Scoring

To avoid wasting time on unqualified leads, lots of marketing and sales teams rely on lead scoring to sort through their contacts. Lead scoring is a methodology used to rank the importance of individual leads based on certain actions they take within the sales funnel.

Behavorial Lead Score Chart

Most companies score leads using a point-based system where different actions are worth varying amounts of points. For instance, scheduling a product demo may be worth more than signing up for a newsletter subscription. Leads are prioritized based on how many points they accumulate.

But not everyone still uses the traditional scoring model. Some are turning to predictive lead scoring, an algorithm-based method that relies on aggregated data to, as the name suggests, predict a leads' value in advance.

Predictive lead scoring analyzes different data points, such as demographics and behavioral data, taken from previous leads in your database. With the help of A.I., the tool then “learns” all the shared traits between your customers, and similarly, the shared traits between leads that didn’t convert.

Once it has a clearer idea of what factors make up the ideal lead, the algorithm can then automatically score incoming leads, all without having to rely on the outdated point system.

A.I. for Lead Validation

Lead validation is an absolutely crucial step in the lead generation process. Like lead scoring, lead validation reviews all potential leads coming in through form fills and phone calls and separates them by sales leads and non-sales leads.

Sales leads are more likely to convert into customers and usually submit real information or inquiries through forms or calls. On the other hand, non-sales leads tend to send spam, solicitations, and other irrelevant material.

To cut down on time spent sorting through all that info, some marketers employ A.I. as part of their lead validation team. A.I. programs can quickly analyze submitted data, like names and phone numbers, and compare it to publicly available sources or internal databases. Based on the findings, leads are then sorted into one of the two categories.

A.I. for Lead Nurturing

Rarely will a lead convert to a customer right off the bat. It takes time for most people to make buying decisions, regardless of where they are in the customer journey. That’s where lead nurturing comes in. This practice emphasizes building relationships with leads with the goal of earning their business at their own pace.

In the past, marketers relied on tried-and-true lead nurturing techniques, such as sharing personalized content and sending email follow-ups. But the problem plaguing most marketers is getting the right messages to the right leads at the right time.

Luckily, A.I. offers a solution in a surprisingly accessible form: the chatbot. Easy to implement, highly customizable, and user-friendly, chatbots offer another point of contact between marketers and leads. Improved technology has made creating chatbots easier than ever, especially for small businesses with limited resources.

Chatbots are programmed to respond to user inquiries via live chat and can be found on company websites, SMS services, and messaging platforms, such as Facebook Messenger. When building a chatbot, many marketers develop characters for their A.I. “employee” to make the conversations between user and bot seem more natural.

Chatbots can send highly targeted messages to users, depending on their purpose. An eCommerce chatbot, for example, might send coupons or tailored product suggestions to users that visit specific parts of a site. Other chatbots might play a more customer service-centric role, asking users if they need help or answers to questions they may have about a site.

Since they are automated, chatbots can increase lead retention rates, as they offer a shorter turnaround time between the inquiry and the response.

Chatbots

A.I. and You

As artificial intelligence tech grows, you’ll certainly see its effects impact your current lead generation plan. In fact, you probably have some form of A.I. already built into your strategy, especially if you rely on a CRM platform to do your business.

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