Lead generation is a crucial stage in marketing; It’s how we find new business. You may be in search of a few new clients, and due to the basic math, there’s only one option for finding more. You must “get out” to generate new leads. Technology has changed how sales teams do this, but what we need from our leads remains a part of the traditional business model. You want to schedule appointments, qualify your prospects, and spend less time doing each.

These reasons make educating your staff on new, emerging AI systems something that every modern business must do. Otherwise, you’re stuck with the work: the data mining, processing, and analyses are taking time from the consumer relationships you build. Digital is helpful but can also be time-consuming. You’re in an unfortunate predicament if you rely on “blind tactics” like cold calling or “randomly choosing leads out of a hat.” Such won’t work.

Crunching the endless data of online marketing is a thing of the past—with the help of automation. According to Scott Smith, the president and CEO of lead generation company Launch Leads, automation can verify “leads with which your sales team [then] engage … [by] spending less time and effort on disinterested opportunities.” Being competitive requires you to minimize your workload, and artificial intelligence is redefining how marketing is scaled. Let’s see why AI is important and how it can boost your revenue.

When Sales Automation Comes into Play

Sales automation is taking digital marketing to greater heights. Automation is a simple concept, although powered by sophisticated technology. It’s applied in fundamental ways to achieve the things that we would usually do ourselves. In seeing automation at its core value, we find that scaling the manual labor of computer processing as the what. Every day, data processing is necessary, but it needs some manual input if you’re without automation.

Working online forces you to work with data—be it figures that need to be shifted through, labeled, or placed somewhere. Data processing gives us “the” definition for the ideal role of computers. Each phase is only bypassed with automation. It’s not enough to say that the process is done by computers, for automation processes data without you pressing a button. After each unit, person or money enters, the next stage occurs without your touch.

Here’s where the usefulness and power of artificial intelligence come into focus. The scope of AI still allows you to automate but with a better eye for the details, a faster work sequence with fewer people involved. This scalability means that, though you didn’t decide, AI, after processing data, decides on the next-best step. No matter what those actions are, with AI’s help, we’ll boost sales, generate more leads, and minimize the work.

Why Artificial Intelligence is Possible in Online Marketing

Machine Learning and AI Capabilities

Artificial intelligence uses machine learning to learn from new data. Most AI systems act on the data and processes they have. Machine learning, however, gives AI the ability to act on the data it acquires. These technologies work on “new intelligence” to diversify what they can do. Though common AI bots can repeat a pre-programmed function, those with machine learning, as built within, can process data to decide outside of the protocol.

These algorithms, depending on their purpose or their creator, can extract data directly from patterns, filters, or by receiving new instructions. Predictive analysis is part of this process and gives AI a future projection. It’s “computational statistics” that enables AI to think. Machine learning isn’t just about learning new info. The marketing value it has, which we use to boost lead generation, is that AI can anticipate a future action based on today’s data.

This aspect requires that AI leverage predictive analysis. We, ourselves, can’t predict the future, and neither can robots, but this form analysis gathers data about what’s most likely to happen. Predictive analysis uses probability and statistics to give your marketing software “reasonable information [with which] to reason.” Predictive analysis is how computers measure something before making their decisions.

Predictive analysis considers risks, comparisons, and historical stats as related to any specific entity. In this case, our focus is on your consumer: these are the leads that you want to convert. Automation is only effective once your leads receive a label and a measurable rating. That label is called a predictive score, and we’ll talk more about lead scoring later. We must first start with how AI uses new data to find more buyers.

Lead Generation

Generating leads, as it stands, is a simple concept. As a practice, it can be complicated if you’re managing too many pieces at once. In every case, leads must be contacted before they can buy. We must tell them about who you are, what you do, and why it matters. Your worst strategy is in building a business with the hopes of people just showing up. We must reach out to the most qualified leads to “get them.”

AI can improve many digital outreach tools, but you need to decide on how to generate your leads. You can collect leads through measurable metrics: contacts, emails, and addresses. Each step is repeatable. Social media, organic search, email marketing, guest posting, blogging, and pay-per-click ads are options to consider. Artificial intelligence can optimize each, and due to our competitive world, AI may even be necessary.

Your objective is to process the most amount of data within the least amount of time. Remember, lead prospecting is about finding consumers who fit with your consumer profile. Quality is also important, for with AI, what’s collected from your prospect must be used for predictive analysis during AI’s decision making. Automation reduces your manual labor, but AI gives your data a purpose. You want data, sure, but you will also want to act on it.

Artificial intelligence scales down the work in lead prospecting by also managing the content. Content is a crucial piece in every stage of online marketing, and this includes lead generation. With content, your leads make the first or final connection with your brand. You must speak to your leads clearly, so the structure of a prepared message is crucial. Let’s get a better grasp of what a lead is as we begin to see the framework of a practical strategy.

A Better Way to Define Your Leads

Leads are the consumers who’re initiated into your sales funnel. Leads, when looking at the equation from a business’ perspective, have the single objective of becoming your buyers. You cannot close every prospect on a sale. We’re not looking for just anyone. You don’t want to comb the internet in search of random people to pitch. A lead must fit your consumer profile, and you can write a profile in detail with the help of AI software.

Organizing a profile doesn’t guarantee that your leads will convert, but you will improve how your resources are used to acquire them. By creating a profile, you can essentially create boundaries. Your AI program will then know how to rate a new or existing lead. This profile gives AI a better trajectory when it makes decisions. Your goal is to get leads into a sale by automating a relationship based on who they are and what they do.

Though automated with AI, this is called lead nurturing. Nurturing will warm/bring leads into your product sell and delivery stages. Artificial intelligence will streamline this by collecting historical data on a lead and by keeping a score on that person’s marketability. Consumer data can then guide the software into a strategic decision that closes a prospect on a sale.

Lead Scoring

Getting technology to determine the value of a lead is essential in sales automation. You don’t want to discriminate or to portray one sample size as better than the other. Our aim is to find out who your active leads are, who’s ready to convert and who needs to be brought to the next level of sales. Your lead score is essentially a measure of priority. Every business must manage its outreach cost, and that can only happen once you track your leads.

Let’s consider what dictates the score of a lead. The first is engagement. How often does a lead make searches for your brand? Have you tracked them on your website and landing pages? Did they sign up for your webinar or newsletter? Are they opening your emails at a consistent rate? You can track these factors with machine-learning software, and just as you would, the software assigns a priority score to behaviors and actions.

Scores allow you to send personal materials and messages to individuals. It’s important to note since you won’t need to treat each person the same as another. The scores given to each lead are automated via machine learning. You have the power to analyze the criteria and to see how effective your leads are at entering your sales funnel, but you won’t have to tally every detail manually. Let’s now consider the explicit and implicit data of your leads.

We consider someone’s name, occupation, or age as specific data in sales automation. These metrics are measured when scoring your consumer’s priority. Implicit data measures the actions that each lead takes. Implicit data includes clicks, time spent reading your content, and website visits. These are two metrics that are used by artificial intelligence to create a lead score.

The Benefits of Lead Scoring

A consumer profile is as essential to you as is the structure of your business. The business market is a digital one, but there are still many things to achieve that are part of a traditional business model. There are no one-size-fits-all for lead prospecting. Every lead is different, and through small differences, for example, some prefer Pepsi but not Coca-Cola. Others say that there’s no difference. This is not an accident. Scoring your leads helps in building a consumer profile that fits your brand.

It tells you about what people like and who. You then want to target people that fit. The clearer your outline of the ideal customer is, the faster that you’ll meet them “eye to eye.”

1. Marketing:

Targeting is not just the art of marketing. It’s the act of highlighting a specific persona and telling your artificial intelligence to only invest in that “persona.” It takes study and preparation to identify the ideal target and to know where they are. Artificial intelligence can maximize your marketing by only interacting with the leads who care.

2. Sales:

Once you know “the who,” you no longer must pursue them manually. Preset your AI program to automate your outreach and to invigorate your campaign. Consider having artificial intelligence take over: let it do the marketing, lead generation, nurturing, and then sales. Machine learning will even adjust to the changing whims of your consumer.

3. Accuracy and Revenue:

The closer you are to your leads, the more you’ll understand the way that they behave and why.  This part is the warm stage of lead nurturing, and the data extracted by machine learning and artificial intelligence can help you better achieve it.

How Artificial Intelligence Can Help

The power of AI now takes hold of online marketing as the web grows and expands. The complexity of digital makes it difficult for you to find the right leads. You need to ensure that your consumers aren’t robots, that they fit into your consumer profile and that their actions reveal the likelihood of buying. If you have some content, you can program your AI service to send it to the right person. This fact is why artificial intelligence is making a breakthrough.

It can decide on what, from your batch of prewritten materials, to present to your prospects. Imagine what you can do to prospect, and nurture leads within a single hour. Artificial intelligence can do it within seconds—and for hundreds of thousands of potential sales.

Written by 

Rahul Yadav is Digital Marketing consultant and Expert in Delhi, India. He provides SEO, Social Media Marketing & PPC Consulting Services worldwide. Follow Facebook, Twitter, Linkedin

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