How to Use Machine Learning for Better Lead Qualification and Management

How to Use Machine Learning for Better Lead Qualification and Management

How to Use Machine Learning for Better Lead Qualification and Management

Every business needs to find new audiences to grow — but not every prospect will prove fruitful.

New lead management tools have powerful features that help marketers identify the most important prospects. Some use advanced technology like machine learning and artificial intelligence.

While AI and ML may seem complex, they’re more accessible than ever, thanks to new tools designed for marketers and salespeople without a technical background. 

This is why ML is so useful for lead qualification and management — and how any business can use ML-powered lead qualification tools to manage its most important prospects.

What Is Lead Qualification? How Can ML Make It Easier?

Lead qualification is the process of determining how likely someone is to convert — make a purchase, subscribe, rent or otherwise shop with your business. Typically, it’s most important to B2Bs. 

However, lead qualification is also important for B2Cs that make most of their revenue from high-value purchases. The high-spending customers that shop with these companies may spend a significant amount of time in contact with the brand before making a purchase, making lead qualification more useful.

Qualifying leads is essential for businesses that want to get the most out of their marketing and sales efforts. Identifying prospects that are likely to convert and estimating how much value they’ll offer directs your attention to the most worthwhile leads. 

In most cases, lead qualification relies on buyer personas representing a business’s key audience, combined with data from previous sales. These help companies identify patterns in leads that have converted and use them to their advantage. 

Lead qualification allows companies to get hard data on the prospects most likely to convert, allowing salespeople and managers to make more informed decisions.

This process can also help with lead nurturing. Many prospects never turn into sales. Some would have never converted, but others drop off due to a lack of engagement from the business. 

A company can nurture leads and build relationships with potential customers through emails, instant messages, phone calls and other communication channels. A strong nurturing process can help any business encourage conversion. Qualification also makes it easier to keep track of leads, making things more consistent.

What Is Machine Learning and How Does It Help Lead Qualification?

Machine learning is a kind of artificial intelligence software and program that allows a computer to perform tasks that typically require a person’s creativity or problem-solving ability. ML is a subcategory of AI that includes software and algorithms capable of improving through experience. 

A machine learning tool can effectively use new information and previous successes or failures to get better at a task.  

ML and AI have both been challenging to use for the past few decades. For the most part, their use was limited to businesses that employed computer engineers and other workers with the technical knowledge to build their own ML/AI tools from scratch. 

Now, there’s a growing market of ML software for general-purpose users, meaning that the average marketer, salesperson or manager can start taking advantage of the technology.

Predictive lead qualification software is some of the most valuable AI technology available for B2Bs. These tools use ML, combined with data your business may already collect, to predict the value of a lead.

Some major e-commerce platforms already offer predictive lead qualification, like HubSpot. HubSpot’s system uses thousands of data points to determine how likely a lead is to convert.  

You can also use standalone platforms, like Infer, MadKudu and Pathmonk, which allow you to learn more about your leads with your business’s website data.

Using Machine Learning to Qualify, Nurture and Manage Leads

Using ML for lead management is often as simple as researching available platforms and choosing the one that works best for your business. For example, if you need an all-in-one marketing and CRM platform that also includes predictive lead qualification tools, a platform like HubSpot may be a good investment. If you’re already happy with your CRM platform and just want to invest in predictive lead qualification, another simpler tool may be a better pick. 

Predictive lead qualification is often simple once you’ve selected a tool and have it running. It probably comes with tutorials and documentation that will explain how to use it. You’ll also have direct access to a customer service line if something doesn’t go right — or if you need a little help learning how to use the software. 

How a tool qualifies leads may vary. Most programs will assign each prospect a score or probability of converting. They will also tell you what factors were considered and give you an idea of the data used to qualify the lead. 

You can use this information to manage your prospects. You may also be able to export the data to other tools — like a CRM or dedicated lead management system.

Machine Learning Can Make Lead Qualification Easy

Lead qualification is essential for most B2Bs, as well as B2Cs that rely on high-value customers. Predictive lead qualification, powered by machine learning, is a powerful tool for these businesses — and, right now, it’s more accessible than ever.

An existing CRM or lead qualification tool lets your team automatically qualify the value or conversion likelihood of a new lead. Over time, these tools can help you predict which prospects will offer the most value, allowing the business’s sales team to focus their energy where it matters most.

Tags: Leadsai
Nick Loggie:
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