AI Lead Scoring: How To Use AI To Manage Leads More Efficiently
As a small business owner, you know that time is your most valuable asset. You can’t afford to waste time on fruitless actions or tasks that require too much manual effort—like pursuing poor leads. Lead scoring can help you avoid this problem altogether.
What Is Lead Scoring
Lead scoring is a term used to describe a company’s internal process of determining how likely a lead is to convert. Each company develops its own scoring system that assigns a numerical value or point to each lead based on specific criteria such as how often and how long a customer engaged with the company website, the number of interactions on social media, and how closely their demographic information aligns with the target market. The higher the score, the more likely a lead is to convert into a sale.
The Importance of Lead Scoring
Initially, the goal may be to get as many people into the sales funnel as possible, but once you’re consistently generating leads, it pays off to prioritize those who are actually interested and ready to act. Analyzing a lead’s likelihood to convert through lead scoring helps sales and marketing reps quickly gauge the quality of each lead so they can focus their efforts on the most promising. This reduces the amount of time and resources wasted following up on bad leads that amount to nothing and also ensures a good lead never falls through the cracks.
The Rise of AI in Sales And Marketing
Traditional sales and marketing strategies such as lead scoring are evolving at breakneck speed, largely due to the introduction of Artificial Intelligence (AI). AI is a groundbreaking tool with advanced analysis capabilities that allow for traditional research and data analytics to be completed in seconds instead of hours. In the case of lead scoring, AI has made a very manual, labor-intensive process faster, more efficient, and more robust with predictive lead scoring capabilities.
Understanding Lead Scoring
Before jumping into the changes AI has brought to lead scoring, let’s first review how traditional lead scoring works.
Any company that wants to implement lead scoring needs to start with step one—develop a value system for awarding or subtracting points from a new lead so it can be ranked appropriately. This is done by analyzing past contacts who became customers and contacts who didn’t become customers to see what attributes they have in common. You can utilize any attributes you feel are relevant to measuring a lead’s likelihood of converting into a sale, but some attributes are used more commonly than others, such as demographic and company information, online behavior, and past engagement with the brand via email or social media.
The company assigns a weight or value to each attribute, often represented by a certain number of points. These values are then totaled up to create a score for the lead. The simplest way to calculate a lead’s score is to manually analyze the various attributes of the lead and add up the assigned values. Alternatively, you could take a more mathematical approach and use data mining techniques like logistic regression, which involves building a formula in Excel to analyze inputs like company size, location, etc., and return the probability of a particular lead turning into a customer. However, this method requires a more advanced understanding of lead scoring and Excel, which is why many businesses are ditching both this and the manual method in favor of predictive lead scoring made possible by AI.
How to Add AI Into Lead Scoring
The traditional lead scoring methods can be tedious and time-consuming, requiring hours of data analysis. They’re also very rigid processes that lack the flexibility needed to keep up with rapidly changing consumer habits and behaviors. That’s why lead-scoring AI is such a game-changer.
What Is AI Lead Scoring
AI lead scoring takes traditional lead scoring methods to the next level by applying machine learning algorithms to the standard scoring process. With its advanced pattern recognition and analytical capabilities, AI can analyze and qualify a lead faster and more efficiently than humans can. Plus it removes the human bias that was an inevitable part of traditional lead-scoring.
How Does AI Lead Scoring Work
AI lead scoring takes the manual work and subjective human analysis out of the lead scoring process. Using historical actions as its guide, lead-scoring AI compares leads to each other and past successful conversions to look for patterns in behavior that most often led to a sale. It then performs lead-scoring predictive analytics to predict how likely a lead is to convert. Within seconds, the algorithm can compare the lead to established criteria, account for the relationship between those criteria, and then calculate and assign a score automatically.
How Is AI Lead Scoring Better Than Regular Lead Scoring
Not only is lead scoring AI faster than a human and more accurate than a human due to the lack of biases, but it’s also more dynamic. At its core, AI is a machine learning algorithm, which means it’s constantly learning and adapting. This means as your customers’ habits and behaviors change, so does your lead-scoring AI.
Meet Podium’s AI Employee
Here at Podium, we’ve implemented our own AI to assist with managing and closing leads. Our AI Employee is an all-in-one conversational AI. Its has been trained to schedule appointments and respond to customer texts, all without any additional staff oversight and while sounding completely human. With our AI Employee, a lead can be followed up on within seconds of arrival in the queue, giving you a headstart on winning the potential customer’s business over other companies who will still need to manually review and qualify the lead before ever sending a response.
5 Benefits of AI Lead Scoring
Increased speed and efficiency when qualifying and responding to leads are some of the most recognizable benefits of using lead-scoring AI, but there are many more that make themselves known over time. Here are the top five benefits business owners rave about the most.
Error Elimination Through Automation
Human error is an inevitable part of doing business, but steps can be taken to minimize the chances of it happening. Traditional lead scoring is a manual, hands-on process that relies on human data manipulation. Humans aren’t perfect, so the more data is manipulated manually the greater the opportunity for mistakes. Lead scoring AI uses algorithms to perform analyses, which means each lead is analyzed the same way every time with no risk of errors due to human fatigue or bias.
Enhanced Insights via Data-Driven Intelligent Modeling
Lead scoring AI is capable of analyzing vast amounts of data independently and as a whole. The depth of analysis it can perform far exceeds what’s possible in the amount of time a human can allot to review each lead. Predictive lead scoring models can provide more information in less time, giving you a better understanding of each lead that comes through so you can respond accordingly.
Seamless Integration with CRM Platforms
Customer Relationship Management (CRM) platforms are an integral part of managing the customer journey from start to finish. Lead scoring AI can integrate seamlessly with existing workflows in your current CRM, enabling all team members with greater access to lead insights and scoring so you can work better together to nurture leads into conversions.
Align Sales And Marketing Teams
By expediting the scoring process, lead scoring AI makes scoring more readily accessible to both sales and marketing team members. When both teams are on the same page, they can work hand-in-hand to smoothly transition leads to sales and close deals more quickly.
Accelerated Revenue Growth
At its heart, every business’s goal is to increase revenue. With the help of lead scoring AI, teams can identify and pursue the leads with the highest likelihood of closing. This results in better use of company time and resources, more positive sales interactions, and higher conversion rates, which will ultimately boost the company’s financial standing.
Top 10 Lead Scoring Apps of 2024
Now that you understand why you should prioritize lead-scoring AI over traditional lead-scoring methods, let’s take a closer look at what lead-scoring AI options are available. Here are the best lead-scoring apps of 2024.
Podium’s AI Employee
Podium is an all-in-one lead conversion platform with an AI Employee add on that can help you follow up with leads in record time. Our AI Employee can engage in text conversations with potential leads without any additional human oversight, helping you respond faster than the competition. The AI Employee can be added to any Podium plan. Podium’s pricing starts at $399/month.
Salesflare
Salesflare is designed for small and medium-sized businesses looking to automate their CRM. Key features include automation for CRM data input and tracking for emails, links, and website visits to easily report on behavior online. Salesflare’s Growth plan charges $29/user/month and is billed annually.
ActiveCampaign
ActiveCampaign is a CRM designed specifically with sales teams in mind. Its platform is focused on optimizing the sales process with every plan including key tools like lead scoring AI, sales automation, and task management capabilities. ActiveCampaign’s plans begin at $19/month billed annually.
HubSpot
HubSpot’s lead scoring AI uses a holistic approach to predictive modeling, studying the entire customer journey to provide key insights. Currently, lead scoring is only available in the Enterprise plan for $3,600/month and the Sales Hub plan for $1,200/month.
Clearbit
Clearbit is designed for business-to-business (B2B) companies looking to enrich their data with precise lead scoring and customer segmentation that drive performance and deliver results. Contact Clearbit for pricing information.
Leadsquared
Leadsquared is a sales automation platform with the goal of easily connecting sales team members across channels so no opportunities are missed. The lead-scoring AI will automatically capture leads from all channels and deliver them to the right team for the next steps. Pricing for Leadsquared starts at $400/month for 10,000 contacts.
Marketo
Adobe’s Marketo Engaged is a B2B-focused automation that uses predictive AI to build audiences and provide segmentation so sales and marketing can work together to nurture leads across all channels. Marketo plans start at $895/month.
Oracle Eloqua
B2B-focused, Oracle Eloqua’s AI offers advanced lead scoring and real-time data analysis of firmographic data so users have everything they need to launch and manage a cross-channel marketing campaign. Contact Oracle Eloqua for pricing details.
Infer
Infer’s lead scoring AI can be easily integrated with your CRM, so real-time scoring is available to all sales and marketing teams. Their AI is always learning, so with each conversion, new insights are gathered and applied to all future predictions. Contact Infer for pricing details.
Pardot
Salesforce’s Pardot is the smarter marketing automation designed to work seamlessly with your Salesforce CRM to manage all aspects of the sales journey and maximize your return on investment. Pricing starts at $1,250/month.
Ready to take your lead management to the next level? Podium can help! Learn more about Podium and how our AI-infused platform can help automate manual tasks, helping you convert more leads in less time.
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