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Implementing lead scoring safeguards your sales team’s time by helping them spot and engage with the highest-value leads while avoiding low-value ones. In this post, we’ll go over the basics of lead scoring and lay out a five-step process for creating your business’s lead scoring system. We’ll also share some software tools and best practices that can help you manage the ongoing process of scoring and ranking your leads for the best results.
Lead scoring is the ongoing process of scoring and ranking the leads in your sales funnel against a set benchmark. Lead scoring uses a point system, where leads earn points for behaviors that show interest in your business and for demographics indicative of a good fit. Commonly scored behaviors include web page visits, content downloads, and social media activity. Meanwhile, demographics consist of data points like company size, job title, age, and gender.
Over time, a lead takes multiple actions, and their score increases. Some actions, like visiting the pricing page, earn them more points than others. Typically, leads are given a score out of 100, with 80 or above being a qualified lead. However, these numbers may vary based on your situation.
Lead scoring is typically done automatically using lead scoring software to qualify marketing qualified leads (MQL) before handing them off to the sales team. However, anyone can use an automated lead scoring system to rank prospects at any point in their lead funnel. Ultimately, lead scoring helps you move qualified prospects from the lead generation to the lead nurturing stage of your sales process. Let’s now take a look at the top benefits of lead scoring.
Any type of business can benefit from implementing a lead scoring system. It helps you focus your sales efforts on your most fruitful leads, respond to them quickly and appropriately, and ultimately close more deals. But that’s just the beginning. Here are some specific benefits of lead scoring:
Whether you convert leads into customers using outbound or inbound sales tactics, lead scoring can help you fine-tune your sales process.
Now that you know the basics of lead scoring, let’s go over how to create your own lead scoring process. Below is a five-step plan for creating a lead scoring process that will successfully locate and bubble up hot leads based on their interest levels (behavioral data) and business fitness levels (demographic data). The barebones of the plan are as follows:
Now that you know the basics, let’s dive into each step and explain how to do it.
An ideal lead is one with characteristics (demographic data) indicating a high likelihood of making a purchase. They will look like your best current customers. In this process of identifying your ideal lead, you are selecting demographic data to assign point values later in your scoring system.
To find these demographic data points, start by evaluating the customers who derive the most value from your solution. A lead who shares their traits is likely to receive a similar amount of value. So these leads are also the ones to whom it will be easiest to sell; therefore, they will receive higher lead scores than those who lack these specific characteristics.
Now, write up the demographics of your ideal lead, filling in the following:
Which data points matter most for identifying an ideal lead will depend on your company. For instance, a B2C company will care more about the individual’s attributes like age, gender, or marital status. Meanwhile, a B2B company will focus on the individual’s company data such as job title, location, decision-maker status, industry vertical, company size, or company revenue.
Keep in mind that these data points are unequally useful in predicting the likelihood a lead will convert, so they will receive different point values later on. For example, a B2B tech company might find that larger companies are most likely to purchase their tech, but that the company’s location matters only slightly. Therefore, having the right company size earns more points than being in the right location. In step three, we’ll help you assign these point values.
Your demographic data has helped you narrow down the leads you are interested in speaking with. Now you have to figure out how to determine whether a lead is interested in talking to you. Do this by listing every behavioral data point, or actions your leads take that signals purchase intent. How a lead interacts with your marketing emails, website, and content helps you determine their level of interest in making a purchase.
Just focus on getting those actions down on paper. You will assign point values to them later. The actions listed below descend from high- to low-scoring actions. Of course, that’s a generalization and scoring systems depend on your business. As you’ll notice, actions that have to do with learning more about your product or service usually receive more points.
The above are actions that will receive positive scores. Be sure to incorporate negative scoring actions, as well. These are actions that signal disinterest in your product or service, like email unsubscribes, visits to a careers page, or a long time without interaction.
While developing your list, highlight in yellow critical conversion behavior: actions taken by nearly all leads who end up becoming customers. Usually, these are things like visits to a pricing page or requests for a demo. Doing this will help you start thinking about which behaviors will earn leads the most points.
Assigning point values to each data point is the most difficult part of lead scoring. But, don’t worry about being perfect at the start. As long as you make educated estimates about the point values, your lead scoring system will work effectively. You can always make changes down the line. For now, let’s focus on assigning point values in a way that gives you a balanced scoring system that takes equally into account both demographic and behavioral data. Here’s how.
Most companies choose to rank on a scale of 1-100 total points. Others might expand their scoring range to classify leads by other crucial factors, such as size. For example, one company might expand the scoring range to 1-4,000 so that they can classify leads by whether they are small, medium, or enterprise leads.
For example, all small businesses’ scores might begin with the digit one, medium businesses’ with two, and enterprises’ with three. An enterprise business that is a perfect match might be 3,100, while a small business with a 50/100 score would be 1,050.
The best way to do this is by dividing your total possible points evenly between the demographic and behavioral categories. So if your point total is 100, leads can only earn 50 from the behavioral category and 50 from the demographic. That way, the lead scoring system won’t qualify ideal leads unless they both express interest in your solution through their behaviors and are a good business fit according to their demographics.
From there, allocate those 50 points to the unique data points in each category. The actions and characteristics that most define a promising lead will receive the most points. For example, the final scoring system for a B2B tech company might look like this.
Demographic Point Values (out of 50):
In this system, if a lead has the job title of VP or higher, they’ll earn 15 points. If they’re a CEO and a manager, for example, they’ll earn 25 points. If they’re neither, they’ll earn zero. If their company industry is something other than real estate, they’ll earn zero points. In this system, it’s all or nothing. A more intricate system might include other fields in the scoring system; perhaps leads who manage one person receive five points instead of zero.
Note that a VP with management responsibility of a team bigger than two earns 25 points, while a VP without that responsibility only gets 15. This means the company sees better conversion rates with VPs who also manage a team. Also notice that even if a lead checks all of these boxes, they still earn only 50/100 points. They have to take some interest-expressing actions. The B2B tech company’s behavioral scoring system might look like the below.
Behavioral Point Values (out of 50):
Going with the above example, if a CEO of an accounting firm took all of these actions, they would still earn just 50/100 points, coming short of a sales-ready threshold of 80/100 — a standard scoring threshold for a lead to enter the sales team’s domain.
This makes sense. A company has no reason to reach out to a lead who is such a dreadful match with their ideal customer profile. Instead, if they have their contact information, they should continue marketing to them and learn more about them. Perhaps there’s information they haven’t yet revealed. But if it turns out they are a bad fit, they should consider dropping them from marketing campaigns.
When selecting data points and assigning them point values, you can get as broad and complex as you’d like, especially if using a software tool, which helps you keep track of every scored action a lead takes. What matters most is that you create a balanced scoring system that takes equally into account both the behavior and demographics of the leads.
Next, it’s time to set your scoring thresholds: a score a lead must meet to enter the next qualification stage. When a lead surpasses it, marketing passes the lead to the sales team. From there, a sales rep takes a defined action. Commonly, this is reaching out to qualify them further before marking them as a prospect.
You can get fancier here if you’d like and create multiple lead thresholds for leads with lower scores, as well. Maybe leads who hit scores of 50/100 are considered warm leads, so a lead with a score of 55 is considered an MQL, and therefore receives marketing content and mass emails. And perhaps throughout this time in the funnel, the lead interacts with enough content to hit 80. Now it’s time for sales to take over.
Including more than one threshold can help you personalize your marketing and sales efforts based on a buyer’s level of interest and fitness, which will help you convert the qualified ones into prospects more quickly.
Now that you’ve chosen your data points to score for, assigned them point values, and chosen a scoring threshold, it’s time to start tracking and scoring leads for qualification. If you have lead scoring software (usually in your CRM), the software will walk you through the process and track score-earning actions and demographics for you.
If you still don’t have lead scoring software, start recording it in a spreadsheet. Each time a lead reveals a demographic that earns a score, add it to their total. The same goes for any of the score-earning actions they take. When leads hit your threshold, qualify them into the next stage of lead qualification. Do this for a month, then assess the effectiveness of your point system.
During this process, keep feedback open between you and the sales team regarding whether the leads you pass were actually qualified. Have them inform you when a lead passes the threshold but wasn’t qualified. Take note of these occurrences for later. This will help you in the next step, where you figure out how to fine-tune your lead scoring system.
Your point distributions are mainly educated estimates and will rarely be perfect on your first try. Luckily, if you continue evaluating and refining your model, you will approach perfection. We recommend evaluating your lead scoring system every month. For instance, you might have originally thought a visit to the pricing page was worth more than a white paper download. After analysis, you might realize that it’s the other way around and make some adjustments.
During the evaluation process, ask your team these questions:
There will always be a few outliers. As long as the average score of converted leads is higher than the average score of those who never converted, you are moving in the right direction.
Rather than adding points to a lead in a spreadsheet when they reply to your email, try automating the process with lead scoring software that scores them for you. With most of these tools, you set up your own lead scoring rules. Based on these rules, the software recognizes when a lead should earn points and adds them appropriately. This makes your job much easier. Let’s go over the three best lead scoring software solutions.
Freshsales offers a CRM with a built-in lead scoring tool that can help both B2B and B2C companies of any size. Freshsales knows that the actions and characteristics that define ideal leads differ from business to business, so the software gives plenty of opportunities to customize your lead scoring rules and thresholds, as shown below. The CRM’s starting cost is $29 per month. Larger businesses focused on efficiency might want to try the Pro plan ($69 per month).
HubSpot Marketing Hub is an all-in-one toolkit for inbound lead generation that helps you enact and track marketing campaigns. The Enterprise plan ($3,200/month) specializes in predictive lead scoring. With machine learning, it analyzes thousands of data points to score your leads, as shown below. This makes it best for larger companies who want to leverage artificial intelligence in their lead scoring.
ActiveCampaign is a marketing automation platform that provides email marketing, marketing automation, and CRM tools that enable you to optimize the customer experience. ActiveCampaign’s Plus package is best for companies looking for a basic, less expensive lead scoring option ($49 per month). Users set up their own lead scoring rules, and the system adds and tracks points automatically. It can also autostart nurturing campaigns when a lead hits a score threshold.
Follow these four lead scoring tips to create a lead scoring system and ensure that it accurately predicts a lead’s likelihood to buy.
Your lead’s likelihood to buy can depend on where they came from. Pretend you have two leads who both ended up on your pricing page. Perhaps one came from a PPC Google Ads campaign, while the other came there through organic search. Both show intention to buy a solution like yours. But the one who came organically, without your influence, shows an intention to buy from you specifically. They therefore may deserve to earn 10% more points.
Some leads will sit somewhere in your sales funnel for many months without taking any action. The longer they refrain from engaging, the less likely they are to buy your solution. Your lead scoring system should factor this in by instituting a point decay rate where leads lose points for inaction. Best practice states that companies with longer sales cycles can have longer durations of inactivity before a lead gets a deduction.
Here’s an example of a point decay rate:
You don’t want to inflate a lead’s score by giving them points for every email open. For all you know, they just open every email they receive to keep their inbox tidy. Instead, give points only for a number of initial email opens. Usually, the difference in interest level is negligible for a lead who opens 10 of your marketing emails and for one who opens 50. After they reach that initial threshold, only give them points for replies, internal link clicks, or compliance with email CTAs.
When you are researching software options for lead scoring, including the ones mentioned above, be sure to ask about this functionality. Most will be able to accommodate this need, but others might just add points for every email open.
The more data points you include in your lead scoring model the more accurate it will be. But manually keeping track of hundreds of data points is unfeasible for most businesses. It’s therefore critical to automate your lead scoring using software platforms. That way, your salespeople can focus on reaching out to sales-ready leads and marketing can work on evaluating and optimizing the lead scoring model.
Lead scoring enables your sales reps to give the high-value leads the attention they deserve, leading to higher win rates, increased sales velocity, and improved revenue numbers. Not to mention, it will do wonders for their confidence and morale. It’s a lot more fun to reach out to promising leads than to ones who give you a feeling of uncertainty. Start building your customized lead scoring model today and begin earning some points of your own.