Lead scoring is a shared sales and marketing methodology for ranking leads in order to determine their sales-readiness.
It’s important to provide sales teams with sales-ready leads. So businesses must use lead scoring to rank leads and determine their sales-readiness. But since it’s a delicate science, a misstep could damage your results. Nevertheless, this complete guide to lead scoring could make you a master.
Lead scoring is the process of using accurate data to determine how likely a particular lead is to become a customer. This information data is a blend of explicit and implicit data. (A lead gives you explicit data, but you have to acquire implicit data through research.)
As the name suggests, a score is attributed to leads based on the explicit and implicit data you have. That score acts as an indicator of a lead’s sales-readiness, and it helps add structure to the lead-nurturing process. These actions can be taken according to the group a lead is assigned to.
Lead scoring helps businesses make sure they focus their attention on viable, sales-ready prospects. This solution helps improve conversion rates, forge stronger links between sales and marketing, and keep your salespeople happy.
Since traditional lead scoring methods involve a lot of manual work, they have almost been entirely replaced by predictive lead scoring methods. These methods rely on sophisticated algorithms to automate the lead scoring process.
There are countless reasons why you should develop a sophisticated lead scoring process. Here’s a closer look at those reasons…
When it comes to the leads you send your salespeople, quality is often better than quantity. Since your salespeople only have so much time, it’s important to use the time you have to try to convert the leads that are likely to become customers.
Lead scoring can help your team to strike while the iron is hot. Then you can boost their conversion rates and close more high-dollar deals.
Since sales is such a demanding discipline, even the toughest, most resilient salespeople inevitably become disheartened if they fail to close deals. And if they aren’t being fed poor-quality leads, they’re often doomed to failure.
So if you can provide your salespeople with sales-ready leads, they’ll close more deals. As a consequence, their motivation — and performance — will inevitably rise.
In the past, sales and marketing were treated as two very distinct departments. But in most digital businesses, these two departments have never been more intertwined. So a clear lead scoring process can help get these two teams on the same page.
The very existence of a lead scoring process can also help forge stronger bonds between the two teams, which will keep them communicating.
In the world of lead scoring, there are two dominant approaches: predictive and traditional.
This type of scoring uses algorithms and a range of data points to determine the sales-readiness of your various leads. In other words, you don’t have to worry about weighing and updating values yourself; they’re handled automatically.
In addition, the most sophisticated algorithms are able to learn over time, according to your success and failure rates. They’re also more accurate because they take a larger amount of data into account.
This method uses a blend of explicit and implicit data. With this technique, you assign a point value to each criterion, then divide leads into groups according to their relative scores.
As the name suggests, traditional lead scoring is the older of the two methods. In many ways, it’s inferior to predictive lead scoring. Comparatively, it’s much simpler, but it requires more manual work. Here’s another issue: This method of lead scoring is useful for eliminating inappropriate leads, but it falters when it comes to identifying a promising lead.
As with any other process or discipline, you should follow best practices to get off to a great start and achieve the best results possible…
If your lead scoring initiative is going to be successful, you have to create the right buckets, in order to rank your leads according to their scores.
To create the right buckets, you’ll have to think about the customer journey your leads will pass through, including the factors that make sense for your product, your industry, and the markets you operate in.
So if you have a highly specialized product, you might find that it makes sense to try and initiate direct contact as early as possible. But if you operate a SaaS model, you might want to make sure that the majority of the process is heavily automated.
If your model is going to become a seriously useful tool, it’s important for you to take full control of the scores you attribute to the firmographic, demographic, and behavioral criteria you’ve established.
For instance, an off-the-shelf model for lead scoring might assign a certain score to the size of the business. But this score could be an imperative way to determine whether your lead should be contacted.
If you can customize your scoring, your model will be as relevant and applicable to your business as possible.
Lead scoring is a delicate science that’s affected by a wide range of factors, both inside and outside your business. For instance, you might adjust your SaaS over time, and create a set of features that are useful for individual users (rather than just enterprises).
In these situations, it’s important to be able to adjust your lead scoring model and facilitate your new approach. Therefore, it’s vital for you to see your lead scoring model as a constant work in progress. It’s something that will evolve over time. You should also feel free to make adjustments according to the feedback of your sales team. For example, they might suggest you should lower the score assigned to visiting a particular landing page—because those leads are often colder.
It’s important for you to educate and train your team about your lead scoring activities. Everybody in your sales and marketing departments should understand the goal and strategy you’ve adopted about lead scoring.
So you should carefully explain the logic behind the score attributes you’ve developed and the groupings you’ve chosen. When everybody is on the same page, they’ll be more likely to stick to the script.
The more eyes you have on your lead scoring process, the more constructive feedback you can get about it.
If you’re going to get the best results possible, the lead scoring model you use has to be specific to your business.
A customized scoring model will ensure that your scoring is relevant to your product, your industry, and the markets you operate in. Furthermore, it gives you full control, and it makes it easier to make small, iterative adjustments in the future.
Building your own model may sound intimidating. But it’s worth the investment, and it will save you lots of time in the future.
Here’s a look at the steps you should take as you develop your proprietary lead scoring model.
The first step you should take involves properly outlining your lead scoring objectives. Are you hoping to improve your conversion rates as a whole, or close more deals with high-paying leads?
You should take the time to identify exactly what you’re hoping to accomplish during your lead scoring process, in order to create benchmarks and assess their efficacy.
Now that you have your goals, it’s time to think about the firmographic and demographic data you’re going to consider. This data will often carry a higher weight, and it will determine whether you pursue a lead.
You’ll want to identify key criteria, such as the size of the lead’s business, its growth, and the technology it uses.
Now it’s time to identify the behaviors you’re going to assign a score, as well as the value of that score.
Some marketing departments decide to assign scores to things like visiting a particular landing page, attending a webinar or event, and opening an email. You should regularly assess the range of interactions you’ll have with your leads and assign scores to each of them.
Equipped with a better understanding of the criteria you’ll use, it’s time to think about whether to use a traditional or predictive approach to lead scoring.
Since you’ll often find that a predictive approach makes the most sense, you should take the time to explore the various providers out there, as well as the structure of the algorithms they use. Then it will be possible for you to identify the most predictive approach.
To get the most accurate results from your lead scoring initiative, it’s very important to have the appropriate spam filters in place. This tactic can help you maintain quality and filter out any spam leads.
For instance, you might notice that a lead has completed a landing page, but he’s put the same text in all the fields on the form. In this situation, you might want to give that behavior a negative score, in order to reduce the quality of the lead without eliminating it entirely.
Now that you understand the behaviors you’re going to assign either a positive or negative score, it’s time to strategize the ways the actual lead scoring formula will come together.
You’ll want to create logical groups that place your leads according to the score value they have. To make sure your scoring is as accurate as possible, you should adjust those brackets over time.
Since traditional lead scoring requires a lot of effort, the results are often less than the ones offered by predictive lead scoring.
Throughout the process of creating your lead scoring model, you should try to identify opportunities to implement automation. Then you can make your process as smooth as possible and improve the results you see.
Now that you have various buckets for your leads in place, you should think about ways to nurture each group. Let’s imagine that you created the following groups:
When you have a cold lead, you might decide that your priority is educating them about your product or service. You could also establish an automated email campaign that will provide this person with the information he or she needs.
Now that your lead has acquired the points to be considered educated, it’s all about trying to inspire action and transform him or her into an interested lead. This goal could be accomplished by using webinar invites and case studies.
The success of your lead scoring model hinges on whether you choose the right data points for it. Here are ways to make sure you choose properly…
To begin, determine the most important data points you use, and think about your ideal customer in terms of firmographic data. Does he or she have an annual revenue threshold or a certain number of employees? Does he or she work in a particular industry?
Decide which factors are the most important, then use them as data points in your lead scoring model.
How are you going to nurture and sell to your leads? For example, do you use a lot of content marketing? If so, you’ll want to use their engagement with your content as a data point.
Do you try to engage with senior-level contacts? If so, you’ll want to make sure your job title is a data point.
Sometimes, you simply won’t be able to work with a lead. Their business may be too small, or you may not be able to serve their industry.
In those instances, it’s important for you to assign a negative score to the appropriate firmographic data points.
Lead scoring can sometimes sound a little abstract and difficult to understand. But it almost always falls into place when you take a look at some lead scoring examples.
Here’s a closer look at ways you can calculate the scores for different series of leads…
It’s important to identify the leads that have moved from initial interest to light engagement. Here’s a breakdown of what a lead’s score might look, based on a series of firmographic and behavioral data points:
Total: 52 points
Depending on the groups you’ve developed, you might find that this score takes a lead into the next threshold and defines him or her as a mature lead.
You also have to develop your lead scoring activities, so that your mature leads have their own groupings. Then you’ll have the opportunity to place them into more specific automated programs that can convince them to take the plunge.
Here’s what their score breakdown may look like:
Total: 72 points
Let’s say you have a mature lead who’s a woman. After you’ve provided her with the appropriate marketing and outreach, she might take a critical step that makes her become a sales-ready lead. In other words, she’s ready to be qualified by your sales development representative or passed directly to sales.
You might decide that the trigger for moving a lead into this group is reaching a certain threshold of points. Or you might decide it’s triggered when the lead takes a particular action.
For instance, you might decide to automatically add the previous lead to the sales-ready group after she’s filled out a demo request form. Then you can qualify her.
The lead scoring model you adopt will vary greatly according to a range of factors. One of the most significant factors is your business model.
If you interact on a B2B basis and offer specialized solutions to your customers, you might find that your lead scoring model needs to adopt a larger viewpoint. For instance, the inside sales process might look much longer, and you’ll have to reach more significant milestones along the way.
Therefore, you might find that you attribute high scores to particular milestones that your lead achieves. For instance, you might have a few meetings or calls with him before you seal the deal. So you’d attribute high scores to those types of behaviors.
In the world of SaaS, you want to automate your marketing and sales processes as much as possible while you reduce the length of your typical sales process.
This tactic will help you close as many deals as possible in the shortest amount of time, which will boost your sales volume and your monthly recurring revenue. To achieve these goals, you’ll want to finetune your lead scoring model, based on the behaviors of your different targets.
For instance, you might offer a few different services. If so, it might make sense to develop a range of automated marketing programs according to the specific interests of your lead.
We hope this piece has inspired you to unlock the massive potential of lead scoring. If your lead scoring activities are going to be successful, you need access to the right data.