When people first begin to implement inbound marketing strategies, they’re mostly concerned about how to get enough leads into the funnel.
But once you have lots of leads it’s time to determine those who are truly attracted to your product and who’s just starting to investigate.
This is the point where lead scoring comes in.
What is Lead Scoring?
Leap scoring refers to the process of assigning value, typically in the form of a number “points,” to each lead you create for your business. You can score leads according to a variety of attributes, including the professional information that they’ve given you and how they’ve engaged with your website and brand online. This method aids sales and marketing teams prioritize leads, handle them appropriately, and increase the rate at which leads eventually become customers.
Every company has a different system for assigning points to their leads, but one of the most used ways is using data from past leads to develop the value system.
How? First, take a look at your contacts who were customers to see what they have in common. Then, you’ll examine the characteristics of your contacts that didn’t become customers. After looking at the historical information from both sides, you’ll be able to determine which of the attributes should be heavily weighted depending on the likelihood they will be a sign of a person’s suitability for your service.
Lead scoring sounds easy, right? Based on the business model you’re using and the leads stored in your database, this can quickly become a bit complicated. To make the procedure a little simpler for us, we’ll walk you through the basics of making a lead score, including the types of data you need to look over in order to determine the most significant attributes and the process for actually creating a simple score.
Lead Scoring Models
Lead scoring models will ensure that the numbers the lead is assigned reflect the actual compatibility they have for your service. Many lead scores are based on a range of points from between 0 and 100. However each model you design will reflect an individual characteristic of your primary customer.
Here are six lead scoring models based on the type of data you can collect from the individuals who are involved with your company
1. Demographic Information
Are you selling to people of a certain age group, such as parents of children in the early years or CIOs? Answer questions about demographics on form on the landing pages you’ve created, and you can then utilize your leads’ answers to see how well they are a part of your intended audience.
One way to use this information is to remove those who aren’t in your sales team’s queue by removing points for people who belong to an area you don’t sell to. In the case of example, if you sell only to a specific geographical area then you could assign an unfavorable score to any lead that doesn’t belong to the city state zip code, country, and so on.
If some of your field fields aren’t required (like a phone number, for instance), then you also might award extra points to those who fill in those fields in exchange for.
2. Company Information
If you’re an B2B organization, are you more than interested in selling to businesses of a certain size or type? Are you more interested in B2B organizations or B2C companies? You can include questions like these on your landing page form, too, so you can offer points to leads that meet the criteria of your target audience and take points away from leads who aren’t at all what you’re searching for.
3. Online Behavior
How a prospect interacts your website can tell you how interested customers are in buying from you. Take a look at your leads who eventually become customers: Which offers did they download? How many offers did they download? What pages in addition to how manydid they visit on your website prior to becoming a customer?
Both the quantity and type of pages and forms are important. You might award higher leads scores to people who visited high-value sites (like price pages) or completed forms with high value (like demo requests). Additionally, you might award greater scores to leads who had 30 page views on your site in comparison to just three.
What about leads who have changed their behavior over time? If the lead has stopped coming to your website or downloading your offers and offers, they might not be interested anymore. You might take points away from leads who have stopped engaging with your website after specific time. How long -10-days, 30 days, 90 days is contingent on the sales cycle you typically follow.
4. Email Engagement
If someone has signed up to receive email from your business You don’t know how interested that person is in buying from you. The clickthrough and open rates in contrast will give you a much better idea of their level of interest. Your sales team will want to know who read every email in your lead nurturing sequence, or who has always clicked through your email promotions for offers. So, they can choose the leads that appear to be the most engaged. It is also possible to give an advantage to those who open important emails, like demo offers.
5. Social Engagement
How engaged a person is with your brand’s presence on social networks can also give you the idea on how interested they are. How many times did they click through on your brand’s Facebook and Twitter posts? What percentage of them retweeted or share those posts? If your target buyers are active on social media platforms and you are interested in awarding points to leads with specific Klout scores or numbers of followers.
6. Spam Detection
Not least, it’s possible to award negative points to those who submitted form on landing pages with a manner that might indicate they’re spam. For example, were your first and last name and/or the company’s name not capitalized? Did the lead fill in the form fields using four or more letters within the standard “QWERTY” wording side-by-side?
It’s also worth taking time to think about which types of email addresses your leads use compared to the emails of your customer base. If you’re selling to businesses, for example it is possible to disengage customers who have Gmail as well as a Yahoo! email address.
How Can You Determine What Matters Most?
There’s a lot of information to sort through. how do you determine the most important data? What should you ask your sales staff? Do you need to talk with your customers? Should you dig deeper into your data and run few reports?
We recommend the combination with all three. Customers, salespeople along with your data analytics report will assist you in determining which content is most valuable to convert leads into customers that will allow you to make sure you attach specific points to certain offers, emails, and so on.
Contact your sales team.
Sales reps are on the ground, communicating directly with leads who converted into customers as well as those who weren’t. They usually be pretty aware of what pieces of marketing material helps encourage conversion.
What blog posts and offers do your sales reps like to distribute leads? You may find some of them telling you “Every whenever I send someone this certain piece of collateral, it’s easier to close the deal.” This is important information. Find out what those collateral items are and assign points accordingly.
Speak to your customers.
While your salespeople may say that certain content is effective in converting customers, you could find that the people who completed the sales procedure have different opinions. That’s fine. You’re interested to hear about it from both sides.
Conduct a few customer interviews to understand what they believe is the main reason they chose to purchase from you. Make sure that you’re talking to customers with short and long sales cycles, so that you can get different perspectives.
Turn to the analytics.
You should also complement all this in-person research with hard data from your analytics for marketing.
Run an attribution report to figure out which marketing efforts result in conversions across the funnel. Don’t only look at the content that converts leads to customers. What about the content that people consume before they’ve become leads? You may award a specific number of points for those who download content which has historically turned people into leads as well as a higher amount of points to those who download content that has historically transformed people into customers.
Another method to help you make sense of the valuable information on your website is to run a report. A contacts report will show you the number of contactsand also how much revenue produced as a result of specific marketing actions. Marketing activities can include offers downloads, emails campaign clickthroughs, and so on. Keep track of what activities tend to be first-touch conversions, last-touch conversions as well as others, and assign points accordingly.
Does One Lead Score suffice?
If you have one core client at present it’s enough to get a single score. But as your company scales it will be selling to different customers. You could expand into new products, new areas and even create new personas. You could even be focusing more on cross-selling and up-selling to your existing customers rather than seeking new ones. If your contacts aren’t “one size will fit all” your scoring system shouldn’t either.
In some platforms for marketing allow you to set up different lead scoring systems that give you the option of evaluating various sets of contacts in different ways. Unsure of how to create different scores? Here are a few ideas to get you started:
Fit vs. Interest
For instance, your sales team wants to analyze customers based on the quality and fit (i.e. is a customer in the right area? The appropriate industry? The proper job?) and their level of interest (e.g. how interested have they been with your online and content?). If these factors are important to you and you want to create both an engagement score and a score for fit, so you can determine which outreach to send to contacts whose values are good in both categories.
Multiple Personas
Say you’re a software company that sells two types of software through different sales teams, to various kinds of buyers. You could create two different lead scores, one to determine a buyer’s suitability and the other based on their attraction to each of the tools. This would allow you to use the individual scores to guide leads to the correct sales teams.
New Business as opposed to. Up-sell
As you gain experience and expand, you could begin to concentrate on up-sells or cross-sell more often as new businesses. However, keep in mind that the signals that indicate high-quality prospects as well as existing customers often look completely different.
For prospects, you might examine demographics and site engagement. For current customers, you could take a look at the number of customer support tickets they’ve submitted or their involvement with an onboarding consultant as well as how engaged they currently are with your products. If these buying signals look different in different sales, think about creating several lead scores.
There are numerous ways to determine a lead score. The most straightforward way to do it is:
Manual Lead Scoring
1. Determine the conversion rate of lead-to-customer for all your leads.
The conversion rate for your leads to customers is the ratio of the amount of brand new customers that earn multiplied by the number of leads you generate. Make this conversion rate your benchmark.
2. Choose and select different attributes customers who you believe were better quality leads.
Customers could have wanted to try a trial for free at some point, or customers from the finance industry, or customers with 10-20 employees.
There’s a particular art in choosing the aspects to include in your model. The attributes you choose will be from the conversations you had in your team with sales, the analytics, and so on — but overall, it’s a judgment call. Five different people perform the same task and develop five different scenarios. However, that’s fine as you make sure that your score is dependent on the information we discussed previously.
3. Calculate the individual closing rates of each of those aspects.
The calculation of the closing rates for every kind of action an individual performs on your site or the kind of person taking that action is crucial because it dictates the steps you’ll take as a response.
Then, you can figure out how many people are suitable leads (and ultimately, customers) based on the actions they make or the position they’re in relation to your primary customer. These close rates will be used to actually “score” your leads during the next step.
4. Compare the close rates of each attribute with your overall close rate, and assign points accordingly.
Look for the attributes with closed rates greater than your overall close rate. Select which attributes to assign points to, and If so, how many points. The point value of each attribute based on the size of their individual close rates.
The actual values of points may be somewhat random however, try to be as consistent as you can. If, for instance, your overall closing rate is 1% and you’re “requested demo” close rate is 20 percent, then the closing rates of the “requested demo” attribute is 20X your overall close rate -which means you can, for instance, award lead with 20 points with those attributes.
Logistic Regression Lead Scoring
The simple method, above, for calculating a lead score is a good beginning. However, the most mathematically sound option is one that utilizes an approach to data mining that includes logistic regression.
Data mining methods are more complex and are often more logical to your actual close rates in the end. Logistic regression involves building an equation in Excel that’ll spit out the odds of a lead turning to becoming a customer. It’s more precise than the technique we’ve outlined in the previous paragraphs because it’s a comprehensive method that considers the way in which all the characteristics of a customer — including size of company, industry, and whether or not the person requested a trialare interconnected.
Predictive Lead Scoring
Creating a lead score can make a big difference to your business: improve lead-handoff processes, increase the rate of lead conversion and increase productivity of reps, and many more. However, as you observe from the two approaches above, coming up with the right scoring system could be an extremely time-consuming process when it is done by hand.
Additionally, formulating scoring criteria isn’t “set to forget.” In the event that you get the feedback of your staff and test your scores, you’ll need to modify your lead-scoring system on a frequent basis to ensure it’s accurate. Wouldn’t it be easier to eliminate the manual setup and continuous tweaking out, leaving your team more time to develop relationships with your clients?
This is where predictive scoring comes in. Predictive scoring employs machine learning in order to sift through thousands of data points in order to determine your most promising leads, so you don’t have to. Predictive scoring examines the information your customers share and also what information the leads that did not close share and develops a the formula to sort your contacts according to importance according to their likelihood to be customers. This enables your sales team and you to rank leads so that you’re not contacting people who aren’t (yet) engaged and engaging those who are.
The best part about predictive scoring? As with any application using machine-learning, your predicted score will become more accurate over time, so your lead following-up strategy will be optimized.
