When most people start implementing inbound marketing strategies, they’re mostly concerned about how to get enough new leads through the funnel.
However, once you’ve got several leads, you need to figure out who is really interested in your offering and who’s just starting to look around.
This is the point where lead scoring comes in.
What is Lead Scoring?
Lead scoring is the method of assigning value, typically in the form of numbers or “points,” to each lead that you generate for your company. You can score your leads using a variety attributes such as the professional information they’ve submitted to you and the way they’ve interacted through your website and brand online. This process assists marketing and sales teams prioritize leads, respond to them in a timely manner, and improve the rate at which those leads eventually become customers.
Every business has its own model for assigning points to score their leads, but one of the most popular methods is using data from past leads to create this value-based system.
How? In the beginning, take a look at the contacts who were customers to determine what they share. Then, you’ll examine the characteristics of your contacts who didn’t become customers. After you’ve reviewed the historical data from both sides you’ll have the ability to decide which aspects are worth weighing heavily depending on the likelihood they will show that a person is a good fit for your service.
Lead scoring sounds simple, right? Based on the business model you’re using and the leads stored in your database, this can quickly become complicated. To make this process a bit easier for you, we’ll guide you through the fundamentals of creating a lead score, which includes what information you should be looking at and how to identify the most important characteristics, and the process for actually creating a simple score.
Lead Scoring Models
Lead scoring models guarantee that the scores that you give to every lead reflect the real compatibility in relation to the product you offer. Most lead scores are based on a point range of between 0 and 100. However, each model you create will support a particular attribute of your core customer.
Here are six lead scoring models based on the type of data you can collect from the individuals who are involved with your business
1. Demographic Information
Are you only selling to people belonging to a particular age group, such as parents of children in the early years or CIOs? Answer questions about demographics on these forms you’ll find on landing pages, and you can then utilize your leads’ answers to see how well they fit in with the people you want to reach.
One thing you can do with this information is to remove outliers from your sales team’s queue by subtracting points for those who are in the same category that you don’t sell to. In the case of example, if you sell only to a specific geographical area, you might give the lead a negative score if it’s a leads that aren’t within the correct city state or zip code, and so on.
If certain form fields are merely optional (like the number of a phone, for instance) You might award extra points to those who fill in those fields in exchange for.
2. Company Information
If you’re a B2B organization, are you more looking to sell to organizations of a certain size or type? Are you more interested in B2B organisations or B2C organisations? You can ask questions like these on your landing page forms as well, to give points to leads that are in line with your ideal audience and take points away from leads that aren’t at all what you’re looking for.
3. Online Behavior
How leads interact with your site can reveal a lot about how interested they are in buying from you. Review your leads that ultimately become customers: Which offers have they downloaded? What number of offers did they download? What pages — and how many pages- did they visit on your site prior to becoming a customer?
Both the quantity and type of pages and forms are crucial. You could give higher lead scores to leads who visited high-value pages (like prices pages) or completed forms with high value (like an application for a demo). Similarly, you might give greater scores to leads who had 30 page visits on your site rather than three.
What about leads who have changed their behavior over time? If a lead has stopped visiting your website or downloading your offers, they may not be in the market anymore. You could take points from leads who have stopped engaging on your website after a specific time. The amount of time -10 days 30, 30 or 90 days — will vary based on the sales cycle you typically follow.
4. Engagement through Email
If someone’s opted in to receive email from your company however, you’re not certain what level of interest they have in buying products from you. Clickthrough and open rates however can provide you with more insight into their interest level. Your sales team needs to know who has opened each email in your lead nurturing series, or who was always clicking through your offer promotion emails. This way, they can choose the leads that appear to be the most engaged. It is also possible to give a higher lead score to people who click on important emails, like demo offers.
5. Social Engagement
How engaged a person is with your brand’s social networks will also give you the idea on how involved they are. How often did they browse your company’s tweets and Facebook posts? What percentage of them retweeted, retweet, or share the content? If your customers are active on social media Then you may want to consider giving points to leads who have certain Klout scores or numbers of followers.
6. Spam Detection
Not least, you may want to assign negative points to those who completed form on landing pages in ways that could indicate they’re not legitimate. For instance, was the your first and last name, or the company’s name not capitalized? Did the lead complete any form fields by typing the letters of four or more in the standard “QWERTY” keyword side-by-side?
It’s also worth taking time to look at the kinds of email addresses people use compared to the emails of your customer base. If you’re selling to companies like this you could take points away from prospects who have a Gmail or Yahoo! email address.
What Do You Know About What Matters Most?
This is a lot of information to weed through — what do you do to determine what data is most important? Should you seek out information from your sales team? Should you talk to your customers? Should you dig deeper into your data and run couple of reports?
Actually, we recommend an amalgamation between all three. The sales staff, the customers as well as your reports on analytics will all assist you in determining which material is most useful to convert leads into customers, which will help you connect certain aspects to specific offers emails, sales, and so on.
Ask your sales representatives.
Sales reps are those on the ground, communicating directly with leads who have turned into customers as well as those who didn’t. They usually have an idea of which pieces of materials can help in promoting conversion.
Which blog posts and special offers do your sales reps prefer to send leads? You may get some of them saying “Every time I send people this particular document, it’s easier to close them.” This is a valuable piece of information. Find out what those collateral items are and assign points based on that.
Talk to your customers.
While your sales team might claim that certain types of content convert customers, you could find that the people who actually completed the sales procedure are of different opinion. This is fine. You’re entitled to hear the story from both sides.
Do a few interviews with customers to learn what they think was a factor in their decision to buy from you. Make sure you’re speaking with customers with long and short sales cycles so you get diverse viewpoints.
Go to the analytics.
You must also supplement these in-person surveys with data from your analytics for marketing.
Do an attribution study to determine which marketing efforts can result in conversions through the funnel. Don’t just look at the content that converts leads into customers. What about the content that people consume before they become a lead? You might give a certain amount of points to those who download content that’s traditionally transformed leads into leads, and a higher number of points to people who download content that’s traditionally turned people into customers.
Another approach to put together useful pieces of content for your website is to run a contacts report. A contacts report will show the number of contactsand the amount of revenue — has been generated as a result of specific, targeted marketing actions. Marketing activities might include certain offer downloads, email campaign clickthroughs, and more. Take note of which activities are typically first-touch conversions, last-touch converts and so on, and then assign points accordingly.
Is One Lead Score Enough?
If you only have one primary customer right now one score is enough. But as your business expands it will be selling to different customers. You may expand into new products, new areas, or new personas. You might even focus more on up-selling and cross-selling to your existing customers rather than looking for new ones. If your relationships aren’t “one size will fit all” your scoring system shouldn’t be either.
In some platforms for marketing, you can create multiple lead-scoring systems, giving you the ability to score various sets of contacts in different ways. Not sure how to set up several scores? Here are a few examples to help you get started:
Fit vs. Interest
For instance, your sales team wants to assess customers based on suitability (i.e. is the contact located in the right area? The appropriate industry? The correct position?) and level of interest (e.g. how active have they been with your website and content?). When both characteristics are important to you then you can build both an engagement score and a score for fit, so you can focus your outreach to contacts whose values are good in both categories.
Multiple Personas
Let’s say you’re a business which sells two distinct types of software, with different sales teams, to different kinds of buyers. It is possible to create two different lead scores – one for buyer’s fit and the other for their attraction to each software. This would allow you to use the respective scores to route leads to the correct sales teams.
New Business as opposed to. Up-sell
As you get bigger in your business, you might begin to concentrate on up-sells or cross-sell as much as new businesses. Keep in mind those signals that signal the how well new prospects are doing and current customers can look different.
For potential customers, you can take a look at demographics or website engagement. For current customers, you might consider how many customer support tickets they’ve submitted as well as their interactions with an onboarding specialist and how engaged they currently are with your offerings. If these buy signals appear different for different sales, you might want to create multiple lead scores.
There are numerous methods to determine the lead score. The simplest way to do it is this:
Manual Lead Scoring
1. Determine the conversion rate of lead-to-customer for all your leads.
Your conversion rate from lead to customer is the sum of the amount of brand new customers that get multiplied by the number of leads that you generate. Make this conversion rate your standard.
2. Select and pick different attributes clients you believe to have been better quality leads.
Customers could have requested a free trial at some point in time, or customers from the finance industry, or customers who have 10-20 employees.
There’s a certain art to choosing which features to include in your model. It’s in light of the conversations with your sales team, your analytics, and so on — but all in all, it’s a judgement call. There’s a possibility that five people do the same exercise and develop five different models. However, that’s fine as you make sure that your score is basing on the data that we discussed previously.
3. Calculate the individual close rates of each of those attributes.
The calculation of the closing rates for each type of action an individual performs on your website — or the type of person doing the step — is essential since it will determine the actions you’ll take in response.
Then, you can figure out the percentage of people who become qualifiers for leads (and ultimately customers) by their actions or the position they’re in relation to your customer base. Then, you can use these close rates to actually “score” your leads during the next step.
4. Examine the close rates for each of the attributes with your overall close rate, and assign points accordingly.
Find attributes with closing rates substantially over your overall close rate. Choose which attributes to assign points to, and in the event that you do, how many points. You can base the points values of each attribute based on the size of their close rates.
The actual value of points will vary however, try to be as consistent as is possible. For example, if your overall close rate is 1%, and that your “requested demo” close rate is 20%, then the close ratio of the “requested demo” attribute is 20 times your overall close rate -therefore, you could, as an example, give twenty points for leads with these attributes.
Logistic Regression Lead Scoring
The simplest method, as mentioned above, to calculate the lead score can be a good start. However, the most scientifically sound method is one that uses a data mining technique that includes logistic regression.
The methods for data mining are more complex, and usually more intuitive than close rates than you actually have due to this. Logistic regression involves creating the formula in Excel that’ll spit out the likelihood that a lead will close to a client. It’s much more accurate than the method we’ve described previously since it’s an integrated approach that takes into account how the various characteristics of a customer — including the size of the business, its industry, and whether or not you requested a trialare interconnected.
Predictive Lead Scoring
Creating a lead score can be a huge benefit to your business. It can help improve lead-handoff processes, increase the rate of lead conversion as well as increase the productivity of reps and more. But, as you can see from the two methods above, coming up with the right scoring system could be laborious when completed manually.
Plus, coming up with scores isn’t “set the criteria and then forget about it.” In the event that you get the feedback of your staff members and evaluate your scores, you’ll need to tweak your lead scoring system on a regularly basis to ensure that accuracy. What to have technology take the manual process of setting up and continuously tweaking out, leaving your team with more time to build relationships with your customers?
That’s where predictive scoring comes in. Predictive scoring makes use of machine learning to parse through hundreds of data points in order to pinpoint your best prospects, so that you don’t have to. Predictive scoring analyzes what information your customers have in common and also what leads who didn’t close have in common and develops a a formula that sorts your contacts according to their likelihood to be customers. This allows your sales team and you to prioritize leads so you’re not contacting people who aren’t (yet) interested or engaging with the ones who do.
The greatest benefit of predictive scoring? Similar to any application that uses machine learning techniques, your predictive score gets smarter over time So your lead follow-up strategy will become more efficient.
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