Sales Growth Services: Sales Lead Scoring Made Simple
Understanding lead scoring can help leverage a company's success and efficiency in following new leads.
Most leads don’t become customers; according to one study, the average conversion rate falls between 2 and 10 percent, depending on the industry. So how can you tell which leads are ready to pull the trigger, which need more time, and which you shouldn’t invest much time in nurturing?
Welcome to a process known as lead scoring.
Table of Contents:
- What Is Lead Scoring for Sales?
- Challenges Solved by Lead Scoring
- What Goes Into a Lead Score?
- Example of a Prospect Lead Score
- What’s a Perfect Score?
- Sales Lead Scoring Made Simple
- Lead scoring assigns a number to each sales lead. Usually, the higher the number, the closer the lead is to converting.
- Factors that go into a lead score include how close the lead is to your ideal customer and how good a fit your product is for their business.
- Lead scoring can be complicated, so it’s often done via technology.
- Lead scoring can help you raise sales closing rates, improve customer engagement, and streamline your sales cycle.
What Is Lead Scoring for Sales?
Because time is always a precious commodity, it’s important to prioritize hot leads (who are ready to buy). You also want to spend time cultivating warm leads (who show interest but aren’t quite at the buying stage yet). And you don’t want to spend much time chasing cold (i.e. uninterested and unproductive) leads.
Finally, you need to pace your communications to each group, taking care not to overwhelm warm leads with information that’s more suitable further along their buyer journey.
This is where lead scoring comes into play. According to HubSpot, “Lead scoring is the process of assigning values, often in the form of numerical ‘points’, to each lead you generate for the business. You can score your leads based on multiple attributes, including the professional information they've submitted to you and how they've engaged with your website and brand across the internet. This process helps sales and marketing teams prioritize leads, respond to them appropriately, and increase the rate at which those leads become customers.”
Challenges Solved by Lead Scoring
What Goes Into a Lead Score?
Before you tackle lead scoring for your sales team, you first need to understand your customers’ buying journey and who your ideal customer(s) are. You should also analyze your current clientele. What do they have in common? Try to find patterns in their behavior or attributes (such as industry, job role, company size, etc.).
Your actual lead scoring criteria is flexible and should be based on your company. It’s a good idea to get sales reps’ input on this, as they have an up-close view of what clients are looking for. Generally, lead scores will include at least some of the following information:
- Fit. How close is this lead to our ideal customer?
- Shared attributes, as discussed above.
- Need. How well does our offering(s) solve their problem?
- Firmographic information, i.e. company size, industry, etc. You can often get this information through your landing page (i.e. you request the info when the lead signs up for a free demo) or via publicly available sources.
- Job title or role. Do they have the authority to make a decision? Are they one of several decision makers? Or are they in a supportive role (e.g. assistant or admin)?
- Interest. Have they expressed interest in our company via website visits, social media behavior, phone calls, or other contacts?
- Contact history, e.g. all that person’s phone, email, social media, and website contacts with your organization.
- Timeline, e.g. older or newer lead, frequent or repeated website visits, etc.
Example of a Prospect Lead Score
Let’s look at the following example of lead scoring. Notice how the lead takes on certain attributes in the scoring model. As we learn more about the prospect's actions, we can build a model that reflects the perfect customer's needs. The more positive data we have for a lead, the more qualified that lead is for sales.
Here is an example of how you might score a lead:
- The prospect uses a form to download a lead magnet (i.e. the prospect converts). 100 points assigned.
- In that form, the prospect indicated they work for a small to medium business – the perfect sized company for your offerings. 1,000 points assigned.
- This lead is now on a nurture track and has opened 3 emails. 10 points assigned per email open, or 30 points total.
- This lead clicks on a link every email; 50 points each or 150 points total.
Final score = 1,280 points
What’s the Perfect Score?
Lead scores are designed to inform marketing whether this person is a marketing qualified lead (MQL, or not yet ready for sales), a sales qualified lead (SQL, or ready to send to the sales team) or maybe just not qualified at all (stop nurturing).
Today's marketing and sales teams usually agree on a Service Level Agreement (SLA). These agreements lay out the actions a lead must take to ultimately become a SQL. The perfect score is more about the value that the number represents.
Sales Lead Scoring Made Simple
If you’re thinking, “Wow, this lead scoring is a complicated business”, you’re absolutely right. Companies with dozens or hundreds of leads can quickly get drowned in all the data. That’s why lead scoring models have been developed – some of which rely on advanced computing techniques to sort through data. A few of the most common include:
Company information model. This considers how well the lead’s company fits your customer profile. Are they in your target geography, industry, or size? Do they focus on selling to businesses or to consumers? The closer they match your profile, the higher priority this lead becomes.
Need-based model. This flips the previous model around and asks “How well does my company fit this lead’s needs?” Again, the better the fit, the higher the priority.
Online behavior model. This looks at the customer’s interactions, primarily with your website. How often do they visit? What pages do they spend time on? Have they given you contact information or signed up for anything? The answers will give you a good idea of this lead’s level of interest.
Predictive scoring. This method relies on Artificial Intelligence to process all of the data points discussed above (and a lot more) and classify leads. These lead scoring mechanisms can be packaged with your CRM, or they can be part of another solution. Their main selling point is that they don't require much human oversight, which saves your team a lot of time. Plus, the sophisticated underlying programming can improve its own performance over time, which means they get more effective as you use them.
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