Lead scoring is a very effective model that helps marketing and sales teams to accurately identify which prospects are potentially most valuable to the organization and its current sales as well. However, a lead scoring model only works when it is used on a regular basis after its proper setup. Else, it poses the risk of being a waste of sales and marketing’s resources and time.
It can be hard to decide which leads your sales and marketing teams should be giving the most attention to, even with a clearly defined ideal customer profile (ICP). When executing campaigns, reaching out to leads with relevant messages already takes a lot of time. So, the last thing you want to do is spend more time on figuring out which leads to select for your campaign. Luckily, you can make sure the right leads are prioritized automatically with the right tech intelligence embedded in your CRM or MAP.
Going beyond typical and more general lead scoring criteria like demographics, behavioural and firmographic data, technology intelligence enables you to get in-depth insights on your leads. With the help of technology intelligence, you can dig deep and prioritize leads based on their technology footprint.
For example, you can segment your leads based on whether they are a late or early adopter of SaaS applications, whether they are using a competing or complementary technology product to yours, and whether they are using legacy or obsolete products.
This valuable and unique knowledge enables you to better understand your audience and reach out to them with a message that is much more likely to respond as it directly addresses their pain points. Additionally, with the right leads prioritized, it makes it much easier to deliver more marketing qualified leads (MQLs), create better marketing and sales alignment, and convert leads to sales.
What is Lead Scoring and Prioritization?
Lead scoring is a very effective model that helps marketing and sales teams to accurately identify which prospects are potentially most valuable to the organization and its current sales as well. However, a lead scoring model only works when it is used on a regular basis after its proper set up. Else, it poses the risk of being a waste of sales and marketing’s resources and time.
Lead scoring is basically a technique or method for quantifying the expected value of a prospect or a lead based on the prospect’s behavior (online and/or offline), profile, demographics, and likelihood to purchase. The score in lead scoring method is used to prioritize and articulate the potential value of leads for sales and marketing; allowing each function to maximize the effectiveness by sending high priority leads to the sales team and low priority leads in nurturing campaigns. Lead scoring attributes are both implicit (based on behavior) and explicit (through the prospects own input- surveys, forms, etc.) in nature, and usually require a combination of offline and online inputs.
How lead scoring works:
- For each action a lead takes in the sales funnel, they earn points.
- Each action has a point value.
- Once a lead reaches a specific point total, they are considered a hot prospect
Lead Scoring Actions May Include:
- Which pages do they view?
- The pricing page will have a higher value
- A career page will lower their score
- What does lead search for
- Their searches show their priorities and interests
- Specific downloads can indicate where a lead is the buying cycle
- Don’t assign points for every email open
- Look at submissions, click-through, or page views generated from the email
- Which landing pages do they visit?
- Which product or services are they interested in?
- What part of the funnel is the landing page in?
- Show what a lead’s pain points are
- The custom links your leads click can show where they are in their customer journey
- Give a good indication of topics of interest
- Can also show where they are in the funnel
Proper Lead Scoring Setup:
Lead scoring actually has the potential to generate more sales for the organization when implemented correctly. Unfortunately, there are a lot of lead scoring models out there that aren’t set up correctly, which results in sales funnel dropouts, poor conversion rates, or customers who stop considering your company for the solution they want to purchase. And you may easily prevent your customers from becoming interested enough to hear what your sales professionals have to say by contacting them too early in the sales process.
You must decide the action that determines a lead shift from interest to intent, in order to properly score them in the sales funnel. This action clearly shows that a lead has moved from the research phase, which includes actions like reading a blog post or watching a webinar, to the next part of the sales funnel, where actions include signing up for a free trial, completing a specific form, or asking for a price quote.
The customer information can be sent directly to a sales representative when the customer does something to trigger the particular action. This can be done quite easily when your marketing and sales teams use integrated platforms that have a lead scoring module. Instead of manually combing downloaded reports or contact forms for contact information, this automation makes it much easier for a sales representative to know exactly who to reach out to on any given day.
An effective lead scoring module makes it much easier for the sales team to determine their top prospects; however, those prospects wouldn’t be coming in if it wasn’t for the advertising and marketing teams doing their part to fill the sales funnel with potential prospects. This is why it’s very critical for marketing and sales teams to work together to determine the following:
- What makes a top prospect?
- What type of content or campaign most drive top prospects into the sales funnel?
Lead scoring can increase closing rates 30%, but this only works if marketing and sales collaborate on what drives leads most effectively, according to Douglas Burdett in his post “How B2B Marketers Can Use Lead Scoring to Better Arm Sales.” (link: https://www.salesartillery.com/blog/bid/151610/How-B2B-Marketers-Can-Use-Lead-Scoring-to-Better-Arm-Sales)And one of the most effective ways to collaborate is to work in a cycle: based on the sales team’s current experience and data, they can tell the marketing team which customers close most often. This helps the marketing team to identify where to focus most of their efforts. For example, if your sales team finds that a customer closes at a much faster rate after they download a price sheet, then the marketing team can channel their campaign and content towards getting more downloads for the price sheet.
Based on the hesitations or the questions sales team hear from prospects, they can also help the marketing team to identify key insights. And if the marketing team can create more proactive content that explains concepts, answers questions, or clears up confusion before the customer ever gets to the intent stage, it may actually help the sales team to close customers more often. Obviously, this information is beneficial to the marketing team as well: it helps them to refine their strategy by knowing exactly what to focus on.
Best Practices for your Lead Scoring Model:
Use negative scoring and score degradation
- Helps weed out people who visit your website but actually aren’t the leads, like content writers and job seekers
Set up separate lead scoring models for different solutions
Establish a lead scoring threshold
- Use an automation rule that automatically sends a lead to sales when they reach a certain score
Customize your lead scoring model based on high-value actions and webpages
- Be specific when assigning scores
Use the right actions
The sales team can close more leads once the marketing team has honed its focus and developed content around what generates the most deals, thus leading to good feedback and increased profit for all teams.
Predictive Lead Scoring:
Once your well-organized lead scoring module is in place, and the collaboration between marketing and sales has reached a decent stride, it may be a good time to focus more on predictive lead scoring that is fueled by artificial intelligence (AI). It is an algorithm-based approach to the lead scoring module. Based on the purchase and behavioral data of your customers AI will learn patterns, and then it predicts when a customer will make a purchase.
From data and experience, traditional lead scoring depends on people in your marketing and sales teams to determine which customers to focus on. Predictive lead scoring does the calculations and research for them automatically. Equipped with AI and a lot of data, this technology takes the platform so most companies that use predictive lead scoring have thousands of customers and hence enough information to make the algorithm as accurate as possible.
Although, if you have enough data and inconsistencies or see gaps with your traditional lead scoring model, it may be a good time to try predictive lead scoring to know if it is more accurate and can also help your sales team improve conversion rate.
Predictive Lead Scoring Differs from Traditional Lead Scoring:
The predictive lead scoring module uses a larger volume of data
- New information collected as it’s created
- Historical trends
- Information from big data sources that help you predict lead quality based ion other businesses in your industry
Compares your previous and current customers to automatically build the profile of a qualified lead
- Adjusts with new information
Leads are automatically scored against the profile of your qualified list
- Identifies leads for you who are most likely to convert to customers
Predictive Lead Scoring Regular Use:
Lead scoring systems are only as successful as the frequency in which they are used, as with any technology or system. Your sales team will get the most out of their lead scoring module if they use it daily to determine which prospects to focus on. However, if they don’t, and sales representatives start contacting leads who are still in the research or interest phase, very likely, they aren’t going to see as high of a conversion rate. In turn, this can affect sales projections or company profits.
And the same goes for your marketing team as well. If they don’t depend on regular feedback and communication from your sales team, especially in terms of how their marketing efforts impact the number of qualified leads that comes in, they have very little understanding of how their efforts are performing.
You can easily ensure that the resources and efforts needed to implement lead scoring process and metric helps your marketing and sales teams become more efficient simply by making lead scoring an integral part of your marketing and sale teams.
Predictive Lead Scoring Regular Maintenance:
Regularly scheduled maintenance and review of the lead scoring system along with regular use is crucial to its success. Marketing and sales teams should regularly analyze the following to determine what is still effective:
- Are the lead generation forms easy to use?
- Is there any required information (like a lead’s job title or phone number) that isn’t used by the sales team and could be removed to make it easier to complete the form?
Parts of the Sales Funnel
- Is the sales funnel still the same as it was when it was last analyzed?
- Is there a new action, part, or tool, like an online demonstration or free tool that needs to be added?
- Has your data shown any changes in buying patterns or funnel path? For example, if more customers start converting from webinars, the sales team may need to focus more on reaching out to webinar attendees after the event is over.
- Are you analyzing the right actions and metrics?
Look at your existing sales funnels, lead scoring module, and multi-departmental collaboration on a regular basis. With proper action and analysis, you can easily ensure that your sales team gets the most qualified prospects, which will then likely close at a much higher rate.
Popular Lead Scoring & Prioritization Use Cases:
You can easily ensure that your sales and marketing teams stay focused on pursuing the leads that generate the most revenue, by using technology intelligence to automatically score and prioritize your leads based on your ICP.
The following are the most successful lead scoring and prioritization use cases that customers have implemented using technology intelligence:
Score and prioritize leads that use a technology product you enhance, and reach out to them with your value proposition
Boost scoring for leads using competitor hardware or software products and then target them with a message that shows how your product solves their problems
Know the complete technology environment of your leads and prioritize those that are using legacy products to your marketing and sales teams for automated outreach
Case Study: Lead Scoring & Prioritization in Action
Alfresco was actively looking for a way to prioritize their accounts in a more efficient way. So that their marketing and sales efforts were more aligned and so they could achieve the best results. Alfresco increased engagement rates by 75% for their online ad program after using technology intelligence to score their leads, while reducing their cost per lead by 50%.