Traditional Lead Scoring vs Predictive Lead Scoring


Proficiency in inbound marketing helps you to attract a huge amount of leads. But once having plenty of leads you may face the challenge of separating the quality leads from those prospects who are not ready to buy your products or services yet. Lead scoring methods can help you to decide which leads will convert to customers by attaching scores to each of your leads based on their digital behaviour and information you know about them. There are two main types of lead scoring methods: traditional lead scoring and predictive lead scoring.

Traditional lead scoring

Traditional lead scoring is a process during which sales teams identify those criteria that determine lead quality, evaluate prospects and attribute a score based on established criteria. The resulting score helps sales teams to determine which leads are more likely to engage in buying and which of them will probably not become your customer. Two different kinds of information can help to deduce lead scores: explicit and implicit information. Explicit data is based on the information that prospects actually tell you, including their company email, budget, business title and area of work. Implicit data is implied from the digital behaviour of the prospect, such as clicking through emails, blog subscriptions and clicking or viewing various content in your website.

Sales teams use the collected explicit and implicit information to make up the score of each lead based on the established criteria. IBM developed a widely used set of criteria, called BANT, which includes:

Budget: How much money does the lead plans to spend on your products/ services?

Authority: Is your lead the decision maker?

Need: Does your leads’ company really need your products / services?

Timeline: How much time does your lead need to make the purchase decision?

In order to make as precise lead evaluation as possible, sales teams should add two more information categories: demographics and activities.

Demographics: Treat every lead as an individual person when you build profiles. Store and refresh every available information about your leads’ company including annual revenue and number of employees. It can be also important to collect data about past dealings and buying behaviour.

Activity: Collect as much information as possible about interaction history using home-grown systems and information from outside vendors to make your lead evaluation more reliable.

How does traditional lead scoring works?

You can set up a traditional lead scoring system in 3 steps.

  1. The first step is to determine the criteria of a quality lead using disposable explicit and implicit information. BANT is a widely used set of criteria but before using it think through whether BANT criteria fit your company. If not, do not be afraid to establish you own criteria. It is also advisable to talk with your sales teams and determine together those demographics, activities and behaviours which makes a lead more qualified than others.
  2. After establishing a set of criteria, the second step is to create a scale and a points system to assign values to the different criteria that makes a lead qualified.
  3. The last step is to determine a threshold score that indicates whether a lead is ready to purchase.

3 weakness of traditional lead scoring

  1. Traditional lead scoring systems use oversimplified models. These systems are only able to determine obviously bad leads but not effective enough to prioritize a huge amount of leads based on various criteria.
  2. Traditional lead scoring systems do not perform well in fast changing markets. In changing market conditions, companies should update the criteria that they use for lead scoring at least quarterly. However most companies update them less frequently. Consequently the applied lead scoring systems may mislead sales team, resulting in lower sales performance.
  3. Traditional lead scoring systems do not provide opportunities to sales teams to give feedbacks and incorporate them. Without the valuable feedback of sales teams, the company misses out on opportunities to improve lead scoring systems. Consequently, the company does not forego the opportunity to increase the number of sales.

Predictive lead scoring

Predictive lead scoring is a scientific method that determines lead quality and estimates the probability that a lead will buy. Predictive lead scoring is different from traditional lead scoring on 3 important factors:

  1. Predictive lead scoring methods use a huge amount of data: behavioural and historical data from CRM and marketing automation systems combined with “big data” collected from multiple sources. Predictive lead scoring systems collect information such as demographic details, marketing actions, company size, company revenue and social network activity.
  2. Predictive lead scoring methods use the available data to build the profile of a quality lead (sales ready lead).
  3. Predictive lead scoring methods score each of your lead against the quality lead to determine which of your leads will convert to customers.

How does it work?

  1. Find out what you know about your leads. Data, gained from your marketing and CRM systems, does not just deliver a valuable insight about your leads but also help to determine those mistakes that decrease the efficiency of your sales pipeline. The most common mistakes are:
  • Most companies use limited number of variables to create the profile of their leads. An average company uses 10 demographic variables, such as name, industry, revenue. That information is necessary but not sufficient to build a comprehensive profile.
  • Marketing databases outdate very quickly. At least 30% of the lead profiles outdate every year because they change jobs or the information about them are not valid any more.

In order to avoid these mistakes find out what information you need to create more credible lead profiles and ensure that the marketing and CRM databases are updated frequently.

  1. Add more information mined from the web. Review company websites, third party websites, press releases, social networks and job boards to find valuable information about financials, marketing and sales techniques, technologies and staff of you leads’ companies. These information contribute to create more comprehensive and punctual profiles about your leads.
  2. Apply predictive analytics. Predictive analytics assess you leads’ profiles and find your highest valued leads. After determining the profile of a sales ready lead, the predictive lead scoring systems compares your leads’ profile to that of the high value lead. This method help to identify which leads are likely to convert and on which leads sales team should not waste time.

3 important benefits of using predictive lead scoring

  1. Predictive lead scoring systems improves the efficiency of B2B sales and marketing. These systems analyse the leads’ behavioural patterns and help to determine those marketing actions which can improve the quality of leads, resulting in growing revenue from the already existing client base.
  2. Predictive lead scoring systems contribute to create content that meet the interest of your target audience. These systems create the individual profile of each lead which makes it possible for sales teams to create tailored messages and personalized content for their target audience.
  3. Predictive lead scoring systems help to keep your customers. These systems can identify not just those leads that are more likely to convert but also those customers that will probably leave. Consequently these lead scoring systems can determine which relationships you should nurture to avoid churn.

An effective but unrealized method

Despite the benefits of using predictive lead scoring, B2B organizations are just beginning to use predictive lead scoring systems. Based on the research of SiriusDecisions, 64% of the surveyed B2B organizations started to use predictive lead scoring less than a year ago, 24% of them have been applying predictive lead scoring for one to two years and only 5% of them have been using it from two to three years. Key findings of SiriusDecisions also included that mainly small and medium businesses adopted predictive lead scoring and most of them run in the High Tech industry. All of those companies, which began to use predictive lead scoring, evaluated this method as a useful tool to improve sales efficiency and 98% of the respondents said that they would buy and use predictive lead scoring again.


Why is predictive lead scoring better than traditional lead scoring?

Predictive lead scoring, compared to traditional lead scoring, helps you to build a more efficient sales pipeline in two ways:

  1. No more guesswork: In case of traditional lead scoring methods, criteria to evaluate leads are determined by guess and check method. It is possible to make highly educated guesses about which factors influence conversion but this process is difficult, slow and usually not satisfying. Predictive lead scoring uses statistical methods to give scientific result and evaluate your leads instantly. As a result the use of predictive lead scoring makes lead evaluation quicker, more effective and more reliable.
  2. Use of a huge amount of data: Traditional lead scoring uses the data of Marketing Automation and CRM systems. However, traditional lead soring methods only use a tiny subset of accessible data to get a picture of the prospects. In contrast to traditional lead scoring, predictive lead scoring uses thousands of data endpoints to create a comprehensive profile about each of your leads including financial data, job postings, social media activity, demographic data and much more.

All thing considered, both lead scoring methods can help to evaluate your leads but predictive lead scoring, compared to traditional lead scoring, can be a more effective tool for this purpose. Predictive lead scoring exceed traditional lead scoring as the former method use a huge amount of statistically proven information to score your leads instantly. Traditional lead scoring cannot provide the same benefits because this method relies on limited amount of data and does not automatize lead scoring that may result in outdated and misleading lead profiles.

If you are ready to benefit from the reliable result of predictive analytics that rely on a huge amount of data, you should sacrifice time and money to establish a predictive lead scoring system in your company. We can help you to reach this goal as we provide information about your prospects digital behavior by tracking and monitoring how engaged your prospects are with your content. Check those activities that you can monitor by using our services!

We hope that we gave a good insight into lead scoring methods and persuaded you that lead scoring, especially predictive lead scoring, is an efficient means to increase your sales performance.