Why score marketing leads?

Scoring marketing leads is not an easy task. However, a little bit of effort will take your marketing and business to a different level. It is a growth hack that you cannot ignore.

Written By Anil Kumar P.

On August 12, 2022

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Anil brings immense value to the digital marketing space as a techno-marketer with 30+ years of experience. He understands both eco-systems – technology and marketing. Digital marketing is the love of his life & he has been pursuing it for over 20 years. His other interests areas are Artificial Intelligence, Expert Systems, Sustainable Technology and Coding.

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Read time: 7 minutes

Achieving monthly targets for marketing or sales teams is difficult and tough. Scoring marketing leads and then re-scoring by sales can work very well to achieve targets in a smarter way. Identifying and prioritising leads to chase is the first step to getting there.

Why score marketing leads?

Every business is unique, and each has its own lead scoring system. Scoring marketing leads is not entirely a scientific process, it is an unknown blend of experience and data. Experience is a variable, however, having accurate data can help you score the leads efficiently. Smarter scores are workable and yield results. The process of scoring marketing leads changes depending on the digital marketing trends.

Lead score is usually a number that, normally expressed in percentage of chances of making the sale. Once you have a few leads in your marketing pipeline, score each one based on a set of pre-determined metrics. This will not only help pass valid leads to sales but also give you insights into what leads you are generating and how you can tweak the marketing process to attract better leads. This cyclic process will help you get better at the game with time.

Marketing lead scoring

Marketing lead scoring can be simple or complicated depending on your domain and business goals. Looking at old data and analysing successful buyer journeys and their persona is a very important aspect of lead scoring. Most businesses do not take this into consideration, when considered your lead scores can change drastically and the process can be simplified and accurately executed.

Step 1: Choose scoring variables

Scoring marketing leads involves understanding of your visitors. Create an average audience profile that resonates the characteristics of your average customer. Categorise by profession – do they run their own businesses or are they salaried? What is their domain? What are their actions before making a purchase – free trials, sampling? Take a feedback from sales and analyse the basis of their conversion to customers.

Normally, scoring marketing leads depends on the following variables:

  • Industry – Depending on your product or service, which domains or industries do you cater to? Get data from sales, analyse it and sort them by industry, calculate the percentage of conversion domain-wise. Use this data as a basis for analysing leads in the current pipeline.
  • Business size – Which size of businesses or customers working in those businesses gets you a higher conversion rate? SMBs Vs enterprise businesses is a big touchpoint to score your leads.
  • B2B – If your products or services are B2B, who approved the purchase from the client’s end? A C-Club executive, a VP, a manager or the purchase department? This analysis will give you accurate data on target oriented marketing.
  • Website – As the owner of the website, the marketing team needs to identify pre-purchase activity. Scoring marketing leads here will also depend on free-trial customers or visits to pricing pages, etc. If you can analyse and execute search intent optimisation (https://efficaci.us/search-intent-optimization-a-complete-guide/), it will give you fantastic results.

All touchpoints or factors that identify your high converting customers are called “segments”or “variables” in marketing lead scoring jargon. They do not have barriers and are interchangeable. Once you have these segments or variables in place in your entire marketing funnel, the next step is to find out the value of these leads.

Step 2: Analyse average conversion rates

Once you are done with marketing lead scoring for all leads in the funnel, you can use the following methods to calculate the conversion rates and the lead yield.

Conversion rate – Conversion rate is a simple ratio between the number of conversions or deals and the total leads. The formula:

(# of deals or conversions / Toal leads) * 100

Lead yield – This is the ratio between the total revenue from closed deals and the total leads. The formula:

Total revenue from deals / Total # of leads

Once you are done with these calculations, prioritising the conversion rate of lead yield will depend upon your business goals and the pricing models. For example, if you run a subscription-based revue model, conversion rates are very important because you are getting long-term customers and their value increases. If you are selling white goods, lead yield is a prioritised metric because you are doing onetime deals and onetime price is the only revenue.

Once this prioritisation is done, it is time to delve deeper into your lead behaviour and fine tune it.

Step 3: Compare your data

Once you are done with the ratios, how do you know if they are good or bad? It is always important to compare them with your old data. To do that, calculate the same for all your customers over a period (1 year data should be good enough). This will give you the conversion rates and lead yields for an average customer. Compare the present data (probably for the last 30 days or a month) with the average customer data. This insight is very critical to marketing lead scoring.

Scoring marketing leads

For example, if your lead conversion rate is 20% for the last year and your present funnel segment is averaging 5%, the lead score assigned should be low.

Step 4: Assign lead score to variables and segments

Scoring marketing leads depends on the how the present data on a particular segment compares to your old data. Many businesses use a scale of 1 to 10. However, if you are looking for precision, expanding the scale to 1 to 100 will be a good idea.

Scoring marketing leads

Having keys within the score will enhance your consistency in marketing lead scoring. Use a point system, for example, a 10% lead score could be equal to 2 points and so on. A larger scale will be more precise for now and for future analysis.

Step 5: Evaluate leads

Once you have the list of attributes (as in Step 1) and lead scores, use them to evaluate leads in the funnel, one by one. Although many CRMs make a good job of lead scoring, a manual evaluation will give you more insights. Once you do this 5 or 6 times, the differences between a CRM evaluation and yours will be transparent and you can only expect so much from a CRM. This data will be useful to enhance your experience of marketing lead scoring and fortify your perspective on the differences.

Add up the attribute scores for each prospect in the funnel and create a list. You will have a much clearer perspective on the leads you are generating and this data can help tweak your marketing strategy and the sales pitches used.

Lead scores in marketing strategy

Once you have a first-hand experience in marketing lead scoring and understand the conversion attributes for your business and domain, you will gain insights into new marketing opportunities.

Scoring marketing leads

These could include better targeted marketing, targeted landing pages, targeting newly found segments and variables. This will help identify and prospect for high-scoring customers on the right channels.

These insights will also help recreate targeted email marketing campaigns month on month. When the outreach is better targeted, results are not far away.


Marketing lead scoring helps marketers target the right customers and get a higher value for their efforts. However, marketing and sales need to work in tandem here and tread the thin red line between them with care. 

Make this process a part of your digital marketing strategy. After all, a cohesive business is always more efficient than not.

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