What is lead scoring?

Lead scor­ing is all about assign­ing val­ue to dif­fer­ent poten­tial customers.

It’s a method­ol­o­gy that ranks some leads above oth­ers in terms of how valu­able they could be to businesses.

Lead scor­ing is used by busi­ness­es to eval­u­ate and rank poten­tial cus­tomers (leads) based on their like­li­hood of becom­ing pay­ing cus­tomers. Each lead is analysed for cer­tain cri­te­ria (e.g., behav­iour, demo­graph­ic, and engage­ment) and assigned a val­ue or score based on these factors.

Lead scor­ing can help busi­ness­es focus their sales and mar­ket­ing efforts by high­light­ing which leads are most like­ly to con­vert due to their appar­ent engage­ment or inter­est lev­els. Ulti­mate­ly, this process allows for more effi­cient use of resources and can ulti­mate­ly lead to increased sales and revenue.

There are numer­ous oth­er ben­e­fits to lead scor­ing, which we’ll delve into below. This arti­cle will also explore the var­i­ous ways busi­ness­es can con­duct lead scor­ing, as well as some dos and don’ts.

Let’s get started.

Why should I start lead scoring?

Once your busi­ness starts imple­ment­ing lead scor­ing, you can expect to see the fol­low­ing results:

Better prioritisation of sales and marketing efforts

As men­tioned above, lead scor­ing helps busi­ness­es iden­ti­fy the most promis­ing leads. This helps them focus their sales and mar­ket­ing resources on those indi­vid­u­als who are most like­ly to make a pur­chase, ulti­mate­ly sav­ing time and mon­ey by avoid­ing wast­ed efforts on leads that are less like­ly to convert.

Improved ROI

By stream­lin­ing their resources on the most promis­ing leads, busi­ness­es often see increas­es in their return on invest­ment (ROI) for sales and mar­ket­ing efforts. In fact, organ­i­sa­tions using lead scor­ing expe­ri­ence a 77% increase in lead gen­er­a­tion ROI.

Improved lead conversion rates

Busi­ness­es using lead scor­ing also see increased con­ver­sion rates (CR). By focus­ing on leads that are most like­ly to con­vert, a high­er per­cent­age of those tar­get­ed will ulti­mate­ly become pay­ing cus­tomers. A boost­ed CR also means that busi­ness­es are spend­ing less time, mon­ey, and ener­gy on lead gen­er­a­tion.

More personalised communication

A key com­po­nent of lead scor­ing is under­stand­ing the needs and pref­er­ences of indi­vid­ual leads, allow­ing busi­ness­es to com­mu­ni­cate with cus­tomers in a more per­son­alised and rel­e­vant way. This is known to build stronger rela­tion­ships with cus­tomers and increase the chances of con­vert­ing them to pay­ing customers.

Increased customer satisfaction

Since lead scor­ing means that B2C com­mu­ni­ca­tion is bet­ter tai­lored to the spe­cif­ic needs of indi­vid­ual leads, busi­ness­es can see boost­ed cus­tomer sat­is­fac­tion lev­els. This is because cus­tomers feel that a busi­ness under­stands their needs and pref­er­ences, which can encour­age them to rec­om­mend the brand to friends and become repeat customers.

Over­all, con­duct­ing lead scor­ing can pro­vide sig­nif­i­cant ben­e­fits for busi­ness­es by help­ing them to bet­ter under­stand their cus­tomers and focus their resources on the most promis­ing opportunities.

If you’re con­vinced and want to kick start a lead scor­ing cam­paign, read on to learn how you can do so:

How do businesses conduct lead scoring?

Lead scor­ing is typ­i­cal­ly con­duct­ed with a com­bi­na­tion of auto­mat­ed tools and human analy­sis. Here are the steps typ­i­cal­ly involved in the process:

1. Determine which data is important to your business

Busi­ness­es first need to deter­mine the cri­te­ria that are most rel­e­vant to their spe­cif­ic goals. Doing this will help iden­ti­fy which data is rel­e­vant to their lead scor­ing efforts because it will inform the fac­tors that leads will be scored on.

For exam­ple, the online behav­iour of web­site vis­i­tors could be real­ly impor­tant to an e‑commerce busi­ness, while a local busi­ness could be more inter­est­ed in loca­tion data. These cri­te­ria will then inform scor­ing in that users who engage more with a web­site will receive a high score and leads that live out­side a catch­ment area will receive a low or neg­a­tive score.

Here are some oth­er exam­ples of data that could form the basis of your lead scor­ing efforts:

• Demo­graph­ic infor­ma­tion (e.g., age, gen­der, location)
• Com­pa­ny infor­ma­tion (e.g., if B2B, industry)
• Online behav­iour (e.g., web­pages vis­it­ed, down­loads, forms filled, pur­chase and brows­ing history)
• Email and social media behav­iour (e.g., open rates, click­through rates, shares, likes, fol­lows, retweets)

Lead scor­ing typ­i­cal­ly involves a com­bi­na­tion of both explic­it (infor­ma­tion pro­vid­ed by the lead) and implic­it data (gath­ered through the lead­’s behav­iour), so don’t feel pres­sured to pick just one.

If you’re not sure which data will be most impor­tant to your lead scor­ing efforts, you can get help by involv­ing your sales team in the dis­cus­sion, con­duct­ing cus­tomer sur­veys, and look­ing at cus­tomer-acqui­si­tion data reports.

Your sales team and cus­tomers will know lots about the sales process and, there­fore, what was and was­n’t effec­tive in dri­ving sales. Plus, your ana­lyt­ics report will give con­crete answers to ques­tions regard­ing con­ver­sion and help iden­ti­fy the most com­mon traits among con­vert­ing customers.

2. Create a value range

Once the cri­te­ria are iden­ti­fied, each one is assigned a val­ue range. For exam­ple, if mul­ti­ple pur­chas­es are an impor­tant fac­tor for your busi­ness, you’ll cre­ate a cor­re­spond­ing range. In this instance, you might set up your val­ue range like this:

1 pur­chase = 10 points, 2 pur­chas­es = 20 points, 3 pur­chas­es = 30 points, and so on.

You might cre­ate a mul­ti­fac­eted val­ue range based on sev­er­al fac­tors. For instance:

Fill­ing a form = 10 points, mail­ing list sign-up = 15 points, vis­it­ing a high-val­ue page = 20 points

There are count­less ways you could set up your val­ue ranges. Just make sure that high points are only award­ed to fac­tors that are proven to be valu­able to your busi­ness and that points are award­ed pro­por­tion­ate­ly in accor­dance with your con­ver­sion analytics.

For instance, if users that signed up to your mail­ing list proved to be more valu­able than those who just made an account with your e‑commerce site, don’t award the lat­ter more points.

3. Score your leads

Using the cri­te­ria and ranges you have estab­lished, it’s time to score each lead accord­ing to their behav­iour and char­ac­ter­is­tics. This can be done using an auto­mat­ed lead scor­ing tool that aggre­gates data from var­i­ous sources, or it can be done man­u­al­ly by a sales or mar­ket­ing team member.

For large datasets, an auto­mat­ed tool is most effi­cient, and it will sync up with your CRM soft­ware so every­thing’s in one place.

4. Start prioritising leads

Once leads have been scored, you can start pri­ori­tis­ing them. The leads with the high­est scores are typ­i­cal­ly giv­en the most atten­tion and resources, as they are con­sid­ered to be the most like­ly to con­vert to pay­ing customers.

A great way to cel­e­brate your new lead scor­ing efforts would be to launch a high­ly tar­get­ed email mar­ket­ing cam­paign on your small­er but more qual­i­fied list of leads. Or you might just car­ry on with your sales and mar­ket­ing efforts but trim down the list of peo­ple you intend to reach out to.

5. Adjust your criteria and scoring as time goes on

Over time, busi­ness­es may need to adjust their lead scor­ing cri­te­ria and val­ue ranges based on changes to their goals, cus­tomer behav­iour, or the state of the mar­ket. By doing so, they can remain rel­e­vant and in tune with cus­tomers even as things evolve. We rec­om­mend eval­u­at­ing your lead scor­ing process if sales or con­ver­sions sud­den­ly take a down­ward turn or if you open up a new mar­ket­ing chan­nel (e.g., cre­ate a com­pa­ny social media account).

Different lead scoring models

Depend­ing on their spe­cif­ic needs and goals, busi­ness­es can choose from a few dif­fer­ent lead scor­ing mod­els. Here are three to be aware of:

1. Rule-based model

The rule-based mod­el involves set­ting up a set of pre­de­fined rules to score leads. These rules can be based on var­i­ous cri­te­ria, such as those list­ed above.

This mod­el is use­ful for busi­ness­es that have a clear under­stand­ing of their ide­al cus­tomer pro­file and want to focus on those who meet spe­cif­ic cri­te­ria. How­ev­er, it’s lim­it­ed in its abil­i­ty to cap­ture com­plex rela­tion­ships between dif­fer­ent lead attributes.

2. Predictive model

The pre­dic­tive mod­el involves using machine learn­ing algo­rithms to analyse his­tor­i­cal data and pre­dict the like­li­hood of a lead converting.

This mod­el is par­tic­u­lar­ly use­ful for busi­ness­es that have large vol­umes of data and want to lever­age it to make more accu­rate pre­dic­tions. The mod­el can be trained to look for pat­terns in datasets that are indica­tive of a lead being more like­ly to con­vert and then use this infor­ma­tion to score leads.

3. Hybrid model

The hybrid mod­el is a com­bi­na­tion of both rule-based and pre­dic­tive mod­els. It involves set­ting up pre­de­fined rules as well as using machine learn­ing algo­rithms to iden­ti­fy pat­terns in the data.

This mod­el is use­ful for busi­ness­es that want to lever­age the ben­e­fits of both mod­els. They’ll like­ly have some pre­de­fined rules in place, such as the exam­ples list­ed in our “how-to” section.

Lead scoring Dos and Don’ts

If you’re going to embark on lead scor­ing for the first time, there are some things you’ll need to know. Here are our top dos and don’ts for lead scoring:

Don’t rely solely on one source of data

It’s impor­tant to con­sid­er mul­ti­ple sources of data when scor­ing leads. Rely­ing sole­ly on one type of data, such as demo­graph­ic or behav­iour­al, may result in an incom­plete pic­ture of each lead­’s poten­tial. Instead, make sure you com­bine the infor­ma­tion from both types for a more com­pre­hen­sive approach.

Don’t use subjective or arbitrary criteria

Lead scor­ing cri­te­ria should be based on objec­tive data that is mea­sur­able and rel­e­vant to your busi­ness goals. Using sub­jec­tive or arbi­trary cri­te­ria can lead to incon­sis­tent and inac­cu­rate lead scor­ing. Instead, the cri­te­ria used to score leads should be clear­ly defined from the very beginning.

Don’t set it and forget it

Lead scor­ing should be an ongo­ing process that is reg­u­lar­ly eval­u­at­ed and adjust­ed as need­ed. Set­ting the cri­te­ria and then nev­er revis­it­ing them can lead to an out­dat­ed and inef­fec­tive scor­ing methodology.

Don’t ignore negative scoring

Neg­a­tive scor­ing is a way to sub­tract points from a lead­’s score based on spe­cif­ic behav­iours or char­ac­ter­is­tics that indi­cate a low like­li­hood of conversion.

For exam­ple, it might be used to indi­cate an inac­tive mail­ing list sub­scriber. If you’re going to embark on a lead scor­ing strat­e­gy, it would be a good idea to imple­ment neg­a­tive scor­ing to cre­ate the most accu­rate pic­ture of your leads.

Don’t segregate your sales and marketing teams

Lead scor­ing should be a col­lab­o­ra­tive effort between sales and mar­ket­ing teams. This will ensure that the scor­ing method­ol­o­gy devel­oped aligns with both teams’ goals and pro­fes­sion­al opin­ions. Plus, uni­ty between these teams will ensure the smooth-run­ning devel­op­ment and imple­men­ta­tion of lead scoring.

Don’t neglect the human element

While auto­mat­ed tools can be help­ful for lead scor­ing, it’s impor­tant to involve human analy­sis and inter­pre­ta­tion as well. Human input can pro­vide con­text, nuance, and expe­ri­ence that auto­mat­ed tools may miss. So, make sure you ask your sales and mar­ket­ing teams for their opin­ions when eval­u­at­ing the most effec­tive con­ver­sion and lead nur­tur­ing techniques.

Final thoughts

Lead scor­ing can seem like a lot of work. But the pay­off can be invaluable.

To make things eas­i­er for you, we rec­om­mend that you use tech­nol­o­gy as much as pos­si­ble to help with the more com­pli­cat­ed aspects of con­fig­ur­ing and analysing data. How­ev­er, don’t for­get to ask the mem­bers of your team who under­stand the sales jour­ney best for their pro­fes­sion­al opinions.

As there can be a lot of data to con­sid­er, it’s easy to focus too much on a sin­gle cri­te­ri­on. It’s impor­tant, though, that busi­ness­es try to under­stand how dif­fer­ent fac­tors can inter­link and devel­op a lead scor­ing process that allows for this.

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