The Intentional Lead Scoring Workbook

The Intentional

Lead Scoring

Workbook

Leads are a

double-edged sword.

Yep. You read that right.

While most blogs, articles, and consultants tell you

that lead collection is critical for your business to

survive (and it is), there’s also a dark side to collecting

leads that’s not often discussed:

Leads can be an incredible waste of time if they’re not

genuinely qualied or in-market for your product or service.

Despite our best hopes, not everyone who downloads an

eBook or registers for a webinar is fully interested or able to

buy your product or service, and passing all of these leads

through to sales can easily overwhelm them, leading to

burnout or distrust of future leads.

At its worst, all of this extra activity can distract sales from

the accounts and leads who are most likely to convert, which

can directly impact your bottom line.

All leads aren’t created equal.

It’s clear that we need a method to determine which leads

are most likely to buy, so we don’t spend all of our time

on customers who are just window shopping. That’s where

lead scoring comes in.

At its most basic level, lead scoring is the practice of

assigning a score to each lead to help dene its priority over

other leads and to determine when the lead is ready to be

contacted by sales. While it may sound overly simplistic, lead

scoring can oer huge benets to sales teams.

With a quality lead scoring process, sales can:

l Tell at a glance which leads have the highest level of interest

(without having to compile dozens of data points from

dierent sources).

l Get a more informed view of how a particular lead has

interacted with the business and the actions that they’ve taken

so far.

l Align better with marketing on a clear denition of when a lead

is qualied and ready to be passed o from marketing to sales.

l Better personalize and meet customers where they are based

on their demonstrated level of interest.

Despite the many benets for sales, lead scoring is often

seen as purely a marketing function (after all, it’s built into

most major marketing automation platforms like HubSpot and

Marketo), but developing your lead scoring rubric in a vacuum

apart from sales can be a recipe for failure.

Sales will have to work with the output of the lead scoring

model, so it’s important that they contribute to the logic that

makes the model work eectively.

Your salespeople have gained a wealth of knowledge and experience from seeing

deals close rsthand; therefore, their participation in helping you set up your

lead scoring model will ensure it’s accounting for all of those sales insights and

best practices you can only learn from the eld.

To encourage cooperation and reduce friction, you need to ask good questions

and frame them in a way that sales will understand and see the benet in

answering.

Here are a few examples of eective, sales-focused questions:

1. From your experience, which actions taken by

prospects lead to the best meetings?

2. Have you noticed any trends in specic prospect

activity that often lead to less productive/“I’m not

ready yet” conversations?

3. Have you found that prospects from specic

industries or company structures are quicker to hop

on a call than others?

Lack of budget

Yes

Misplaced authority

Uncertain timeline for transaction urgency

Unsure of product/service needs

Not enough information to respond

Other:

Open your

worksheet to

get started!

Fill in your

personalized

responses

How to use Sales for

ecient lead ltering

Let’s build an eective lead

scoring system!

This workbook will walk you through the four critical steps

you need to build a comprehensive lead scoring model that

will keep your sales team happy and your pipeline full of

engaged leads!

Let’s go!

Ready to get started with your

lead scoring program?

Use this worksheet template

Lead Scoring Step 1:

Explicit scoring with demographic

and rmographic data

Your product or service isn’t a perfect t for everyone—

and this is a good thing.

This means, without much eort, you can easily categorize

leads based on how well they align with your ideal customer’s

demographic and rmographic attributes.

For this rst step, work with sales to determine the most

critical demographic and rmographic data that coincides

with your ideal customer prole (ICP) and then assign scoring

related to the magnitude of each of those key attributes.

Working at the account level? No sweat! Lead scoring is also

eective in account-based strategies.

With this data in hand, you’re already one big step closer to

sparing sales from unqualied leads and delivering leads with

a higher probability of conversion!

Demographic data

includes personal customer

attributes such as title, role,

purchasing authority, number

of direct reports, and years in

current position.

Firmographic data

consists of business attributes

such as geographic region,

type of organization, industry,

technologies used, number of

employees, and revenue.

Key individual—specic

demographic data

Title

Purchasing authority

Role

Level of seniority

Industry of expertise

Designations/certications

Public recommendations

Career interests

Years at current position

Social network participation

Aliations—groups

and associations

Personal interests

associations

Key company—specic

rmographic data

Number of employees

Revenue growth

(growing declining)

Company revenue

Rankings

Number of products sold or

subscribers

Headquarters or satellite

Location

Year founded

Geographic market served

Partners

Web trac

Organizational structure

Competitors

Fiscal year end

Industry

Explicit data checklist

Here’s a great starting point

to begin your explicit scoring

activity.

Do you have all the right pieces?

Your explicit lead scoring worksheet

Check out the example in the sheet.

Now it’s your turn!

Your explicit scoring list

Attribute Score Example

Lead Scoring Step 2: Implicit scoring

with rst-party Intent data

Ok, now we can rank our leads based on how well they t

the right demographic and rmographic attributes, but this

doesn’t tell us anything about their actual level of interest.

This is where your Implicit (or rst-party Intent)

data comes in.

First-party Intent data includes the actions that your lead

takes that you can directly measure from your own MAP

and integrations.

Examples of these actions include:

Content conversions (e.g. eBook and

industry report downloads)

Webinar/event registrations

Free trial registrations

Email opens and clicks

Page views

Chatbot conversations

Social media engagement

Hand raisers (e.g. contact us and demo

request form submissions)

Use dierent scoring tiers to award more points to eBooks,

webinars, and other content directly relevant to your

business/product, and fewer points to more generic or

“industry-related” content.

3 Don’t award singular email opens and clicks too heavily.

Someone may open an email or two but still not be

highly interested—Wait until a lead has reached a higher

frequency of opens and clicks (i.e. 5+) before assigning a

slightly higher score.

◦ Opens are more passive than clicks, so weigh each

action accordingly.

Passively looking at a webpage shows less interest than

watching a webinar or signing up for a product demo, so it’s

important that you weigh your scoring relative to the level of

interest each action demonstrates.

As an example, the table below compares actions with lower,

passive interest to those with higher, active interest for several

content types:

l Not all page views are created equally, so don’t rate every page view

the same. Assign more points for views of specic product or pricing

pages and for the number of page views per lead.

l Don’t forget social media! Award points to leads if they follow your

organization on social (especially if they’re following on multiple

channels) and if they’re actively engaging with your posts and content

(e.g. comments, likes, shares).

l The greatest amount of points should be applied for direct requests

for contact and demos.

Check out this pre-lled example

of key implicit attributes

Now it’s your turn!

Your implicit lead scoring worksheet

Your implicit scoring list

Activity Score Example

Lead Scoring Step 3:

Comprehensive scoring with

third-party Intent data

Rarely does one person make an important corporate

purchase by him or herself. In fact, Gartner research has

found that “the typical buying group for a complex B2B

solution involves 6 to 10 decision-makers,” and this number

has been increasing year over year.

While there will most likely be several people on the buying

committee, with each role needing their own individual

messaging, only one of them may score high enough to break

through the MQL barrier—leaving the rest to be ignored.

Incorporating Intent data into your lead scoring model will

help ensure that you capture all of the members of the buying

committee at any particular account, and you can implement

it in 2 easy steps:

1. Note which accounts are most

actively researching your

organization, product, competitors,

and/or topic clusters on your

Bombora Company Surge

report.

2. Boost leads from the above

accounts with enough points

to surface them to sales.

Scoring attribute Score Examples

Combined research activity across an entire account is

something you can’t aord to miss, as a spike in research

activity from a potential prospect is a very solid buying sign.

Curious about how Bombora’s Co-op is lled with only

privacy-compliant Intent data? Here’s how:

Fill in who your

main competitors are

Check out this

pre-lled

example

Name 3 topics,

verticals, industries or

categories your best

customers are in

Active intent signals

Bombora’s Intent data is gathered from the B2B ecosystem across multiple content sources

Real world B2B activity

Making the scale of this Intent data unparalleled—globally

Company Surge

data identifies when businesses are actively

researching products or services signaling buying intent.

Listening to an average

of 3.2M unique domains

Across an average of

694 B2B devices

Researching on

9,000+ B2B topics

White papers Case studies Search Registration

Ethically-sourced Intent data

It is used to produce Company Surge® data

*Figures for Q2 2021 (average of monthly figures from April to June)

Lead Scoring Step 4:

Implement score decay and

negative scoring

Un-qualify leads? Are you serious?

Yep. Situations change, buying windows close, and even the

best leads can become ineective over time. When it comes

to keeping your leads clean, maintaining a pile of stale leads

in the system can be just as bad as if you didn’t score them at

all.

In addition to deducting points for leads who don’t meet

the demographic and rmographic data, implementing score

decay over time can help ensure you’re delivering your MQLs

to sales while they’re still fresh.

Here are a few situations for which you should score

negatively or implement score decay:

Deduct points for any prospects who don’t

align with the rmographic or demographic

data of your Ideal Customer Prole (e.g.

remove points if the account is in an industry

you can’t or don’t want to sell to)

Remove the associated points for attending a

webinar or downloading an eBook after 30-60

days, as this lead has probably cooled down

If individuals opt out of outreach/sales

enablement sequences, this is a denite sign

to remove signicant points (You may also

want to deduct some points if leads opt-out

of marketing emails)

If sales are able to disqualify a lead in your

system, ensure that this is reected with a

large point deduction as well

Remove points for entry-level job titles if

they’re not part of your ICP

Deduct points for associated leads 20-30 days

after their account stops showing high intent

signals

Check out

this pre-lled

example

Now it’s your

turn!

Point Deductions

The bottom line is that the level of interest of your leads

changes over time, so your lead scoring system needs to

reect this as well.

Removing stale leads is the best way to ensure your sales

teams are spending their limited time most eectively—

approaching the leads who are most active and most likely

to convert.

Regardless of how much data you have access to, it’s great to be

proactive in building your lead scoring model! If you’re only set

up to reach step 1 or step 2 with your current stack, no worries!

Revisiting your lead scoring model is essential to building and

optimizing your program. Working your way through each stage

is essential to an eective lead scoring model, and the best of us

haven’t started at stage 4!

Using

first-party data:

engagement,

demographic,

and firmographic

data only

Using third-party

Intent data, one

tight Intent topic

cluster, applying to

your lead or account

scoring model

Using multiple

topic clusters or

third-party sources

that signal different

buying stages or

levels of interest

and score them

differently

(for example,

G2’s data)

Deploying a

sophisticated, predictive

scoring system that

includes both lead and

account scores and

activity, as well as more

advanced predictive

models

(or start using a

platform like 6sense

or Demandbase

that does this work

for you)

Stage

The lead scoring maturity curve

Curious about proven lead

scoring results with Intent data?

CLIENT

CHALLENGE

DESIRED LEAD

EVENT

PERFORMANCE

Turtl needed to create

and expand their SDR call

lists based on data-backed

insights versus anecdotal

sales feedback.

Booking a meeting

with the SDR team

After only four months of using

Company Surge

for HubSpot, Turtl

booked over 40 sales meetings and

increased its meeting creation rate by

more than 300%.

Snowake identied the

need for Intent-backed

insights to prioritize high

t accounts with the right

value propositions to

execute its personalized

ABM plan.

Increase in research

activity for several

Intent topics identied

for further analysis by

an internal ABM pod

The ABM pod identied a target

account that showed a signicant

increase in research activity and

through coordinated marketing and

sales outreach, the prospect engaged

with Snowake’s AE team which led to

a new deal closing in 3 months.

Kazoo’s legacy proprietary

t model, failed to show

an increase in conversion

rates for high scoring

accounts compared to

lower scoring accounts.

Qualied email

responses

When Kazoo used Company Surge

scores as a prioritization mechanism,

they saw 2–3x reply rates compared to

not using the data.

Learn more

Get results like this

Read the full story

BONUS Lead Scoring Step 5:

Periodic auditing and optimization

Following the previous four steps will ensure you have a solid starting

point for your lead scoring model, but it’s nearly impossible to get your

model 100% tuned on the rst try. We’d be remiss if we didn’t mention the

importance of periodic audits and optimization of your model.

Maybe you get access to new or more sophisticated data?

Maybe you want to add new content buckets or your ICP has changed?

Or maybe sales has just noticed that the leads just aren’t up to snu?

You should proactively set up meetings at regular intervals to assess the

output of your model so you can make any necessary changes to ensure it’s

still delivering the quality leads you expect.

Bringing it all together

We’ve come a long way from where we started—

In this workbook, we’ve helped demonstrate the

importance of and methods for:

1. Vetting leads against the rmographic and demographic

data of our target customers

2. Implementing weighted scoring from the direct actions

our customers are taking with our content

3. Surfacing whole buying committee by cross-referencing

Intent data with our raw lead data, and

4. Removing stale leads after their window of interest has

faded.

5. Given you a lead scoring worksheet to get started on

your lead scoring journey!

...but now the real work of talking to sales and

determining the right scores for each

action begins.

Bombora tells businesses which accounts are researching their products and services. With this

understanding, sales and marketing teams can be more relevant and consistent and improve

performance across all activities. This Intent-driven approach revolutionizes the way businesses

market and sell to other businesses through transparent data built on an ecosystem of quality,

collaboration and innovation. With direct integrations with dozens of leading data and media-

buying platforms, Bombora is building a world in which business buyers value sales and

marketing for its relevance, timeliness and accuracy. To learn more, visit bombora.com.