Best Metrics to Optimize B2B Demand Gen

®
InsideUP
Best Metrics to Optimize
Your B2B Demand Gen Campaigns
B2B White Paper Series
© 2016-2019 InsideUp. All Rights Reserved.

Fuel Your Account Based Marketing
Success with Predictive Analytics
B2B marketers who need to do more than simply
create brand awareness through outbound marketing
have adopted Account Based Marketing (ABM) in
order to focus on key accounts. Successful ABM
campaigns can produce highly qualified, valuable
prospects.
According to ITSMA’s Account Based Marketing
Forum, 87% of companies claim that AMB produces a
higher ROI than any other form of marketing. ABM is
forecasted to be the primary market model for B2B
technology service providers in the next few years.
“It is my view that Account-Based Marketing (ABM) is
on the threshold of revolutionizing the market domain.”
- Professor Malcolm McDonald, Emeritus
Professor, Cranfield University School of
Management
But, like any new initiative, diligence is a constant
requirement.
“To make account-based marketing work…it’s
essential for all stakeholders to be involved in the
process,” said Brian Grubbs in a blog post for
Seismic. “Sales teams need to communicate which
accounts to target and why, content creators need to
determine proper messaging and positioning for every
target individual, and lead generation specialists need
to ensure they are focusing their campaigns in a
hyper-specific way.”
How We Got Here:
Technology’s Impact On B2B
Marketing
With access to countless resources and
tools, today’s B2B buyer is much better
equipped to make purchasing decisions.
According to a study by McKinsey, the
average B2B buyer will utilize six different
channels while researching solutions. And
nearly 65% will end up frustrated due to
inconsistent experiences.
Further complicating the buying process is
the fact that the average number of decision
makers involved in significant technology
purchases has grown from five to seven, an
IDC study found. And each of these
individuals will have their own approach to
the discovery and research process.
Hoping to meet decision makers on their
path to purchase, many marketers are
focusing on the “buyer journey.”
Unfortunately, this so-called journey is not
so easy to trace. The linear funnel model, or
“point A to point B” journey, has been
discredited recently due to the increase in
control exerted by B2B buyers over the
purchase process.
In a recent study by Forrester, 78% of
respondents agreed that their prospects’
buying journeys have become more
complex and nonlinear. Rather, once
buyers have become aware of a particular
need, they tend to “bounce around” in
search of answers.
The next step after downloading a white
paper, for instance, will not always be to
ask for a demo, as you might expect. Or a
buyer who reads a case study could be
pushed back into the awareness phase
after discovering that the solution they
thought they were looking for will create yet
another need.
© Copyright 2016-2019 Insideup, Inc. All Rights Reserved

Identify Best Accounts and
Personas to Target
To successfully target the right accounts, more is required than having access to data. In
fact, lack of data is no longer the problem it once was for many marketers.
What’s keeping marketers awake at night, as can be seen from the chart below, is how to
manage data from a wide variety of sources while ensuring the quality of that data.
As seen below, there are three main issues that are keeping marketers awake at night
1. Collaborating with the IT team to use big data
Currently, marketers are faced with a deluge of data—but an abundance of data doesn’t
ensure quality. To ensure the highest data quality, marketers have been using third party
organizations to analyze the data and extract the duds.
2. Integrating and translating big data points into useful insight
Managing data from a variety of sources is something easier said than done. Keeping all
information organized and relevant is a necessity for marketers.
3. Providing real-time insights to the business
Marketers need real-time, creative, and customer responsive apps and tools to ensure they
are able to deliver the right messages at the right time from the insights gleamed.
"AI-enabled analytics platforms provide the best customer acquisition and
retention success by automating much of the decision making around the signals
generated from all of this data, allowing the marketing organization to focus more
on strategy and less on tactical execution."
- Kevin Cunningham,
Chief Executive Officer, MRP

Implement Lead Scoring as Part of
Your Target
One way marketers can make the most of the data they have is to assign a score to each
lead. Lead scoring technology has been widely adopted by marketing organizations to
prioritize individual leads.
Lead scoring is vital for companies looking to better qualify leads and thereby increase
conversion rates. New research by Aberdeen reveals that using a system of lead scoring
produces lead qualification rates 192% higher than average.
An Eloqua study found that business service marketers who use lead scoring have 30%
higher closure rates, with closed deals bringing in an average of 17% more revenue per deal.
Detect Early Intent with Account
Scoring
Lead scoring works well in the traditional “funnel” model because every contact is considered
a “lead” located somewhere along a linear progression from “suspect” to BANT qualified
“prospect.” But to successfully execute account based marketing campaigns, another layer of
predictive analytics is needed.
To fuel the multiple touchpoints that characterize today’s B2B buying process, marketers need
to embrace the continual scoring of contact data - even the data that does not show any
recent intent.
This early detection technique improves upon the “shot-in-the-dark” marketing that now occurs
when a vendor is forced to churn through a list of contacts built by running a data extraction
against an in-house database (using a set of basic demographic parameters)-or worse, by
obtaining raw contacts from a data merchant.

Use Predictive Analytics to Identify
the Buying Stage of Target Accounts
While traditional scoring models are rules-based, using only behavioral and profile indicators
to predict conversion, predictive data scoring goes further by incorporating account-level
information, such as previous conversions, to produce a detailed and highly accurate picture
of each lead’s propensity to purchase.
“Data scoring” can happen continuously and is independent of traditional “lead scoring.” It
uses predictive modeling techniques that analyze data, recognize patterns and arrive at a
score based on well-defined attributes (such a data cleanliness, participation in a community
and past behavior in B2B purchasing activities).
Performing data scoring continuously is a reasonable supporting process to achieve what we
like to call Precision Account Based Marketing (PABM). This process can contribute in
advance of any dynamic lead scoring, which helps optimize a campaign once it starts.
Diligence in Marketing Means
Measurement
Predictive analytics are key to the effective use of ABM. By assessing the demographical
profile, online behavior, etc., of multiple contacts from the same company, marketers can
produce an “account score” that identifies “best-fit” accounts.
Dynamic, data-driven account scoring is essential in order to:
 prioritize accounts that already live in your CRM system, and
 better align sales and marketing in the process.
An account score should include all factors that could indicate propensity to buy, according to
Jeff Sands, ABM Practice Co-Lead, ITSMA. Sands also recommends targeting “companies
that are in a dynamic, growing market. It’s far more likely to turn into business than an account
in a shrinking market.”
Measuring results for ABM is relatively straightforward; in the end, you can simply calculate
the percentage of targeted accounts with which you have closed a sale. But to gauge your
progress toward that goal, here are some basic metrics for each stage:

Why Predictive Account Scoring is
Essential to ABM Success
We’ve all read the now legendary statistic from the Corporate Executive Board at Harvard
Business Review (HBR), which says that buyers are already 57% along in their journey before
contacting a sales rep. And each person in the decision making process will view the
purchase from their own angle. Targeted information is clearly needed to help these buyers
see why your offering is in their company’s best interest.
Predictive analytics can reveal intent from an enormous set of data points generated by online
activity across multiple channels. So now you can identify key pain points of the target
company as a whole while also noting the unique concerns of decision makers in their various
roles within the company.
Predictive account scoring provides a multi-faceted view of target accounts so that you can
better tailor your content and communications to the needs and pain points of, not only each
account, but also the decision makers and influencers that data scoring has helped you to
identify within that account.
Awareness
Website page
views
Impressions
Unique visits
Engagement
Content accessed
Number of page
views
Length of time
spent on each
page
Demand
Number of
marketing and
sales qualified
leads per
channel
“Predictive Marketers are 2.9x more likely to report revenue growth at rates higher
than the industry average.”
“Modeling and predicting specific outcomes helps Predictive Marketers execute
account-based marketing (ABM) strategies, enabling them to drive more buyer
engagement and, ultimately, increase revenue opportunities from target
accounts.”
How Predictive Marketing Analytics Boosts B2B Business - Forrester Consulting

Predictive Account Scoring Is More
Than Just Lead Scoring
Make no mistake; lead scoring is well established as a critical component of B2B demand
generation. Company size, industry vertical, and the prospect’s title and department are
always important considerations for lead scoring. And, according to Aberdeen Research,
companies that get lead scoring right have a 192% higher average lead qualification rate.
But the most precise methods of lead scoring incorporate buying signals such as past
behavior, type of content accessed, and amount of time to demonstrate intent, into the overall
lead score, based on conversion data.
Fresh intent data can prove invaluable as a gauge of the latest direction in the thoughts and
feelings of the coveted B2B account. Unfortunately, many companies do not know how to
build a predictable and reliable formula for incorporating behavioral and demographic data to
form lead scores, according to DemandGen Report.
According to Aberdeen Research, companies that get lead scoring right
have a 192% higher average lead qualification rate than those that do not.
Performance Metrics Average Performance
Best-in-class All others
Lead qualification rate
Forecast accuracy
Marketing effectiveness
Sales effectiveness
Lead conversion rate
Response rate
Pipeline thickness
35% 22%
32% 21%
31% 21%
30% 15%
28% 19%
27% 20%
27% 12%
An Aberdeen survey measured the change in key metrics after implementing lead
scoring. Best-in-class companies are those that reported, on average, the highest
increases in revenue growth, lead conversion rates and decrease in cost per lead.
Source: Aberdeen Group, Lead Scoring and Prioritization.

Overcoming challenges such as proving ROI/attribution and lead to account mapping require
a new generation of sophisticated lead and account scoring technology. Scoring
systems combine powerful analytic capabilities and the ability to deliver data-driven
insights. These systems can essentially, predict the future by analyzing the past and then
prescribe the most effective actions to achieve success.
As this chart from the 2017 ABM Benchmark Survey Report shows, identifying ideal accounts
is still a prevalent issue for marketing managers.

Predictive Analytics and Account
Based Marketing: An Ideal Pair
Research from SiriusDecisions found that increasing numbers of B2B marketers are adopting
predictive lead scoring. Using firmographic, demographic, and behavioral data from CRM and
marketing automation to reveal account-level characteristics and buying signals, predictive
lead scoring gives B2B marketers more detailed insights into which leads are the most likely
to convert.
However, based on the online research activity taking place outside your website, predictive
account scoring enables marketers to identify potential ideal fit accounts before those
accounts have already narrowed down their choices.
Predictive account scoring leverages intent proclivities to identify in advance your most likely
champions within potential target companies.
Optimized lead scoring also enables scalable data manipulation activities to fuel a steady
influx of new B2B marketing campaigns. This means not having to go into “panic mode”
whenever a new campaign requirement generates the need for access to fresh data.
Predictive Account Scoring is Only
the Beginning
The results of predictive account scoring are optimized by the distribution of tailored content
and customized account based nurturing. This is important because, according to Harvard
Business Review, “Individual customer stakeholders who perceived supplier content to be
tailored to their specific needs were 40% more willing to buy from that supplier than
stakeholders who didn’t.”
 Predictive analytics and enhanced lead targeting make it easier to identify decision
makers within companies that are more likely to have a need for and interest in your
solution.
 Sales and marketing teams can present prospects with the right content at the right time
to effectively guide buyers through the now non-linear and largely unpredictable buying
process.
 Insights gained through precision account based marketing practices enable consistency
of message at every potential touchpoint, channel, and level of intent in the nurturing
machinery.
Predictive account scoring can help you to identify, in advance, the individuals most likely to
be your advocates within a company, and to reach out with content relevant to each person’s
concerns. The ability to do this effectively is at the core of Precision Account Based Marketing.

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