Chapter 4
Why Should Marketing Care
About Sales Data?
In many B2B organizations, the marketing team has their data, the
sales team has their data, and the two sets rarely overlap. Why would
there ever need to be cross-over?
Marketing should care about sales data because the sales data
holds the ultimate measure of success: revenue. When marketing
can connect their efforts to revenue, they no longer have to report on
activity metrics or even engagement metrics. They can report on
their impact on true business value, which helps them achieve credi-
bility within the organization. It also helps them be more effective in
their efforts because they are optimizing for the right outcome.
At the proverbial table, instead of saying, “This month 500 people
filled out forms on our website,” which doesn’t mean much, the
marketing team can now say, “This month we contributed to 20 new
customers, which accounts for $10,000 in monthly revenue.” It’s a
much stronger statement.
Furthermore, the marketing team can say, “These three pieces of
content contributed to 50% of our new monthly revenue — let’s
create more content like that.” When marketing has access to sales
data, they can measure and optimize their efforts based on what
really matters — creating business value — rather than focusing on
top-of-the-funnel engagement metrics.
Without that final row of information, any marketer would
conclude that Blog Post A was more successful and that she should
write more content like that, instead of Blog Post B. But with that final
piece — the sales data — it’s clear that Blog Post B was more effec-
tive. When optimizing content, marketers need to optimize for reve-
nue first, and they need sales data to do that.
From the perspective of the organization as a whole, having
marketers measuring their success with sales data means that the
marketing team and the sales team are speaking the same language
— marketing is meeting the sales team on their turf. This alignment
makes the company as a whole more effective, as both teams know
they are receiving the fair credit that they are due.
The 2015 State of Pipeline Marketing Report, a survey of over
300 B2B marketers, found a correlation between organizational
alignment and marketing ROI. The study found that marketers who
reported ROIs of greater than 1.5x were more likely to perceive their
alignment with Sales to be ‘tightly aligned.’ Marketers who reported
returns of less than 50 cents on the dollar were more likely to report
being ‘seldomly aligned’ with their sales team.
And finally, from the customer’s perspective, when potential
buyers engage with your company, they are not thinking about what
department they are engaging with — it’s all one and the same to
them. Their experience should be seamless, whether the marketing
team or the sales team is interacting with them. When marketing and
sales are working together, they are able to deliver a consistent
customer experience, which makes for a more efficient and effective
funnel.
Now that you know that marketing does, in fact, have a strong
need to connect to sales data, how do you do it?
Chapter 5
How Does Attribution Connect
Marketing and Sales Data?
Marketing attribution solutions connect marketing and sales data by
tracking and collecting customer data from the very first interaction
with any marketing channel all the way down to the final purchase
data, which is held in the CRM.
For B2B organizations, at the very minimum, this means
connecting data from marketing channels like AdWords and Linke-
dIn, to website data, and then to the CRM. In doing so, ads can be
tracked all the way to downstream metrics, like opportunities and
revenue.
There are three main components involved in connecting
marketing data to sales data:
1. Tracking traffic from marketing channels — this is
usually done through UTM parameters
2. Using on-site JavaScript to track visitor behavior on your
website
3. Integrating with the CRM to connect on-site behavior to
sales data
Tracking Traffic from Your Marketing Channels
UTM parameters are tags attached to the end of a URL, allowing
marketers to track web source traffic. Here are some common UTM
parameters:
• utm_medium= (insert channel medium, e.g. search, social,
email, display)
• utm_source= (insert specific channel source, e.g. adwords,
bing)
• utm_campaign= (insert campaign name)
• utm_content= (insert content name, e.g. ad title, ad
dimensions)
• utm_term= (insert more specific term, e.g. paid search
keyword)
For example, a LinkedIn ad for our AdWords ebook guide may have
the following parameters:
• utm_medium=social
• utm_source=linkedin
• utm_campaign=content-adwords-ebook
• utm_content=adwords-strategies
• utm_term=adwords-ebook-200x400
In practice, the URL would look like this:
bizible.com/?utm_source=linkedin&utm_medium=social&ut
m_term=adwords%20strategies&utm_content=adwords%2
0ebook%20200x400&utm_campaign=content%20adwords
%20ebook
A good attribution system does some of this work for you.
Because it is integrated to your website through on-site JavaScript
(more on this in a bit), a lot of this information can be pulled automat-
ically through referral analysis.
UTM parameters, however, give marketers the ability to deter-
mine what specific marketing effort drove a person to their website.
That’s why UTM parameters are particularly important for tracking
paid media efforts.
From there, marketers are able to follow their actions on-site,
thanks to a line of JavaScript code (also called a JavaScript snippet).
On-Site JavaScript
All web analytics (such as Google Analytics) use a JavaScript snip-
pet to track on-site behavior. It tells them what pages web visitors are
navigating to, what buttons they click on, and even what forms they
are filling out.
Because form fills (how leads are created) are so important in
B2B marketing, on-site behavior is a crucial element of understand-
ing the customer journey. Web analytics answers questions like,
“When a visitor reads Blog Post X, do they bounce or do they visit an
ebook download landing page?”
Going a step further, the analytics that marketing automation
solutions offer is great at answering questions like, “When a visitor
reads Blog Post X, do they go on to fill out a form and become a lead?
Or, ”When they watch the product video, do they go on to request a
live demo?” Basically, it tells you whether your content is driving lead
creation.
These are huge transitions in the customer journey and are
important for marketers to track. But again, this alone covers just the
top and middle of the funnel. We’re not at the all-important stuff yet.
Understanding customer behavior on your website isn’t particu-
larly actionable if you don’t understand how it influences the next
step in the customer journey. And that requires integrating that
marketing data with sales data in the CRM.
CRM Integration
The final step in connecting marketing data to sales data is
integrating web activity data with your customer relationship man-
agement software, more familiarly known as the CRM. The CRM
houses your pipeline information. While your marketing automation
software may track and house lead information, your CRM houses all
the information from qualified leads to sales opportunities and
closed-won deals.
Putting It All Together
So with these three steps — tracking with UTM parameters,
on-site JavaScript, and CRM integration — marketers are able to track
how specific marketing initiatives (e.g. a LinkedIn ad for an ebook) got
someone to fill out a form on their website (e.g. to download the
ebook), and then continued to become a customer down the road
(e.g. after several great conversations with a sales rep, they decided
that the product solved their needs and became a customer).
While there is software that builds and organizes UTM parame-
ters, other software that does web analytics, even more software
that does channel analytics, and still more software that focuses on
lead creation, a marketing attribution solution does all of this and
does it in a single place. This centralization is important.
It’s a common belief that marketers can hack together an attribu-
tion system themselves, using a combination of inexpensive or
included web and channel analytics, plus some Excel expertise. If you
have limited marketing channels and are spending hundreds or
maybe a couple thousand dollars on paid advertising a month, then
hacking something satisfactory is probably achievable. However, if
you’re investing any significant amount, a hacked solution will not
suffice. That’s because there’s still the problem of decentralization.
When you hack together spreadsheets of channel-specific data,
such as Facebook Insights reports or LinkedIn Ads Campaign Manag-
er reports, the attribution data for each marketing channel is siloed
separately, which creates the challenge of double-counting credit.
For example, if a visitor clicks on an AdWords ad on Monday, a Face-
book ad on Wednesday, and then buys something for $100 on Friday,
both your AdWords data and your Facebook data will claim 100%
conversion credit. That’s because they don’t communicate with each
other. When you bring both data sources into your spreadsheet and
associate that conversion with its $100 value, your report will show
$200 of revenue — 2x your actual revenue — a big, and potentially
embarrassing, problem.
As you can see, if you’re using multiple marketing channels with
regularity, a single source of attribution data is necessary for accu-
racy and reliability.
B2B Marketing Attribution 101