For many marketing organizations, marketing qualified leads (MQLs) are entrenched as the holy grail of measurement and success. However, there is a new set of metrics quickly emerging as marketers continue to focus less on volume, and shift to more precise tactics around impacting and influencing targeted accounts and key buyers.
This often means that marketing teams are looking at new indicators and measures — such as account behavior, fit, deal velocity and more — to prioritize and engage the right prospects. The drive to show a more clear influence and impact on pipeline and revenue are also ushering in a new set of metrics, as B2B marketers look to gain more intelligence about real indications of purchase intent and future buying signals.
During the recent 2017 Buyers Insights & Intelligence Series, we saw several new metrics and approaches to measurement emerging, including post-click engagement data, account scores and engagement across key accounts.
Engagement Metrics: Counting Beyond Clicks
Historically, metrics such as shares, open and click-through rates and downloads have given marketers some preliminary insights about their campaigns. However, as marketers struggle with converting leads to opportunities, they realize the number or volume of clicks does not always tell the full story. Instead of simply looking at traditional based metrics, Elle Woulfe, VP of Marketing at LookBookHQ pointed out that more companies are now looking at post click engagement data.
“We’re just adding points together [based on clicks] and saying, ‘the volume of these activities must mean that that person is interested.’ But, unfortunately, your marketing automation platform can’t tell the difference between the people who are clicking on things,” said Elle Woulfe, VP of Marketing at LookBookHQ. “That’s why the number one metric that can help marketers to identify their most qualified buyers is [content] engagement. Not just ‘did they click on it; did they download it,’ but how much time did they spend with it.”
She pointed out that understanding how much time visitors spend on a page or session offers marketers and sales teams valuable information. Not only does it show at the visitor level who is engaging, it can also identify what accounts and content are getting the most engagement and how different channels are performing. “What people do on the destination side is more important than the click,” Woulfe added.
For example, Woulfe described a buyer who spent approximately three seconds on a piece of video content and didn’t spend any time in an accompanying PDF. Then he went to a blog post and immediately bounced from the page. This engagement may imply that the buyer is in the wrong place because he/she is not spending any meaningful time with the content.
On the other hand, if another buyer is clicking on all the same things but the intensity of the research is different — spent a minute on the video, spent three minutes on a PDF, etc. — he/she is spending meaningful time trying to get the info they need. “This is the real buyer,” Woulfe said. “But marketing automation on its own can’t tell the difference.”
Using post-click engagement data, Woulfe pointed out that clients have been able to identify real buyers who are more likely to convert. Several use cases Woulfe shared showed prospects who were binging on content moving through the funnel at 2.3x greater velocity than other buyers, and they represented 2.4x higher average customer value.
Account Scores Helping To Determine “Fit”
Another strategic shift that is leading to a changing set of metrics is the move to account-based strategies.
As part of this shift, many practitioners are using a mix of internal and external data points to identify “fit,” or accounts that have similar qualities to that of their ideal customer.
Dropbox, for example, created an account prioritization model, called a “Priori Score,” that is designed to help gain deeper knowledge of prospective accounts, prioritize outbound initiatives and convert accounts that are currently on the free version of their product to paying customers.
“We get to think about sales in a very data-driven way by using high-level, anonymous usage insights to tell us the kinds of behaviors that are taking place within companies that use our product,” said Christopher Noon, Head of Data Science for Outbound and Channel Sales at Dropbox.
Noon highlighted that the score was formulated from two factors:
- Internal measurement of prospective customers’ usage of their product. This includes the number of files a company has stored on Dropbox, the total amount of storage space and the total number of licenses owned by users within a target account. The higher the level of engagement within the account, the higher the chances of converting into a paid customer.
- External signals gathered through the help of Lattice Engines. This includes the account’s tech stack profile, online presence, the account’s website keywords and more.
The scoring system was on a 0-100 model for both Dropbox’s internal measurement and Lattice’s external measurement. Both scores are then used to plot accounts on a grid broken into four sections called “priorities.”
The highest scoring accounts were slotted into Priority One (the top-right quadrant), where marketing and sales were to spend a majority of their time and effort. Accounts scored into Priority Two and Three were targeted with more nurturing content to drive more engagement and increase their scores. Tier four accounts were to be “avoided unless opportunities exist,” according to Noon.
“This ultimately helps account reps easily understand where their priorities are at a glance — based partly on the model that we built and partly on the deals they’ve closed themselves in the past,” said Noon. “They can zoom into this graph and find accounts with similar scores to those who later became customers.”
This paid off well for Dropbox, with 78% of the tier one accounts becoming closed/won deals.
Tying Metrics To Marketing Impact & Influence
In addition to using new metrics to identify and prioritize most likely buyers, B2B marketers are also looking to provide better analysis of marketing’s influence and impact on different campaigns and stages of the buying cycle.
Dayna Rothman, VP of Marketing and Sales Development at BrightFunnel, pointed out that many marketing teams are starting to look at source attribution as a new metric, which helps identify lead origination rates and track which channels produce the most leads, helping them better understand their campaign performance from various sources.
She added that understanding source attribution is also valuable from a cost perspective, as it helps teams measure the cost effectiveness of source leads, and determine which campaigns to prioritize or retool.
“This analysis, along with regular communication with the sales team, helps makes sure everyone knows what marketing is doing, how it can impact sales and where they can benefit from marketing’s efforts,” said Rothman.
To understand marketing’s impact on pipeline and revenue, Rothman said best-in-class practitioners are now looking at metrics such as:
- Last activity before created opportunity;
- Velocity of specific campaigns by measuring the number of days it took a lead to become an opportunity and opportunities to become deals;
- Percentage of accounts engaged within your Total Addressable Market; and
- Full-funnel view of top engaged accounts.
For example, Rothman stated if a content syndication program takes 15 days to get from a lead to opportunity, but then the time it takes to go from opportunity takes 30 days, it doesn’t necessarily mean that it isn’t a good program. “Instead, this helps me understand that I can run other programs in conjunction with this syndication program to help accelerate that velocity over time,” she said. “Also, if I need quick wins, it helps me identify what levers I can pull to help sales close deals faster.”
