Better Lead Scoring = Better Conversations

Show me a sales team that has the spare time to decipher ambiguous MQLs and I’ll show you a double rainbow. Can it happen? Yes. Does it happen often? Hardly.

Adobe Marketo Engage has the power to go far beyond the basic lead scoring of the simple use case of one email open = one positive lead score.

But taking the time to configure Marketo in ways that sharpen sales conversations can be worth its weight in gold.

Effective Marketo instances score on a wide variety of attributes such as demographic, behavioral, and firmographic data points to build useful MQL (marketing qualified lead) profiles.

Stop sign: Marketo lead scoring is a tango; gathering valuable input from sales is pivotal in identifying exactly how qualified leads should manifest.

Go Beyond Basic Lead Scoring

Basic lead scoring, i.e. scoring only on email clicks and opens, inevitably produces pseudo qualified leads. Here are some of the deeper aspects to Marketo lead scoring:

Explicit Versus Implicit Data

Explicit data is information that can dictate lead scoring based upon aspects such as geography, age, title, decision-making, or company. These are relevant quantifiable data points in which true/falses, yes’/no’s, or clear-cut data points can be defined.

Here are some more advanced explicit factors to consider:

Does the lead’s job title have access to a measurable budget?
Do the lead’s geographical characteristics match with how you can offer them a product/service?
Is your lead’s budget likely to handle your pricing?

On the other hand, implicit data is much more fluid in nature. Implicit data points involve interpretations such as preferences, needs, or problems that require a solution. Implicit data can go as far as what content is desired or how content is ingested.

Here are some implicit factors to consider:

What is the observed readiness to purchase?
What are the barriers to disseminating information across stakeholders?
Is there a type of content that resonates with a particular lead?

Active Versus Passive Behavior

For lead scoring, active behavior measures the potential to buy, based upon measurable activities showing sales readiness.

Passive behavior recognizes the browsing type of engagement activity.

There becomes a discernable difference between a lead’s inquiry of specific prices (active) versus product/service capabilities (passive) for purchase.

Keeping both behaviors in mind, creating a scoring token system that gives confidence to active versus passive behavior will dictate the fidelity of lead scoring.

Leveling Up Lead Scoring

At times, symbolized score leveling can inform a CRM to signal the rise or fall of a lead. This results in more simplified lead score filtering.

Gather

Marketo users don’t always have the inside track of sales personnel’s brains. It becomes difficult to gather the entire picture into what certifies a lead as “sales-ready”. Aggregating the information to convey who, what, when, where, and how MQLs should be passed onto sales is essential. Here are some questions that may help to bridge that gap:

What data is typically missing that would help the selling process?
What is the average time in which a lead is in each stage of the sales cycle?
Is there data that informs on past interactions with sales?
What past opportunities were missed?
What purchases were made by the prospect in the past?

Assign

After an amalgamation of data points above, it becomes necessary to assign scoring tokens to each. Take the time to implement which scoring tokens are the most important, followed by an iterative evaluation of how they come to fruition.

Also, score token naming only allows for 50 characters for each. Navigate your naming conventions wisely if you begin to create numerous score tokens.

Don’t forget about the importance of negative, or degradation, scoring. Leads can choose an alternative product/service or simply lose interest. Account accordingly.

{{my.Basic Lead Scoring}} +100

At the conclusion of launching a more advanced lead scoring program, interact with sales to determine results. Checking in with sales teams ensures the evolution of an iterative, non-basic lead scoring model.

Seeking help with more advanced lead scoring or something much more complicated? Reach out to the Perficient team to uncover how we can help you and your organization with marketing automation.