Behavioral Analytics: An Overview For B2B Marketers

B2B marketing teams spend so much time analyzing data that it’s easy to lose sight of why marketing has evolved to become a data-centric discipline. Ideally, all marketers would operationalize data to identify specific customers who intend to buy (and when they plan to buy). If your data isn’t leading you down that path of discovering purchase intent, then you’re likely analyzing the wrong data.

Purchase intent in B2B is complicated. It can’t be determined with the surface-level data that marketers traditionally measure. Yes, analyzing email open rates, ad impressions, or website traffic does give insight into your brand awareness. But B2B marketers have long suffered from a limited field of vision when it comes to uncovering a buyer’s true intent.

In order to clearly see when and how to influence your target buyers, savvy B2B marketers must rely on behavioral analytics. This strategy is evolving to help sophisticated marketing teams operate much like their counterparts in the B2C space by pinpointing changes in behavior that might indicate purchase intent. Better yet, B2B marketers who take advantage of behavioral analytics can prove real ROI by helping their sales team build a bigger, more qualified funnel.

Traditional Marketing Measurements Can’t Uncover Purchasing Intent

A sales team’s success depends on whether or not a quota is reached. Period. Measuring a marketing team’s effectiveness isn’t so straightforward. Many metrics used to evaluate the ROI of a marketing investment often fail to uncover the real value of purchase intent signals. Those signals are key to being successful with behavioral analytics.

Take note of which traditional marketing metrics are NOT measured in a behavioral analytics strategy:

• Web traffic
• Email open rates
• Click-through rates
• Blog post clicks
• Banner ad impressions
• Social media followers

For example, here's what Peter Weinberg, LinkedIn's global lead for the B2B Institue, has to say about click-through rates: "The most commonly used KPI in marketing is essentially worthless. Click-through rates don’t correlate with any meaningful brand metrics, or any meaningful lead-gen metrics for that matter. Billions of dollars are “optimized” based on nothing but noise. Meanwhile, you are more likely to complete Navy SEAL training than to ever click on a banner ad."

To many, these are considered marketing fundamentals. But building a strategy solely around these metrics won’t put you in the same league as innovative marketers who have a hand in a company’s overall growth. Marketers who can identify right-fit leads based on behavioral analytics can show real ROI. And being able to show real ROI is the key to earning more recognition and unlocking a larger budget.

Why? More than 80 percent of CEOs see marketing as a clear driver of growth, yet nearly 25 percent of those CEOs believe marketing is not delivering that growth (according to a McKinsey report). Helping your entire organization understand the buyer’s journey – and purchase intent along that journey – will ensure that marketing has a seat at the table during any growth conversation.

Driving more traffic to your website might signal better brand awareness and a larger share of voice. But it can’t signal specifically what company – and who, specifically, at that company – is navigating the buyer’s journey and when.

An Overview Of Behavioral Analytics

A behavioral analytics marketing strategy targets specific people – customers or prospects who are a fit for your solution or product. This is the kind of information sales teams crave. To start down this path, your data-driven marketing engine would ideally capture the following:

1. Demographic data (an individual’s name, title, email, job function, location, etc.)
    
2. Firmographic data (a company’s name, type, revenue, product category, etc.)
    
3. Event data (information about how a buyer interacted with your brand via a trade show, webinar, content download, sales demo, etc.)
    
4. Contextual data (information about the specific asset an individual buyer engaged with according to the theme, format, content age, etc.)

Imagine you could wake up tomorrow and suddenly be able to capture this data about all of your target prospects. That’s the “analytics” part. What should you do with that data to understand the “behavioral” part? Which types of activities signal purchasing intent?

B2B products and solutions with long, complex sales cycles don’t exactly have online shopping carts. A midsized pharma company looking for a fill-finish manufacturing partner isn’t waiting for a free shipping coupon code to show up in their Gmail accounts in order to move forward on an RFP. Marketing would be easy if every prospect with sole decision-making authority went to your site, clicked on your content, and instantly filled out a form requesting a conversation with a sales rep. Since buyers aren’t that blatant with their behavior, you have to look for more subtle shifts in engagement.

B2B buyers are humans, and as such are creatures of habit who attend the same trade shows, read the same sources of information, and do so with the same frequency. It’s likely a sign that something is changing when prospect engagement starts to spike across a variety of individuals in the decision-making process.

That is the kind of holistic data tracking involved in a behavioral analytics strategy. Identifying subtle changes in demographic, firmographic, event, and contextual data among a group of individuals involved in purchasing decisions at a target company can help marketers evolve from simply tracking traditional metrics to actually helping their sales team act on the best opportunities.

Why B2B Marketers Struggle With Behavioral Analytics

The outcomes of a behavioral analytics strategy are things marketers dream about: proving ROI, being championed by their sales team, and earning a large share of budget needed to drive growth. Unfortunately, it’s not easy to make those dreams a reality.

Before you can take full advantage of behavioral analytics data, you’ll need to resolve any data integrity and/or data normalization issues. That’s easier said than done. You’re certainly not alone with your data cleansing struggles. According to The Forrester Wave™: Predictive Marketing Analytics For B2B Marketers report, customers of B2B predictive marketing analytics providers were least satisfied with their vendors’ ability to deliver accurate contact information for acting on opportunities. If you’re targeting Johnson & Johnson, for example, and your firmographic data shows the company name as “Johnson & Johnson” or “J&J,” then you’re bound to have a data normalization headache.

For now, let’s assume your data is perfectly clean and captures each of the above categories. You know that Prospect “A,” who is a VP at Company “B,” has downloaded your white paper about “XYZ” and forwarded it to Prospect “C” at that same company. Now you can score that lead and know exactly when and how to begin the nurturing process. Better yet, that data will empower you to hand that prospect off to the sales team at exactly the right time. Now you’re all set, right?

Not quite. There’s still a blind spot that prevents B2B marketers from taking full advantage of the power of behavioral analytics. More on that in our next post, "Imagining An Ideal Application Of Behavioral Analytics."

Originally published on Follow Your Buyer