I love studying human behavior and digging into analytics, so I think about demand generation measurements and optimizing buyer journey touch points more than any reasonable person should.
That said, I can’t be the only person wondering why we’re still implementing the old demand generation waterfall in B2B organizations to measure our campaigns' success and signal handoffs to sales.
Demand generation waterfalls embrace very linear sales cycles. They assume one campaign interaction travels a single straight line to a sale. In reality, our B2B buyer journeys look like a bunch of starving squirrels were dropped into the middle of a feast.
We are so fixated on making the traditional demand generation metrics work for us because our systems aren't developed for B2B buyer cycles. Our technology has been limited because our systems think of buyers exclusively as people--which is fine for B2C.
But it doesn’t have to be this way, and frankly, it shouldn’t be.
Demand generation is the act of creating awareness and desire for your product. This is usually done through press releases, podcasts, videos/television, online paid advertising, and other tactics that drive interest in your brand. The theory is that when more people know about the goodness of your product, it will prompt them to research your company (usually on your website, a product assessment website such as G2 Crowd, and/or within their networks).
While demand generation is technically one of the first legs of the buyer journey, its effectiveness is often measured by the number of leads coming into your funnel. If demand generation tactics are successful, lead generation should increase and match your target profile.
The difference between demand generation and lead generation is confusing because the lines are blurred.
Demand generation is, as we mentioned, the act of creating awareness and desire for your product.
Lead generation is the act of converting interested prospects into known, engaged leads. When you think lead generation, think chatbots, contact us form fills, meetings scheduled at events, and any other obvious indicator a specific person is interested in your product.
Demand generation success is often measured using lead generation statistics. Ideally (or maybe not, depending on how worried you are about how Ex-Machina things are getting with machine learning), we could measure how much prospects are thinking about your brand. Until then, awareness campaign effectiveness can only be measured by proxy metrics.
We can look at the number of impressions a press release generates or click-throughs generated by an article, but that bump in activity may not matter. If you're selling to IT professionals and a publication for elementary school teachers picked up your article, you may not care about the increase in website visitors. It’s like the “if a tree falls in a forest….” thought experiment.
If a person lands on your website and will never purchase from your company, does it matter?
This is precisely why lead generation metrics are a stronger indicator of success than topline web metrics.
Seriously, demand generation is a necessary activity whether you’re in a B2B or B2C organization. The only way people will buy your product is if they know you exist and what you do.
However, B2C demand generation metrics and B2B demand generation metrics should not look the same because the buyer journeys are not the same.
Let’s say we’re on Facebook and see a paid advertisement for a card game we’ve heard good things about from friends. We click on the ad and purchase the product on impulse. This all took place in the span of fewer than five minutes. We skipped straight from awareness to purchase.
Now let’s look at a six-figure deal for SaaS at an enterprise organization. The sales cycle will take six months and involve eight to ten people on the buyer committee. Multiple people at the purchasing company will need to sign off on feature requirements, security compliance, and budget in order to get this deal over the line.
People at the same purchasing company will enter the demand generation funnel at different points of the sale. They’ll consume different content and gauge whether or not the product is acceptable in different ways. The technical person will go to G2 and look at reviews and competitive products before diving into technical documentation. The end-users will look at YouTube testimonials and view quick product demos on the website. If any of these components are seriously lacking (lots of 2-star reviews or rants on YouTube), you may not get the sale.
Demand generation is essential, but it looks very different in B2B than B2C.
B2B sales target accounts and specific people who work at those accounts. The person at the purchasing account who manages the product is most likely the primary contact on the account, but you’ll also need signoff from the people who use the product and other decision-makers in the buying process.
B2B organizations should measure engagement from multiple angles. It’s important to find the right company and interact with the right people. A single demand waterfall following the primary contact simply won’t cut it.
To get the full demand generation picture, you’ll need the right systems and models in place.
If your tech stack is only configured to track sales from the point of contact (lead form, chat, webinar attendee, etc.), you’re missing a great deal of activity. Demand generation reporting should also include web content interactions (whether they’re gated or not) and paid advertising interactions that do not result in a form fill.
B2C customer data platforms are much better at enabling B2C organizations to track activity prior to a sale. With the right analytics infrastructure, B2B organizations can match the tracking available in B2C customer data platforms and aggregate data at the account layer.
The trick is tracking web activity and appending identifying information (from a form fill or chat session) to historical records. Partner integrations with social media platforms and advertising tools also go a long way in uncovering the mystery of demand generation effectiveness.
Once a data transformation layer is in place that can unify the definition of a person and account across all of your marketing and sales data sources, measuring demand generation program success gets a lot easier.
The demand generation metrics like marketing qualified lead and sales accepted lead aren’t useless in B2B organizations. They just don’t give us the full picture. Keep lead identification metrics in place to make sure sales is following up with people who raise their hand, but introduce the concept of a Marketing Qualified Account.
Marketing Qualified Accounts should be flagged when the right people at an account are engaged. Think of this as smarter engagement scoring. Suppose we know that a sale needs a technical expert, an end-user, and a certain executive in order to obtain sign off. In that case, we should see some sort of activity from all three personas before we consider them a qualified account.
The threshold for including activities in an MQA score should not be a hand raise. If we monitor all web activity, we can flag an account showing active buying signals far more quickly than if we only relied on MQL status. In this example, we would flag the account for sales once we saw all three personas interacting with web content.
I know what you’re thinking!
People have been trying to nail down marketing attribution and failing for years now. But some people are succeeding. The difference between these attribution warriors and the rest of us?
If a marketing operations specialist has implemented attribution software without a larger project team (and sign-off from the people who need to buy into the numbers), they’ve wasted their time and a whole lot of money.
Evaluating B2B campaign success based solely on demand generation waterfall metrics is like declaring a harness suitable for sled dogs after testing it on a senile cocker spaniel. Sure, we tested it on a dog, but we have no idea if a sled dog would shred it on its first run like a Warner Brothers cartoon.
Remember our B2B buyer journey?
Measuring campaign influence (attribution), demand generation effectiveness, and pipeline velocity will help businesses determine whether or not a tactic is productive. Some campaigns will look better in some categories than others, but that doesn’t mean they aren’t worth doing.
Disagree? Agree? Have a better idea? Please tell us about it! We can’t keep doing the same thing and expecting different results.
We had a question in the RevOps Co-Op Slack channel that we just couldn’t ignore: “Does anyone have any strong thoughts/feelings about where RevOps should report up to?” It turns out the answer is YES. We all have strong opinions about this topic.
The RevOps professionals who start experimenting with ChatGPT now will have a competitive advantage over those who adopt the tool when they are forced.