SaaS Marketing Science

Of the big four areas rife for SaaS business improvement — sales, marketing, customer success, and institutional readiness — marketing may be the least understood. I’m sure many of you are bristling at that idea but stay with me. That was my motive for my recent SaaS Marketing Guide eBook. Today, I’ll speak to the science of SaaS marketing. Next up is the art of SaaS marketing. The intersections and co-dependencies between them are where things get misunderstood.

SaaS growth methodologies are newer than SaaS itself and subject to the same relentless change as rapidly evolving markets and technologies. Each of the big four is a beast of data-driven metrics and levers. But SaaS marketing is a special combination of science driving art, and art driving science. If either the science or the art is weak, the machine fails. And if it’s the science that’s weak, it can be hard to know what’s failing and why. That’s why we’re starting with the science. It’s not that the art is secondary, it’s just second.

What is SaaS Marketing Science?

I say over and over again that SaaS marketing science is about knowing things rather than guessing or assuming things. What things do I mean? It starts with knowing who our customer is. Then it’s about knowing what they value. And the verbal and visual languages that resonate with them. And how about knowing where and how they get their information? Or what drives their buying decisions? These are really important things to learn and know. When a SaaS business knows these things, it’s much more capital efficient. It can win more customers with less investment.

Winning More Customers with Less Investment

That’s the holy grail of SaaS growth — capital-efficient demand generation. With all of that knowledge comes a predictable funnel. $1 poured into the top of a scientifically defined sales & marketing funnel will — with statistical confidence — result in $X of ARR. Combined with a scientific customer success methodology, that predictability can be extended to include lifetime value (LTV). If you’re growing a SaaS business, those are some pretty heady predictable numbers.

SaaS Marketing Science Starts with the Funnel

Funnels can be very different. Self-service free-to-paid looks very different than personal selling in B2B. But the science of SaaS marketing begins with defining measurable and significant funnel stages. Everything that gets tested and measured from there, contributes to funnel stage efficacies that trickle down to won deals.

Example B2B SaaS Marketing Funnel Stages

Let’s say you’re a B2B SaaS that relies on personal selling to close mid-ticket, relatively high-velocity deals. Perhaps that translates to an $8,000 average contract value and a 30-day sales cycle. Your funnel is likely a mixture of marketing generated leads (MGLs) and sales generated leads (SGLs from outbound effort). We’ll make an arbitrary assumption that 80% of your deal flow comes from MGLs and 20% from SGLs.

MGLs and MQLs — Let the Acronyms Begin

Your scientific SaaS marketing funnel needs to be measurable for quantity and quality. And quality must be measurable by marketing, and separately by sales. That means some percentages of your MGLs at the top of your funnel qualify to become marketing qualified leads (MQLs). This likely happens via marketing automation lead scoring of the lead’s profile as well as their activity. Some of this may be explicit and some of it may be inferred. Your scoring will be more accurate and valuable if it’s based on explicitly known data rather than inferred data. Let’s say that 40% of your MGLs become MQLs.

MQLs and SQLs — Sales Gets in on Quality

The science of SaaS marketing goes down the drain if sales isn’t fully integrated and aligned with lead quality. MQL criteria must be sales-aligned. But that’s not enough. Marketing’s measure of success must come from conversion of MQLs to sales qualified leads (SQLs). This is often not automated, but rather human — where the sales team grabs MQLs, follows up with them, and determines if they are likely to become customers. In many sales organizations this means creating a sales opportunity. Let’s say that 50% of your MQLs become SQLs.

SQLs to Wins! — Sales Takes Over

Marketing’s influence is largely limited once a lead qualifies as an opportunity. From here, sales, and their process takes over to convert opportunities to customers. There are a bevy of measurable variables in that conversion, but those are best left for another post. Let’s say 50% of sales opps (SQLs) convert to won customers.

10 Leads to Get One SaaS Customer

Our example funnel looks like this: 4 out of ten MGLs make it to MQLs; 2 of those 4 MQLs make it to SQLs (sales opps); and 1 of those 2 sales opps close wins. That means it takes 10 MGLs to win a customer.

SaaS Marketing Science is Really Quite Simple

Based on our example funnel, we define hypotheses, test and measure outcomes, and continuously improve to optimize our funnel efficacy. Every quarter should be more efficient than the last. Once funnel efficacy is stable and predictable, testing can focus on reducing cost-per-MGL while preserving performance. This drives down customer acquisition cost (CAC) over time. Again, under the watchful eye of continuous improvement — cycles of innovation and iteration that consistently move the needle.

But It’s Anything But Simple

Yeah, so, remember how I started this post saying that the intersection of the science of SaaS marketing and the art of SaaS marketing was where the misunderstandings happen? Well, let me pay that off right now.

We can all understand the funnel. Stages are pretty clear. And testing is not rocket science. But the number of variables and the nature of those variables in marketing is incredibly complex. And much of that complexity comes from the artful nature of what needs to be tested and optimized.

Getting back to what we want to know… who our ideal customer is; what messages resonate with them; what they value and how that plays with our solution; where they get their information; and how they make decisions. In order to know — and not assume nor guess — we have to test. What we say, how we say it, how it looks, how it works, where it’s used, how it’s used, what it incentivizes, how it incentivizes, what we ask, and how we ask all have quantitive outcomes from highly subjective and qualitative inputs.

The art of SaaS marketing makes everything very, very messy. Yet that mess is where the real value lies. And without it, the upside of the science is limited and the brand is undifferentiated. Artless science in SaaS marketing translates to failure. My next post will focus on making the beautiful mess that is the art of SaaS marketing manageable.

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