March 3, 2017
The Complete Guide to SaaS Conversion Rate Optimization
Conversion optimization is a process that can be translated to any product or service. However, there are some slight differences depending on the type of business model you have, at least in the way you approach optimization. The common paradigm for conversion optimization is that you’re running an e-commerce site with a large variety of products. But how does that translate to SaaS optimization? What’s similar? What’s different?
First, why is SaaS any different from another model?
There are two things that really differentiate a SaaS product from others in terms of optimization: it’s a recurring subscription, and many of the growth opportunities come from the product itself. To further elaborate, much like the differences of _B2B optimization_ in general, the differences with SaaS mostly comes down to differing business cycles, purchasing decisions, and success metrics. Unlike a B2B enterprise software product, though, you usually have to optimize onboarding, not just increase leads and lead quality. And unlike a subscription e-commerce site, like BarkBox, there’s an in-app experience that you can, as someone focused on growth or CRO, actually impact. SaaS is similar to e-commerce, though, in that you could be dealing with a wide variety of pricing models and sales strategies. An inexpensive live chat tool and Oracle’s Marketing Cloud could both be considered SaaS. In addition, there are different solutions within the same company and product line. I could buy Adobe’s Creative Cloud, but they’re also selling to my small company, the world’s largest companies, my old university (UW-Madison), and individual students there. That’s a wide variety of _personas_ for a similar product.
Primary goals of SaaS optimization
In general, you have a broader area of control in SaaS. It’s not just landing page optimization or checkout optimization, but rather what I like to call universal optimization, or _optimization beyond the landing page (which is becoming more common_ in every type of business, actually). In SaaS, you have to worry about:
Generating new leads
Making sure the leads are appropriate for your offer
Making sure your offer is well communicated to each and every segment that may be within your target audience
Measuring and optimizing in-product activity
Reducing churn rate
Increasing activation and encouraging product engagement
Designing upsells and upgrades
Creating promoters and referrals
Usually you optimize for fewer metrics on an e-commerce site, like Average Order Value or conversion rate (not that it’s easy to increase these). But you have to think longer term with SaaS. You have to plan out and measure further down the customer relationship (>90 days after sign up), as well as before they land on the site (are you attracting the right people? Could be wasting sales and customer success time if not). In short, you can experiment across the “pirate metrics,” as well as a different set of Key Performance Indicators. Before we dive into optimizing across the pirate metrics, let’s talk about some basic vernacular.
SaaS metrics and KPIs
Image courtesy of Stephen Pavlovich
Someone doing conversion optimization for a SaaS site will usually have the following options as stages to run tests…
visit → trial (quick to test, but doesn’t always correlate to sales)
visit → sale (better indicator of revenue, but this increases the duration of the test)
visit → qualified trial (use lead qualification to predict better lead quality—gmail address vs. business address, looked at whitepaper, company revenue, etc.)
visit → active user (according to Stephen’s presentation, optimizing for this conversion is the best value long term)
If there were a TL;DR, it’s that in SaaS optimization you’re looking a little further down the road and ensuring quality leads in the first place. You’re also optimizing for a different set of “macro-metrics” (such as Average Order Value for e-commerce), like:
**Monthly Recurring Revenue (MRR): **measures predictable and recurring revenue of your subscription business (not one-off sales, only those on a subscription plan)
Customer Lifetime Value (LTV): the complete monetary value of a customer, usually calculated in aggregate or by segment. You want LTV to by high.
Customer Acquisition Cost (CAC):the average cost of acquiring a customer. You want this to be low, or at least lower than LTV.
Then there’s the case of what a “_micro-conversion_” means in SaaS. According to Stephen Pavlovich, optimizing just for free trial sign ups is akin to optimizing just for add-to-cart in e-commerce. It’s a micro-conversion that may or may not correlate with more important metrics like revenue and active users. He explains that you should view SaaS optimization not as a relay—where you first get the sign up and then optimize for the trial-to-paid, etc.—but rather look at it holistically and optimize for the best value throughout the funnel.
Pirate metrics and optimizing beyond the landing page
You’re probably familiar with the pirate metrics. They’re not just applicable to SaaS of course, but fit very well with a SaaS model:
Acquisition is pretty straightforward. This is the stage in which you acquire the user. For SaaS, this usually means a sign up. As far as the metrics above go, this is the stage where you worry about customer acquisition cost. In general, you want to acquire customers as cheaply as possible, and you want to acquire customer with the highest possible value.
This stage includes all of the traditional channels you’re used to:
In addition, it includes all of the conversion optimization tactics you’re used to, including landing page optimization, which makes your acquisition channels more effective and cost efficient. This stage is where most people focus, but it’s only one part of the growth equation here.
After the signup, you need to nudge the user to actually, well, use your product. This is activation. A good acquisition strategy will help assist with your activation strategy, because if you’re acquiring incompatible customers they will never get value out of your product. The tools you’ll use to activate users are general email and product, with the related inclusion of in-app messaging. This is where tools like _Amplitude_ become incredibly useful. You can analyze _behavioral cohorts_ to find which actions your most valuable customer segments are taking. Then, you can optimize product features to increase activation.
Activation is the stage in which your onboarding is important, as well. It’s an underlooked portion of growth and optimization, because you can acquire all the customers you want, but without a solid activation strategy, the numbers won’t stick. Active users should be your goal.
Retention can be defined by many different parameters, but the broad definition is that the user keeps using your product. This, of course, indicates that they actually like and get value out of your product, and that the customers you are acquiring are a good match for your product. Churn is the opposite of retention, and it has a huge impact on not just lifetime value but customer acquisition cost. Think about it: if you can extend the relationship with your customer over a longer period, you can spend more to acquire customers and zoom past the competition. If you’re churning customers at a rapid pace, you can barely afford to spend anything on marketing.
Just like it sounds, referrals are when the user, through external incentive or just pure joy and appreciation, refers others to use your product. This is the traditional lever you think of when someone says growth hacking. It’s the examples of _Hotmail putting a referral tagline_ on each of their emails or _Dropbox giving you free space_ for inviting friends. The metric you’re optimizing here is the [K-Factor](https://en.wikipedia.org/wiki/K-factor(marketing))_.
Obviously this step is where you collect $$ from your user. Just because it’s last in order in the pirate metrics doesn’t mean it’s last in order for your business. Revenue, realistically, is the most important metric and is a function of all of the other metrics.
Make it rain
The beauty of SaaS is that you’re allowed and encouraged to experiment across each of these metrics. Not only can you tweak email subject lines, landing page headlines, and site navigation for acquisition, but you can trigger in-app overlays for increased revenue upsells, build beautiful onboarding flows for retention, or try different virality experiments for referrals. You can see, now, how CRO for SaaS is a bit more encompassing, at least on the surface (as I alluded, you can optimize things like call centers and email automation flows for e-commerce, but these go the basic paradigm of e-commerce CRO).
How to structure an optimization team for SaaS
There are two general types of optimization team setups in modern organizations: centralized and decentralized.
Centralized optimization teams operate much like a dedicated agency within the company. They’re made up of specialists and program managers, and they own and exclusively focus on CRO. This is opposed to decentralized optimization teams, where individuals with other roles—perhaps product managers, digital marketers, designers, copywriters—will all take it upon themselves to experiment and optimize their work. Perhaps there will be a person or two that takes the lead and owns the metrics, but it is democratized to an extent and decentralized in the organization. SaaS tends to be decentralized. There is no right or wrong way to do this, but there’s a potential snag in the decentralized approach. With no single team setting up a rigorous process (that they can, in turn, optimize over time), it’s hard to maintain a consistent standard for experimentation within the organization in regards to research, prioritization, and KPIs. People could be treating conversion rate optimization entirely different depending on their role and what week it is. Even with a single person owning the testing tool or analytics setup and providing training to everyone else, it’s tough to keep a consolidated optimization approach with a decentralized team. Something to keep in mind, anyway. This can likely be solved by a strong culture of experimentation (hard to fake that), good documentation, healthy investment in employee education, and stellar cross-functional communication.
Continuous optimization and a culture of experimentation
SaaS startups live and die by data and experimentation. Sure, branding is important, but we can certainly agree there’s a qualitative difference in marketing for Levi’s and marketing for Slack, right?
Therefore, it’s important to breed this culture early and nurture it as you grow. This, for all of its nebulousness, is likely the most important part of optimization for SaaS. It’s one thing to test headlines, subject lines, popups, and CTAs to a local maximum. It’s a whole other feat to embed experimentation in your organization. If we’re to take _Michael Schrage_ or _Jake Knapp_ seriously, rapid experimentation should be the key driver of innovation and progress in our organizations. To paraphrase Brian Balfour, “[optimization] is never done.”
SaaS optimization is fun and it’s complex. Instead of optimizing a landing page for a higher conversion rate, you’re optimizing across the inbound acquisition all the way through to retention, referral, and revenue. In addition, the prototypical organizational setup for a SaaS company is both limited and empowering: you may not have a centralized CRO team, but that means everyone is empowered to experiment as they will. And if you’re at a data-driven company, that level of democratized testing is super powerful (and fun). In any case, think of SaaS optimization as a holistic growth process across multiple metrics and parts of the product and user experience. How do you run SaaS CRO in your organization? Anything we missed? Let us know in the comments.