Joel Burke is a data insights and analytics expert and co-owner of Outshine: a data-driven digital marketing agency that specializes in Adwords and PPC management. Burke also lends expertise to CloudKettle as the Analytics Practice Lead. You can find him on LinkedIn here.
Recently, I sat down with Joel to talk about how to manage advertising for SaaS companies from end to end of the customer lifecycle.
Can you give our readers some context on self-serve versus enterprise B2B SaaS companies?
The bulk of SaaS companies are represented by a spectrum of incredibly different types of sales cycles and pricing models. SaaS companies at the low end of the spectrum are completely self-serve, which allows people to purchase on the spot and convert right away. The selling cycle is sometimes 30 seconds. There is no sales team. There may be a customer success team, who answer emails and focus on customer service.
At the other end of the spectrum you have enterprise players selling really complex solutions that have a long selling cycle. The sales cycle can range from six, to twelve, to eighteen months (from onboarding until final sale).This is where we work. Our clients have large, complex deals with long sales cycles.
In the middle of the spectrum, are companies that offer some mix of self-serve to enterprise packages in a tiered pricing model (sometimes called Transactional).
So, what does advertising look like for some of your clients in the B2B SaaS space?
Let’s start with some of the self serve platforms and why that’s a really interesting space for digital marketers. As advertisers, self-serve is awesome because everything happens online – which gives us lots of data to analyze. For example, we can put up a landing page, drive ads offering a free trial to that page and start to see results within a single day.
Access to real-time results allows us to get instant feedback on things like; how our calls to action are working and which ad copy is performing better. We also get a feel for what our cost per trial is going to be. Which is an important metric because knowing how much it’s going to cost to generate leads over the long term, enables marketers to create better targeting, better creative, better landing pages, etc.
Where do advertisers go wrong?
Using the same example, the goal of a free trial campaign is usually to see free trial users become paying customers. What often happens is, marketers start to over-optimize for the lowest cost per trial leads. Which means they are incentivized to get the cheapest trials, regardless of whether those trials become paid customers or not.
If you chase the lowest cost per trial leads, you’re not optimizing for revenue because no transaction sale has been made.
Any good advertising agency can fall into this trap. So, it’s very important to track not only where free trials come from, but also, which ones turn into actual paying customers.
How can advertisers avoid this?
To avoid this, make sure analytics are in place to see which trials become paid users. For more sophisticated and mature SaaS companies we want to take this a step further. Beyond the trial to paid conversion metric, we look at what plans users are signing up for and associate lifetime value at a per trial level.
Alright, so what about some of your clients selling an enterprise SaaS product?
The benefits of a self-serve pricing model [lots of data because everything happens online] make measurement and attribution relatively easy. When you start dealing with SaaS companies that sell an enterprise product and have a long sales cycle, correct attribution becomes much more difficult.
So what we do is, measure from prospect to marketing qualified lead (MQL), to sales qualified lead (SQL), to customer.
How do you track attribution from prospect to MQL to SQL?
We hook into our client’s CRM and as the prospect moves through the various life cycle stages, we have webhooks that fire to our advertising platform. So we can see each lead move through the Sales funnel and how much value is being created at each stage.
If that lead converts, then we can actually see deal sizes, revenue, and ROI. By capturing and optimizing at the various stages of the life cycle, we’re better able to focus our advertising efforts on the activities that generate the most return on investment.
So similar to CRM Retargeting?
Yes, this approach is sometimes referred to in buzzword terms as CRM retargeting. The concept being, as people move through the funnel, you’ve got more data on them and their use case, so your advertising gets more relevant.
With most of clients, our efforts change the moment a lead converts to an opportunity. Everything changes from demand generation to sales enablement. We like using CRM retargeting to show ads to people once they’ve been flagged as opportunities.
Different people have different problems they are trying to solve. A good funnel needs to reflect that. Ultimately our goal is to drive more top line revenue for our clients.