Thoughts from my journey

So how do you know which sales model is best for you – zero touch vs. low touch vs. high touch vs. field?

In his last tip from the Sales 2.0 Convention, Mark Roberge, VP Sales at Hubspot explains that it’s really depends on your buyer, what you’re selling and the full sales context and it does require some experimentation.

Preferably you should aspire to go on no touch or low touch as possible as the economical will always be best if you can pull that off.
But it is best to simply run experiments – set 100 leads to no touch and 100 leads to low touch and check the conversion rate, revenue, Customer Lifetime Value and in SaaS see what the CAC to LTV is  (Customer Acquisition Cost to Lifetime Value) and what the payback periods are and take the approach which has the best economics.

Furthermore, as mentioned in many of my previous posts, it is highly recommended to keep a thorough and updated Cohort Analysis for your metrics so that user behavior would come out accurately. This is the only way a successful SaaS business could reach the right consequences and choose its suitable sales model!

Review Mark’s first tip “Do you Distinguish Your Sales to Hunters and Farmers?”

Review Mark’s second tip “Top-of-Funnel Strategy”

To read the full transcription of the video, click here

Video Transcription:

Mark Roberge, VP of Sales at Hubspot.

Yes so, zero touch versus low touch versus high touch versus fields, the quick answer is it depends, unfortunately, and I’ll walk through the dynamics. It really depends on your buyer and what you’re selling in the full sales context. And it’s gonna require some experimentation. I think in general you’d prefer to go as no touch or low touch as possible.

I think the economics will always be best if you can pull that off. But hey, if you’re wondering, “Here’s a lead that has 50 employees in this particular segment. Should this be a no touch or a low touch or a high touch?” You run experiments. You send a hundred leads like that to no touch, you send a hundred leads like that to low touch, and you see what the conversion rates are, you see what the revenue is, you see what the lifetime value is, in a SaaS role you see what the LTV to CAC and the payback periods are, and then whichever ones have the best economics, you take that approach.

This week I was attending the Business of Software Workshop talking about Using Customer Analytics to Increase Revenues of SaaS Businesses.

I’ve shared the presentation I’ve used in the workshop in which I discussed:

• Characteristics of the SaaS business
• How CLTV (represents Customer Success) should be higher than CAC (represents Marketing & Sales)
• The Customer Engagement Cycle
• Grow Conversion Rates
• A case-study on the SaaS Low Touch Module which shows how to focus on the converting opportunities and create priorities in order to increase conversion, reduce churn and enetually increase revenues for a SaaS business
• Ensure customer success (CLTV)

Can you implement those important tips in your SaaS business?

Defining an active user and setting a baseline

Over the next few weeks, Totango will be posting a blog series on best practices for measuring conversion rates of trial usage for Software-as-a-Service (SaaS). Trial conversion is arguably the single most important business metric for SaaS companies since the model is based on two key parameters: customer acquisition cost and customer lifetime value. The trial conversion moves customers from the acquisition phase to the lifetime value phase and as more potential customers become paying customers, the customer acquisition cost goes down and the customer lifetime value goes up. Simply put, the ratio between customer lifetime value and customer acquisition cost is the entire profit of a SaaS company.

It is important to make sure that the measurement of trial conversion addresses three basic concepts:

1. Simple to measure;
2. Simple to understand;
3. Be actionable.

Unfortunately, trial conversion is not that simple to measure correctly (most organizations do it, but haphazardly) because there is no “single source of truth” per se. That is, trial conversion comes from multiple business processes (marketing and lead generation, in-house sales, and the product itself), which muddies the ability to measure it definitively. As a result, to get an accurate trial conversion number, organizations need to make sure that all the data collected is aligned among the business processes mentioned above.

The second challenge is “noise,” or trials that are “dead on arrival.” These users may have signedup for a trial, but have no intention of buying. They are just playing with the software because they can; it could be for educational reasons, it could be for other reasons. Taking these “dead on arrival” trails into account creates a very blurry picture, which is difficult to take action on.

Considering the challenges of measuring trail conversions (and the need for simplicity), the first step is to define the active, or effective trials (trials who came with the intention to buy and now are evaluating the service) and weed out the “dead on arrival” trials. There are different ways to do this of course, but one example could be measuring active trials based on a second day of usage or perhaps based on what the user is actually doing. Once the SaaS organization defines an active user, a baseline can be established. A baseline is taking the current number of trial conversions (and perhaps taking into account historical information as well, if available), and setting metrics around that.

With a baseline set that weeds out “dead on arrival” trials, organizations can tweak the service they sell or the various parts of their sales and marketing processes to improve trial conversions. Perhaps the organization needs to focus on marketing to get better leads because the current leads aren’t good enough. It could be that the sales process is not effective and it needs to be improved. Or it could be that the service itself needs improvement. Ultimately, the SaaS organization needs to measure continuously in order to put a finger on the right problem.

Imagine an organization that had, for the duration of July, 1,000 new signups for trial. Out of those accounts, 10 ended up “converting”. On the face of it, the conversion rate is 1%.

However, dig a bit deeper and in many cases, you see that many, if not most, of those 1,000 trials never had a “buying potential at all”, evident by the fact that they never did a serious evaluation of the service

(note: it would be nice if numbers in real life would be so round and simple to calculate in ones head!)

Why is this important? First off, because it gives a more real indication to what is going on within the sales team’s pipeline (they are succeeding in selling to 1 out of every 10 prospects not out of every 100), and it is easier to motivate people to improve a metric they intuitively feel is true.

But that is not it, in our next post, we’ll explore what the trial conversion metrics mean and how SaaS companies can best act on the data that is collected to increase conversion rates.

To learn more about Trial conversion,
view our 40 minute webinar: “Best Practices on Trial Conversion”

About TOTANGO:
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