SaaS companies have a problem, and its people like me. Free users who are afraid of a commitment to a paid account.
Let me explain. I love Dropbox. I am a Dropbox power user – I save a lot of my critical files on Dropbox; I access my account from multiple devices; I use it to share files with others; I’ve linked it to multiple other apps and platforms. I even evangelize for Dropbox, encouraging friends and relatives to sign up.
However, I am not a paying Dropbox customer, and I do not intend to be one – ever.
In other words, I’m a common problem for SaaS firms, especially those in the Freemium and Free Trial space. They can get users into the top of the funnel, but nudging the free (or free trial) users to paid subscription remains a challenge.
Given the criticality of converting free users to paid users, SaaS firms do try hard. Different firms try different approaches. I like to broadly classify them into two categories, starting with:
The Entrapment model starts with a common hook: a little bitty ‘sample’ for free.
It works a lot like those tiny potato chip bags.
The first time you eat a tiny bag of potato chips (or chocolate, or whatever snack food is your Achilles’ heel), you enjoy it. What you don’t realize is that these delicious comestibles are actually designed to create cravings for more… and more… and more. Pretty soon, only a big bag of that particular brand will do.
Many SaaS (and other Digital Subscription) businesses try a similar route. The thought process goes “I need to get my users addicted to my product, so I’ll give them a little bit of the good stuff to start with”. So the SaaS firm adds a lot of rock-solid features to their product – and then offers only some them to the free or free-trial users.
In this scenario, paywalls or limited trial periods basically force people to pay up or do without. Everything the firm does is focused on increasing usage and engagement with the product, creating a need within their customers.
Personally, I do not like the idea of being forced to buy. As a consumer, I may end up buying something because of a lack of choice. But afterwards I would always be looking for excuses to exit that icky relationship.
Next, let’s move on to the second method:
The Seduction of the SaaS Free Subscriber
Some organizations think beyond developing their product and pestering the customer to pay. Instead, they zero in on effective marketing. They want you to want them, and they’ll do whatever it takes to get the message across.
They use analytics (or at least claim to do so); they deploy complex lead scoring and marketing automation tools. And they love A/B testing – trying out different types of messages, and adopting the one with the maximum response.
With the armies of data scientists at these organizations, bristling with so many tools, one would expect conversion rates to be shooting up across the industry. Sadly, that is not so. If you do some research on the average conversion rates seen over the years, the numbers continue to hover around 3 to 5% for freemium model. (For details, check out Totango 2014, Totango 2012, and Quora.)
So, with all this data being analyzed and poked and prodded, why aren’t conversion rates higher?
Why SaaS Isn’t Making The Sale
We can actually place some of the blame on the tools. They do a great job of segmenting and prioritizing the users. Firms get a very good idea of who to chase. However, current tools fail to determine the right way to influence these targeted customers. Therefore, SaaS companies are often at a loss to determine their Next Best Action. Predicting what message would work is tricky; reporting what worked in the past is easier. When one does A/B testing, one perforce ignores the possibility of option C. And this may well be the best option for the target users.
When it comes to prescriptive analytics, the tools are missing a beat. Recommendations on when to target (during usage, late night, first thing in the morning, etc.) and the appropriate channel (in-app, email, phone call, etc.) remain largely unaddressed.
And there do not seem to be any recommendation engines to help the Product Development team. They get a lot of dashboards and plenty of reports on usage, but what about product improvement input? Perhaps there are critical features to be developed that would be far more effective than yet another irritating email message screaming “BUY ME!!!”
Will Better Data Analytics be the New SaaS Matchmaker?
It’s a possibility worth exploring. Imagine if Dropbox had a tool that:
- Identifies a user (me, for example) who is about to run out of free space
- Selects the user as a target for conversion
- Understands that my… I mean, the user’s potential conversion is based on the storage of large files
- Drafts a message highlighting the storage space available in a paid version
- Detects that the user prefers to read emails on Sunday morning, and times the message through the e-mail channel accordingly
Wouldn’t this tool be better (and cheaper) than an army of data scientists telling you what worked in the past? I think so. What about you? What do you think the future holds at the intersection of Data Analytics Avenue and SaaS Conversions Street?