This is a guest post from Kyle Racki, co-founder of Proposify. He asked to write a blog post about his experience reading Lean Analytics. We were happy to oblige…
I finished reading Lean Analytics a few short weeks ago. The timing was good, because I just happen to be launching a startup, and the advice I gleaned from the book has been incredible so far.
For starters, Lean Analytics, while being focused on metrics and numbers, is surprisingly approachable for the average person. It isn’t written for data scientists or mathematicians (God knows I am neither of those), it’s written for entrepreneurs — for people who want to build great products and profitable companies.
Due to the applicable nature of the book, the difficult part of reading Lean Analytics was trying to decide if I should keep reading it or put it down and start applying it’s advice immediately. As I read it, tons of ideas came to mind, and I found myself constantly reaching for my laptop or phone to leave notes and reminders of what to do differently.
One of the things I like best about Lean Analytics is that you don’t need to read the whole thing. The authors, Alistair Croll and Benjamin Yoskovitz, have thoughtfully broken the sections out into chapters that each focus exclusively on one type of business model, such as E-commerce, SaaS, free mobile apps and so on. While I would like to one day read all of the chapters for each business model, I’ve got a company to build today, and so I only read the general chapters plus the two chapters that focus on Software-as-a-Service — the business model my company falls under.
I will outline the three major ways I’ve taken the knowledge from the book and applied it to my own startup, but to start, let me give a little background about my company.
Helping companies win new business
My company is called Proposify–online proposal software that helps businesses of all types write, design and manage proposals faster and more easily. We’ve had the idea in the works for over two years, but didn’t really focus on it full-time until late last year when we acquired some capital from ACOA to aid in bootstrapping the product. In the time since then, we built the MVP and released it to a group of private beta testers (in April 2013). That was around the time I started reading Lean Analytics.
I was pretty nervous reading the first couple of chapters, where it asks the reader hard questions like “Should you even be building this product?” The book aptly points out that all of us (entrepreneurs) are liars, and I didn’t want the book to somehow prove me wrong about my business, and my reality distortion field was in high gear.
There were moments in the book, particularly chapter 15 “Stage One: Empathy” where it suggests that the reader should spend a lot of time “getting out of the building” and talking with potential customers, running surveys, researching competitors and basically trying to figure out if you are building a product that addresses a problem worth solving. It forces you to ask yourself “Will enough people pay me to use this software?” Of course, I did actually do all of this over the last couple of years, but not to the degree outlined in the book.
But I can’t go back in time, all I can do is move forward based on the information I have now. Below are the two major things that changed what we are doing.
1. Knowing what stage we’re at
Like all co-founders of startups, I wear a lot of hats; I’m the product manager, UI designer, UX researcher, QA tester, team and project manager, writer and marketer. I felt a huge amount of pressure in the weeks leading up to our private beta to:
- design the right product
- test and find all the bugs
- drive traffic to the website through
- Social media
- Content marketing
- Paid advertising
- Offline networking and conferences
- find and acquire private testers
- ensure we are tracking the right metrics
That’s a lot of pressure and a lot of different types of skills to have to utilize all at once. However Lean Analytics breaks out the 5 stages of a startup into:
- Empathy
- Stickiness
- Virality
- Revenue
- Scale
It didn’t take a lot of time to realize that Proposify is at the Stickiness Stage. Right now we have a small base of test users, and I am actively reaching out to them for feedback on our MVP. That means any time or money spent on trying to acquire customers is mostly a waste — at least for right now when we don’t even know if the product has value.
So what I did was stop worrying so much about stuff like customer acquisition or landing page conversion, and instead I put my focus on how to tweak our product so that the users we do have find it more useful and they engage with it.
2. Finding our One Metric That Matters
In order to make our product more sticky, I had to find our OMTM. Originally I had been paying attention to the number of proposals created, thinking that that was some sort of indication of use. There are some problems with this approach though:
- For starters, a proposal is started with the click of a button, so every user can technically make one immediately after signing into their account, but it will be mostly a blank canvas. That doesn’t mean they used the product.
- Secondly, the amount of proposals may not be an indicator of engagement, since many small companies don’t need to be constantly producing proposals and may only have one to write every few weeks. As it turned out, many of the beta users didn’t actually create a proposal, because they had to first setup their template, which can take a long time, and doing that alone can give a test user an indication of how the software works.
Instead, I decided to start tracking whether or not a user actually sends a proposal to a client as an indication of whether or not they are using the product. In other words, one or more sent proposals in the given time period (one month) will define that user as active. If they don’t send a proposal, they aren’t active for the given time period. We want to increase our percentage of active users. That’s our One Metric That Matters right now.
After one month of private beta testing, I reached out to our users to get feedback. As you might expect, the responses varied from wildly positive to apathetic. But the consistent theme and likely reason for low usage was that either a user didn’t have any proposals to write at the moment (something we can’t control) or that it takes far too long to setup your template, and aspects of the workflow were unintuitive (something we can control).
So what to do with the data?
Armed with this information, we are implementing a fairly substantial pivot. Whereas before we were targeting firms who have designers on staff and want an online tool to remake their pre-existing proposal online, we are now targeting users without design or proposal writing skills who want a beautiful, ready-made proposal template filled with pre-written content that they can tweak.
As one of our test users wrote in his survey, “I want you to make me look like a rock star with the least amount of effort on my part.” That has become our company’s mantra and the promise we hope to fulfill. We are reshaping the product to walk users through choosing from a gallery of awesome templates that are designed and written for their industry, and with a few clicks and a drag-and-drop interface a proposal is virtually built in a few minutes. This will take less than a month to implement, but our hypothesis is that this change to the product will drive our engagement metric dramatically.
3. Our line in the sand
As Lean Analytics taught me, I need to create a line in the sand, and then honestly evaluate whether I can reach that line or if adjusting the line is necessary. For now, we need to have a base of early adopters who stay engaged with the product and pay to use it. In order to achieve that, our product needs to solve their problem. We are launching paid plans so that we can begin experimenting with price points and as a way of weeding out casual testers from the real paying users who need to use our software.
Looking forward to the next stages
In the book, there’s a chapter on virality – the third stage in a startup. It sparked a wealth of ideas for my product, because I hadn’t actually realized before that our product is inherently viral–users send proposals to clients with the tool, which is kind of like free marketing as long as the client notices our branding.
The question is, how do we encourage free promotion without alienating our customers? After all, I want Proposify to make our users look great and keep their clients’ attention focused on their brand, not ours. There are some ideas we have written down, but the great thing is that we aren’t even at that stage yet. For now, I’m going to focus on product/market fit, and user-engagement/stickiness, and once we reach or exceed our OMTM – 50% active users, we’ll move on to goals like lowering churn, improving conversion-to-paid and viral coefficient. Once those metrics are as good as we can get them, we’ll start looking at CAC (Customer Acquisition Cost) and LTV (Lifetime Value), and then look to drive revenue and growth.
The greatest thing I learned from the book is: we can’t focus on everything now — doing so will actually shoot us in the foot. All we need to do is focus on the One Metric That Matters right now. Once that goal is reached, or we learn what we need to from it, we can then focus on the next metric.
This has given me a huge amount of confidence moving forward, and I wouldn’t have gained it without reading Lean Analytics.
Damian (