Customer Validation: What To Do Post Product/Market Fit

Posted on February 21, 2012
Filed Under Entrepreneurship |

The customer discovery playbook has become well known in the web startup space.

Step 1: Release MVP, preferably for free.
Step 2: Get feedback, primarily from customer surveys.
Step 3: Iterate and improve until 40+% of your userbase says they would be really disappointed if your product ceased to exist.

It’s not quite that simple, but the steps are pretty well understood, and there are even some good baseline numbers you can use to qualify your application as having “product/market fit.” But here’s the problem… we treat product/market fit like it’s the holy grail, when it is only the beginning. Every startup I talk to is trying to get product/market fit, but very few seem to know what the hell to do after that. So for what it’s worth, here is my suggested playbook for the next phase - customer validation - based on what I learned at Backupify.

What Is Customer Validation?
Customer Discovery is about getting the product people want. Customer Validation is about finding a repeatable scalable business model around that product. Many first time entrepreneurs don’t realize that there are many good products that people love that are ultimately bad businesses. Customer Validation tries to figure that out as quickly as possible.

First Things First - State Your Sales and Marketing Hypotheses
At this point in your company evolution, you should have some general idea about how you will make money from this product. You should have talked to enough customers to understand what they would pay (or, who would pay to reach them), where they would go to find this product, the profile of the target buyer (it’s whoever is using your product, usually), how that person expects to buy the thing (does he/she need approval, for example?), and you should have an idea of how you would position and message your product.

Your first step is to write down all of these hypotheses. For Backupify, the most challenging part was defining the initial messaging and positioning. We are in a new market and so, like most new market startups, we compete more with indifference or other types of solutions rather than direct competitors. There isn’t a name for what we do, because “cloud backup” means “PC to cloud” and so there is no clear term we can use to harvest SEO or PPC demand. We sometimes say “cloud to cloud” backup, but that hasn’t really taken off. We also focus on “gmail backup” or “google apps backup”, but those have small search volumes.

So how do you position and message in a new market? You have to sell vision. Product features are less important at this stage because people don’t have established buying patterns or guidelines for the product segment. So, you have to talk about all the great things you can do now that you couldn’t do before, and tie into broader themes related to your product category. For instance, we tie into businesses moving to the cloud, and talk about backup as a best practice on premise and in the cloud.

Next, Figure Out Your Channels
Where do you believe you will connect with customers? Where will they hear about you? Where will they click through to go to your site? Where will they buy your product? Will they buy from you or from someone else? If you are a consumer product, you probably want to test some viral component, but we are primarily a B2B product, and backup is too boring to be inherently viral, so that wasn’t an option for us.

What we did at Backupify was run a lot of controlled experiments. In particular, we focused on 5 key direct lead gen experiments with 5 different sources, we experimented with the Google Apps reseller channel, we experimented with inbound (content, tools, etc), we experimented in the Google Apps Marketplace, and we experimented with cross product traction (a consumer version of Backupify that makes you think about a business version). Each turned out to have different advantages and disadvantages, and some didn’t work at all.

Focus on Your Cost to Acquire a Customer
Here is where I think a lot of startups make mistakes when going through customer validation. Too many focus on optimizing their funnel too early. In particular, they focus on visitor -> trial or trial -> paid conversions. Why? Because it’s more fun and internal facing to keep fixing your website or playing with your trial process. It’s like product work, and your early team was probably product centric, so they prefer it. If you do this, you are falling into the worst mistake that startup founders make which is doing what you like to do, or what you are good at, rather than doing what needs to be done.

Remember that your goal as an entrepreneur is to deploy capital effectively, and one of the most effective ways to use capital is to de-risk the business. This means investing in areas that help you learn about the market. The riskiest part of your funnel is the top of funnel, because that is the part over which you have the least control. Let me say that again. Focus on top of funnel the most, because that is where you have the least control. Your customer acquisition options are largely external and dependent on market structure, thus they are out of your control. Your conversion rates once users hit your site are primarily internal and under your control. If you find a scalable lead generation source, you can optimize later for visitor -> trial conversions or trial -> paid. Focus on figuring out what part of your customer acquisition costs are going to come from driving top of funnel. Obviously you will have to do some work on the site, building landing pages, etc. But 75% of your efforts should be on top of funnel.

Don’t worry about pricing at this stage. Don’t get hung up on gross margins. Don’t overanalyze all the pieces of your business model that you can optimize for later. Set a price, and focus on what it costs to acquire a customer because that cost is going to be a HUGE factor in how attractive your business model looks over the long term. In fact, I believe startups should understand COCA first, and build their business model around that later.

Test and Invest
This is the time at a startup where you can start to increase your burn rate a bit. It costs money to test customer acquisition, so don’t be afraid of that. At Backupify, we will allocate $10K - $20K to test a customer acquisition channel. Then if that channel is effective, we start investing more and more, slowly, making sure our results scale. This is ultimately what customer validation is all about. It’s about knowing that if I buy an ad at this place for $5000 and it generates $25,000 in long term customer value, then I still get a similar result at a $50K investment rate, or $500K, or whatever it is. You need to understand where you think your channels will max out.

How do you know if a channel is successful? We think of it in two ways. First, we have to do something, so back when none of our channels had attractive COCAs, we still invested in our lowest COCA channel, even though it was technically unprofitable. But as we ran more experiments, we measured them in two dimensions: COCA payback, and scalability. Those may not be the right dimensions for you. It depends on your product and market.

Optimize and Iterate
Once you find one or more channels to drive customers, then you can start optimizing the rest of your process. We have a certain target customer acquisition cost because we assume we can make it more efficient as we learn more and optimize everything else for that channel. And then, as the market changes and matures, you should revisit some of your old experiments and try them again, to see if they make sense.

How To Know When You Are Done
When you have iterated on your messaging, positioning, and funnel to optimize them for your best customer acquisition channel, you are ready to start scaling. This is where you invest more and more and make sure all your early results hold at scale. You should understand your metrics from top to bottom for this channel, and you should have a good idea how much money you can pour into it before these numbers break down from saturation. This is the point where you can finally build a reasonable revenue plan (even though your investors will ask you for one way way before this point) and start to measure yourself against the plan. As long as your are at or above plan and the customers are individually profitable, you can keep investing. For SaaS companies, investors usually want to see $2M - $3M in ARR before they feel confident you have validated your sales and marketing processes.

It has bothered me for a long time that so much is written about product/market fit, and not much is written about the next steps. Part of that is because the next steps vary more across business types than the early steps, but part of it is because customer development is overall relatively new, and not many companies have been through the customer validation phase. I hope this summary of what we did at Backupify is helpful. Feel free to email me with specific questions or comments.

Comments

3 Responses to “Customer Validation: What To Do Post Product/Market Fit”

  1. Nick Huhn on February 22nd, 2012 3:33 pm

    Customers? Revenue plan? I’m guessing Backupify might be an outlier in the startup world in that topics like this were breached before code was written. ;)

    I’m referring anyone that’s ever gotten stuck in the “Step 1: steal underpants; Step 3: profit” mindset to this post in the future. Thanks, Rob.

  2. laurence haughton on February 23rd, 2012 3:54 pm

    Great work Rob. It’s a pleasure to read someone with the discipline (and honesty) of an engineer tackle the subject of finding customers. It’s where I got started and I always felt marketers could stand to develop an engineer’s mindset.

    Only one minor disagreement. You say “part of it is because customer development is overall relatively new.” Scan the books of Claude Hopkins (from the 1920s). He and his disciples (Ogilvy for one) learned a lot in the first days of advertising that still applies.

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  • About Rob

    Rob is co-founder of Backupify.com. He likes value investing, the Rolling Stones, college basketball, artificial intelligence, economic history and people who think independently.