A lot of companies wait too long to monetize using the argument that they need scale. This is true for some businesses but the extent of scale needed is often exaggerated.

In general, the long awaited monetization products fall short of expectations. Google is the one example everyone points to. Google took it’s time and released a lightening in a bottle revenue product.  But Facebook and Twitter? I give their monetization engines B/B+ grades. As I’ve noted, the size of your user base is inversely correlated with the quality of revenue product you need. Twitter and Facebook have huge user bases so even so-so revenue engines will throw off hundreds of millions or even billions.

But what if they had started sooner and experimented? And what would happen to you if you built your business on the delay revenue experimentation argument and only got to hundreds of thousands oir millions of users. You might not have the runway for subpar revenue products.  Your user number might not be so high that your revenue product can be average.

Also, not all businesses have network effects to the extent Facebook and Twitter do. For most businesses, scale can come at 10s or 100s of thousands of users.

At a startup’s earliest days, product proceeds revenue. But how long do those early days go on for? And if you’re ignoring monetization on the grounds you need to get to massive sale, and claim you are just following Google, Twitter, and Facebook – that is an all in bet.  Mint is a good counter-example, their user numbers got into the millions; awesome and huge, but not super huge.  However, their monetization strategy (look at your finances and offer relevant financials products) is nuanced and ultra-targeted.  Mint’s revenue product is an A.

I think many companies are afraid that, “revenue kills the dream,” and deny themselves the same flexibility to experiment in revenue generation that they do in consumer features.  And the same rules apply, you wouldn’t piss off your users will annoying features but you can still experiment; I think the same goes for revenue features.

You might want to hedge by aiming somewhere in the middle of the inverse correlation between user base size and quality of revenue product.