Andrew Chen Archives

Measuring value created rather than optimizing for yourself
In my last blog post, I talked about the idea that value creation generates revenue, traffic, and other metrics, not the other way around. This is a particularly interesting idea to implement because it goes against much of the standard analytics reports that are out there.

The reason is that ultimately, most metrics tend to focus inwards, on self-interested gain, rather than outwards on the value you’re creating for your customers. Let’s take a couple examples of inward-focused metrics that people often cite:

• account registrations
• pageviews
• unique visitors per month
• revenues

I’m sure you measure many of the above, as I do as well. It’s OK to measure this stuff, but if you start to optimize for it, you are starting to focus on the business of value extraction, not value creation.

Measuring # of life preservers sold versus the # of lives saved
Thus we come back to the title of the post. Most people are using standard analytics packages that are commoditized to focus inwards on metrics like pageviews and revenue. To use an analogy, that’s akin to the idea of measuring the # of life preservers that you sell, and trying to optimize for that, rather than optimizing for the benefit, which is the # of lives saved.

If you focus primarily on selling life preservers, then you’ll tend to do all sorts of stuff like:

• making them cheaper to build
• adding doo-dads to them that are flashy to customers
• using aggressive sales tactics
• etc.

These things might generate revenue in the short to medium run, but if you prioritize this at the expense of actually delivering on the product benefit, then that’s a bad optimization in the long term.

Now contrast that to the idea of trying to save as many lives as possible. You might still want to make them as cheap as possible, so that every ship in the world can have as many of them as needed. You might still want to add upgrades to them, but only if they help save lives. etc. While these changes may be similar in execution, they are different in spirit than the changes you’d make when optimizing for sales.

Introducing “Benefit-Driven Metrics”
So ultimately to start this exercise, you should throw out all the standard metrics (conversion rates, pageviews, etc.) and just focus on one thing:

What are your customers measuring?

By looking at how they define value, then you get yourself aligned to them as closely as possible. Answering this question sets your company up for value creation, which then unlocks the ability to gain something from that value, then you have to start here.

I’ll deem these quantitative measurements as “Benefit-driven metrics.”

How do you measure it?
Here’s the interesting part – everyone’s benefit-driven metrics will be completely different, because most people’s customers and value proposition and product are ultimately very different. Unfortunately, you don’t have the crutch of standardized numbers like pageviews or uniques to lean on.

But let me give you some examples for reference:

For dating sites:
Why do customers join dating sites? To find their soulmates. Thus, measure the quantity of successful matches you make, not the lifetime value of the customer. Focusing on LTV can easily lead you to do things like creating fake accounts to make people come back, or optimizing it so that they find their best matches several months down the line, or trying to get everyone to pre-pay for the service rather than making the product experience awesome.

For marketplaces:
Why do customers sell on a marketplace? To make money and get rid of their stuff. Why do customers buy on a marketplace? So that they can get things cheaply and quickly, and are happy with their purchase. Thus, measure the quantity of how much your sellers take home, and how many buyers are happy with their experiences. Contrast this with overfocusing on listing fee revenues, which might get you into a spiral of raising prices rather than creating the best commerce experience.

For social networks:
Why do customers use social networks? To “connect” with their friends – let’s boil that down to communicating (though it’s obviously much richer than that). Then ideally, you might want to focus on the number of messages/comments/posts that end up getting replies from their friends. If you overfocus on something like user registrations, then you might get a ton of users, but maybe they won’t be getting to experience the benefits of the product.

For online publishers who sell to advertisers:
Why do advertisers buy ads on websites? To generate traffic to their own sites, which in turn leads to revenue. In this case, you should quantify the amount of revenue you generate for your advertiser customers, or at least the number of conversions they receive. Contrast this with the approach of measuring and optimizing your own CPMs as a publisher, which results in potentially delivering a lot of crappy traffic to advertisers who will drop their payments in the long term.

Special note for ad-driven startups :-)
Now ad-supported startups have a particularly interesting issue in this, because I keep using the words “benefits” and “customers” and perhaps it’d be easy to think this refers to the users of the product. But maybe not, as I’ve outlined before in Your ad-supported Web 2.0 site is actually a B2B enterprise in disguise. The reason is that your customer may actually be the advertiser on the site, not your user!

And in fact, if you overfocus on pleasing your users to the detriment of your advertiser customers, which is very easy – then that leads to very bad things.

Start this benefits-driven approach now, not later, so you can learn the right things
Finally, I want to emphasize that I believe it’s important to start thinking about these benefit-driven metrics from the beginning of your business, not later. The reason is that every learning that a startup makes is often hugely applicable to a specific context, but not at all applicable to other variations.

If you’re going to start a website that churns users like crazy but hits massive user goals, you will build an entire organization to optimize for those metrics. And once you’ve gone far on this, it’s not clear that you’ll have the DNA, the technology, the ideas, or the willpower to execute in a different direction.

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