5 metrics to measure and test innovation

Betting on the next big thing

To make innovation happen, you need a system for making lots of small, unsafe bets – and measuring the results.

By Steve Glaveski

The disruptive innovation theory, penned in 1997 by Clayton Christensen in his seminal work The Innovator’s Dilemma, describes a process by which a product takes root in simple applications at the bottom of a small market and moves upmarket, eventually displacing industry incumbents.

We live in Christensen’s world – a world where small companies are regularly disrupting industry incumbents with more than 1000 times their resources.

Traditional metrics, such as net present value and internal rate of return, help finance to communicate with stakeholders. Such metrics, though, favour short-term wins, shareholder demands and performance bonuses, rather than longer-term growth.

These pursuits only ever serve to stretch our existing S-curves but don’t help us capture the next S-curve – the one that will help us survive.

Failing to catch the next S-curve

The phone industry's s-curveAs the graph at the right shows, Nokia’s high-quality “feature phones” sent revenues skywards in the early 2000s, but the company imploded after 2010 as Apple’s full-screen iPhone took over the market. Kodak, Blockbuster and others perished for much the same reason in their respective markets.

If I’m a product manager with an idea pitching for funding, however, I need to demonstrate the projected return on investment. It’s impossible to forecast revenues for products that don’t exist yet. So how do we measure our innovation activity?

How to overcome this challenge

Innovators are in the business of making unsafe bets – safe bets generally aren’t innovation at all. Apple made a big, unsafe bet with the iPhone, and bets such as that often don’t pay off. 

To successfully explore disruptive innovation, most companies will want to create an environment that supports lots of small, unsafe bets. We want to allocate relatively insignificant amounts of capital to a portfolio of ideas, look at how customers react and then make educated decisions on what to keep funding. Innovation metrics are part of this task. 

You might recognise the following approach as Dave McClure’s funnel metrics approach, popular with start-ups, or what Ben Yoskovitz, co-author of Lean Analytics, calls “the one metric that matters”.

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5 innovation metrics and how to test them

1. Rate of acquisition

Do people care enough about an idea to act – for instance, by clicking through from an ad to a website?
How to test: Run ads on platforms like Google and Facebook targeting your customer problem. Count your clicks per 1000 impressions.

2. Rate of activation

When people find out a little about what you offer, will they take a proactive step such as leaving an email address?
How to test: Create landing pages with copy, imagery and a compelling “call to action” button to sell the solution. Count your button clicks per 100 visitors.

3. Rate of conversion

Are people willing to pay for your product or service?
How to test: Display a price point with a “Buy Now” button. Count the clicks on “Buy Now” per 100 visitors.

4. Rate of return

Will people come back for more?
How to test: You can use Google Analytics to track the percentage of new versus returning visitors, monitor email engagement with Mailchimp or track individual user engagement with Kissmetrics.

5. Viral coefficient

Do people refer you to their friends and family?
How to test: Referral programs such as InviteBox and ReferralCandy help you track the number of invited and converted users.

How do you define success?

Success depends on factors such as cost structure, lifetime value of a customer, risk profile and a healthy dose of “gut”.

Expect to fail – but fail small and learn valuable lessons along the way. Tesla founder Elon Musk correctly points out that “if you’re not failing, you’re not innovating”.

Today’s climate favours small cross-functional teams with a relentless focus on defining and solving a customer problem. It particularly favours teams that experiment and measure and constantly adapt their products and business models to deliver what wows customers.

Steve Glaveski is co-founder of Melbourne-based innovation consultancy Collective Campus.

Read next: How the S-Curve delivers personal success

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