Without data to support decisions, you may be simply guessing what is happening. Worse, you may even be falling for confirmation bias where you analyze or interpret results in a way that validates your strategy.

Making key strategic decisions in business without data is akin to driving blindfolded. Dangerous and even deadly.

So how can you use data to support better decision-making?

The key hack here is to use A/B testing. A/B testing in its simplest form is where you split test two different scenarios. For example, imagine your ice-cream shop has Marketing Campaign A using a direct mail campaign with a unique voucher to be presented physically at the counter. Marketing Campaign B might be to conduct a social media campaign with a discount code for digital download to be scanned at the counter.

Conducted parallel, you can measure the performance of campaigns A & B based on cost, sales and margin by measuring take-up by customers.

Of course, there could be any number of these parallel tests A,B,C,D etc to measure which activity results in the highest return on investment.

As you run your beta-tests in the background and collect data, you can then tweak strategy and future execution to optimize results.

This creates a continuous feedback loop that is only limited by your imagination and execution around campaigns.

Adopting a mindset of curiosity and running trials, creates a low-cost internal marketing machine.

I recently read a fascinating book by leading economist and thinker John List titled The Voltage Effect, where he spent time in the early years of Uber’s meteoric rise, testing and building their algorithms.

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