The best marketers experiment every day

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Here’s a statistic to give marketers pause: Google, Meta, and Amazon took in more than 74% of all global digital ad spend last year. That’s a lot of money chasing after the same consumers in the same place.

So how to stand out? There is still too much uncertainty about what works and what doesn’t and which channels are best for which messages. Indeed, to get the most out of each channel, marketers need to experiment – ​​a lot. You must constantly test and learn; test different messages, test different landing pages, test different designs, and find out what works to inform your tactics.

And even once you find what works, you need to keep testing to keep up with changing consumer tastes, the competition, and the online ecosystem at large.

Experimenting so much seems radical. It’s not

It is essential. In all of my work with businesses, agencies, and brands, the biggest predictor of campaign success is the use of rapid experimentation and real-time measurement. What determines whether you are going to get the most out of a channel or not is directly related to the frequency of your experiences and how you can measure them to synthesize the information. Iteration matters more than your budget, your time, or even your creative resources.

When you invest in Google or Facebook for example, you can compare them to each other in a rudimentary way. The question of which got the most impressions, the most clicks, and the most conversions is very easy to answer.

But if you want to get the most out of your investment in each advertising channel and control variables (e.g. which message, which targeting, which time of day, which creative and which tactic worked best), you can’t. just stop there; you have to dig deeper. You need to be able to ask more detailed questions, compare different segments, and deploy multiples of the same campaign, with slightly varying parameters.

The most successful companies launch campaigns daily

Or more precisely, they launch new experiences every day. And the more experiments they run, the more they learn about what works and why.

A large European car manufacturer, for example, was able to increase its conversion rate by 30% compared to its immediate competitor thanks to rapid tests and measurements. And when you’re spending millions of dollars a year, 30% better utilization of marketing budgets is a serious competitive advantage. In another case, a marketing agency was able to spot an opportunity for a better distribution of the budget among all of its clients. While it would typically take weeks to test a hypothesis on such a large scale, an experiment-driven design and modern data stack architecture allowed them to validate the hypothesis in a day.

One reason most companies can’t do this yet is that their marketing teams are simply not structured to iterate, experiment, and analyze data. Another, as the agency’s test suggests, is to implement relevant data stack architecture to make a difference.

A 2021 survey of over 1,700 marketers found that more than 88% say they spend most of their time on reporting tasks, including tracking performance, creating competitive analysis and production of audience information.

While the most obvious conclusion is in the team design and workflow prioritization aspects, we also need to consider the huge amounts of marketing data within organizations. Again, this is primarily about how you manage data – a backbone for further workflow improvements. You can choose to hire marketing data analysts, but even that adds to a marketing budget, narrowing your revenue streams.

A change is coming

Enterprise IT is quickly finding more efficient ways to manage marketing data from multiple sources and present rational insights through no-code or low-code data aggregation tools. This gives more immediate insights, more responsive campaign experience, and a clear picture of what it takes to create more consistent revenue streams.

The best marketers are eager to seize the opportunity presented to them. Namely: create a team and data environments suitable for experiments, move from tracking and reporting and back to creating and experimenting for higher conversions.

Nikita Bykadarov is Vice President of Demand Gen and MarTech for Improvised

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