Making online spend work in the long term

Is long-term thinking dying? The latest work for the Institute of Practitioners in Advertising (IPA) by analysts Les Binet and Peter Field contains some major warning signs. The IPA recommends that 40% of a brand’s marketing budget goes on activation; the rest should be spent on brand-building. According to their latest figures, in 2016 the proportion spent on activation is not 40% – it’s 72%. And Binet and Field says this has consequences. Effectiveness – defined as the proportion of campaigns in the IPA database which lead to very large business effects like profit gain – has begun to decline.

But marketers are not purposefully disregarding long-term profitable growth. They are faced with a precarious economy, a world in which more and more business happens online, and – crucially – a host of new digital metrics and data sources which make short-term activation-based marketing more transparent than ever before. These factors aren’t going away. From this side of the argument, the shift to short-term goals isn’t wilful blindness; it’s an evolutionary response to digital transformation.

So we’re in a truly fascinating moment for marketing. The big prize – long-term, profitable growth, is out there waiting to be claimed. But data-driven digital transformation is not reversible. The brands that win in the near future will be those who manage to find a way to make the shift to online spend work towards long-term profitability.

Take P&G, for instance. In 2016, chief brand officer Marc Pritchard made waves by pointing out that a lot of the company’s Facebook targeting had been ineffective. He got plenty of criticism for his stance, even though he was at pains to point out that the company was still committed to digital and to Facebook, it just wanted less waste in its marketing spend.

In 2017, P&G and Pritchard made headlines again, announcing that cutting back $140m in digital spend had made no difference to the bottom line. Again, he was careful to state that this wasn’t any kind of retreat from online content – P&G had simply worked out which parts weren’t effective.

P&G has the right idea. The brands who are going to handle the current moment best are the ones who neither run from online spend nor dive gung-ho into it, but who understand that the best way to balance brand-building and activation is to aim for profitable growth with zero waste in their online content.

The next question is, how? I believe the answer is to look again at content testing. In recent years it’s felt like testing hasn’t found a place in the conversation around content marketing, and our industry has been partly at fault there.

The fact is, the instant, concrete behavioural data of clicks and views felt more real to marketers than the more abstract, slower data created by comms tracking and copy testing. And in a world where brands produce and optimise online content in quantities yesterday’s advertisers could barely imagine, testing methods didn’t keep up.

But for predicting long-term profitability, testing works.

We already know the route to the most accurate predictions of long-term impact. Binet and Field proved back in 2008 that emotional campaigns are the most effective for business growth. In the wake of their findings we’ve seen more and more brands embrace copy testing which centres measuring emotional response to an ad – the best predictor of long-term impact.

The answer is to give marketers data that accurately predicts long-term impact on profitable growth, but with the kind of speed and agility marketers have become used to from short-term online analytics. With accurate predictions of long-term profitability working in tandem with metrics for short-term effectiveness, brands can make clearer decisions about seeding and investing in content and avoiding waste. They can also build on the content most likely to drive long-term profitable growth.

The idea is to create an ad tracking solution which moves at the pace of the digital age while offering the kind of long-term strategic insight that analytics leaves out. This is possible, but only if you automate testing as much as possible and test in bulk to leverage economies of scale. Researchers need to embrace speed and scale, for example building a platform that tests every piece of online video a brand and its competitors produce, and rapidly delivers predictions of its long-term impact.

Speed and scale are only barriers to predictive testing because the insights sector has traditionally worked on a slow, project-by-project basis when it comes to testing copy. Those of us who believe in long-term effectiveness must aspire to the agility and rapid decision-making that have enabled the rise in short-term thinking. Only then will we be best placed to help our clients achieve the goal of profitable growth with zero waste.

Tom Ewing is senior director, Labs at System1 Group