In the dark days before digital media took the biggest chunk of every ad budget, inventory was purchased directly from media owners by brands and agencies. In those pre and early digital days of yore, an IO was king and advertisers had no visibility on the performance of their campaign, other than an estimation of the activity trickling through to their own end. ‘Tear-sheets’, VHS broadcast tapes and screenshots were the standard of proof for campaign execution and emails between client and media was about as digital as it got.
“half the money I spend on advertising is wasted, the trouble is I don’t know which half”
Then, digital media promised to eradicate the sentiment in this quote from early retail titan Sam Wannamaker. Digital spend has grown like crazy due to increased usage and the promised land of targeting and measurement. Advertisers currently spend around $150 billion on digital ads each year. But fast forward from the early days of media planning and the advent of digital media 10–15 years ago. Has much actually changed?
Advertisers continue to plan campaigns as if the good old days of Print & TV were still here. Identify a persona corresponding to a product and then plan the media investment based on market knowledge, experience and intuition about the best way to target that persona.
Launching an expensive new phone? It probably makes sense to target it at people who consider tech and gadgets a status symbol. Therefore the best target are high earners and the media should be finance publications and serious, broadsheet newspapers… right?
Most campaigns still operate such a ‘spray and pray’ approach. A dive into the unknown. A hope that campaigns perform and if not, they can always be ‘optimized’ to achieve the given KPIs. This describes the vast majority of digital campaigns, ‘optimized’ ad-hoc by humans. Decisions are based on small pockets of data, interpretation and intuition.
This approach is inherently wrong. It isn’t based on whether the targeted users are more likely to buy the story. This is 2020. Applying gut-feel and intuition to marketing spend no longer makes any sense. Such an approach isn’t based on hard facts, and by working in this way, advertisers lose anywhere between 10% to 30% of their spend efficiency.
We’re not saying this approach lacks merit. Brands, media buyers and agencies certainly possess a wealth of insight and experience. What we are saying is that it could be so much better. The data is laying there, waiting to be peeked at.
Programmatic media trading provides access to a crazy amount of data, delivering the ability to analyze consumer’s online behavior. It’s a shame it isn’t used more. It is actually quite easy to find users matching a target persona within the programmatic landscape and uncover their unique online behavioral patterns.
For example, the phone advertiser described above could discover that people who want to buy these phones are also people who listen to urban music and/or look for micro loans to purchase electronics. Most likely they’re not high earners working in finance and reading about South American geopolitics. The advertiser can therefore adapt their targeting strategy based on intent and likelihood to purchase.
They could also uncover many mid/long tail websites, content and keywords, available at a much cheaper rate than the premium publications in the intuitive target persona. This saves costs without impacting performance, which in turn significantly improves ROI.
A data-driven approach to media planning allows advertisers to discover strategies that will perform from day one, instead of ‘testing’ and ‘optimizing’ strategies for weeks or even months trying desperately to achieve the original KPIs.
Because it’s insane and actually quite scary to think that by following their intuition, advertisers are effectively wasting anywhere between $15 and $45 billion each and every year.
By failing to prepare you are preparing to fail
It’s about time we jump start the era of data-driven media planning. It’s about time we play the advertising game with all the cheat codes.