Inch by inch, bit by bit: using Big Data to measure marketing ROI
By Eric Benjamin Seufert, Owner, Heracles
As a consultant, I often see executives at client companies run into two distinct but related dead ends when considering a specific marketing campaign:
- That a campaign looks promising, but we can’t measure it with our existing infrastructure, and we only run campaigns that we can properly measure, attribute, and calculate ROI for
- That a campaign looks interesting, but since we can’t measure it, we can just lump the expense into “brand engagement / extension” and not worry about ROI.
Neither of these lines of thought is ideal. The former leads to companies clinging tightly to a narrow range of marketing channels, all of which will experience a diminishing rate of return over time, leading to loggerheads within the organization: we can’t grow because we can’t spend money on our portfolio of existing channels, but we can’t extend our marketing capabilities to new channels because we have no way of calculating ROI for them.
The second is worse and generally produces a toxic political climate in an organization. ROI is marketing’s north star: without gearing all marketing activities to ROI, marketing becomes an expensive vanity program for a company: a series of parties, sponsored events, partnerships, and stunts that produce introducing Instagram feeds for the company’s marketing employees but little or no revenue.
Every company on the planet now has the opportunity to connect with customers via social media, especially on mobile, which is probably the closest thing to a unifying experience that humanity has ever known. Whether your game is digital or not, you have the ability to reach, engage with, and track customers on mobile now with a high level of precision. Wading into this dynamic, fast moving world isn’t always comfortable, especially for marketers that are used to running a certain type of campaigns, but it’s highly lucrative.
And what’s perhaps even more exciting about the shift to mobile is that the biggest social media companies are doing much of the heavy lifting for advertisers in terms of targeting and measurement. Facebook, and to a lesser extent Snapchat and Twitter, are able to help you create custom audiences, use your own proprietary targeting data, and track users throughout their journey with your product. It’s in their best interest to do so: the more value you get out of campaigns run on their platforms, the more you’re likely to spend with them.
The presentation I recently gave at the European Lotteries Conference in London emphasized the fact that “big data” in marketing is mostly used to connect the various channels that marketers use and, via internal analytics infrastructure, create a single version of the “truth” concerning ROI. Email, social media, video, and even out of home: with enough effort invested into systems and data architecture, all of these channels can be stitched together into a single marketing framework to help you grow your lottery game, whether it exists online or only on the counters of convenience stores.
And increasingly, doing this — building out a business intelligence infrastructure that can accommodate these myriad, varied customer acquisition and engagement channels — is an organizational imperative. Customers live everywhere: if you’re not creating touchpoints for your existing customers or trying to reach new customers on mobile video, or with email campaigns, or in the retail setting, then you’re giving your competitors ample chance to do so uncontested.
Operating across every possible channel and not just the ones you’ve always operated on, with a model that allows for ROI to be calculated on advertising spend, is a strategic challenge that touches every part of the organization, not just marketing. But it’s marketing that bears the brunt of the responsibility for ensuring that the company is reaching every potential new customer, and so it’s the marketing team that must lead the charge into unchartered waters of customer acquisition. “We’ve never run advertising on that channel” is no better of an excuse for a marketing team to use than “We ran that campaign without worrying about ROI” — if the analytics needs of a campaign dictate how much money can be spent on it, then the marketing team must make sure that those analytics needs are met.
“Big Data” as a concept is actually pretty easy to deal with — in fact, lots of data usually lends itself to simple methods of analysis. What’s difficult to organize and use is “messy data”: data from lots of different sources that doesn’t necessarily fit together well. While the big social media outlets do a lot to make messy data useful to advertisers, it’s still important and obligatory for marketing teams to find ways to tie all of their campaigns together in a way that helps utilize new marketing channels while still focusing on ROI.
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- Une campagne semble prometteuse, mais nous ne pouvons pas la mesurer avec notre infrastructure existante, et nous ne lançons que des campagnes dont nous pouvons correctement mesurer, attribuer et calculer le ROI.
- Une campagne semble intéressante, mais comme nous ne pouvons pas la mesurer, nous pouvons simplement attribuer la dépense sous la ligne « engagement/extension de la marque » et ne pas s’inquiéter du ROI.
- una campaña que parece prometedora, pero que no podemos medir con nuestra infraestructura actual; y nosotros solo lanzamos campañas que podamos medir y asignar, y para la que podamos calcular la rentabilidad de la inversión [en inglés, Return On Investment (ROI)] de forma adecuada;
- una campaña que parece interesante, pero ya que no podemos medirla, solo podemos meter el gasto como “expansión/compromiso con la marca” y no preocuparnos por el ROI.
- Dass eine Kampagne vielversprechend aussieht, aber wir sie nicht mit unserer bestehenden Infrastruktur messen können, und wir nur Kampagnen durchführen, die wir für das ROI richtig messen, zuschneiden und berechnen können
- Dass eine Kampagne interessant aussieht, aber da wir sie nicht messen können, können wir einfach die Kosten in „Markenengagement/-erweiterung“ zusammenfassen und müssen uns nicht um das ROI sorgen.
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