Marketing automation and big data have had huge impacts on the marketing world. Both are hot trends right now and both will continue to grow as technology evolves and marketing becomes more complex.

Automation is a staple for any online marketer. And some form of automation tools are required for any company that wishes to stay competitive.

The Impact of Automation and Big Data on Marketing

Algorithms are driving many facets of online marketing. Here are some common uses for automation:

  • Data mining
  • Website updates
  • Social media updates
  • Automatic responses to email, social media, and comments
  • Automated media buying
  • Automatic advertising campaign optimization

Any company that competes in online spaces need automation to keep up with the curve.

Media buying, for instance, refers to the practice of negotiating prices and purchasing ad space. In the past, this was done by humans, but with the advent of information technology, this task has passed almost completely to computers.

Sophisticated automation tools such as promotion platforms handle tasks that would otherwise be impossible. Calculating ROI and LTV, for instance, has become a serious challenge for mobile marketers trying to juggle a dozen ad campaigns on two dozen networks.

These automation tools are necessary, and the same goes for big data. Before the internet, much marketing data were was left to speculation and extrapolation, but now we have access to detailed consumer information that allows for extensive data mining. This data can be used to develop deep customer profiles, psychological profiles, lifestyle profiles, and marketing profiles. Responsive, personalized, and targeted marketing campaigns are becoming the norm, thanks to both automation and big data.

Marketers who don’t take advantage of both will miss out and lose a competitive advantage. But each of these marketing tactics have their drawbacks.

Criticisms

Critics of automation and big data have claimed that they can be harmful in large doses, and that neither one can replace humans. Over-use of automation, for instance, comes across as artificial. Studies have shown statistically significant decreases in conversion rates when companies use automated social media posts versus human-created posts. Putting a real person with a real photo and a real name behind online interactions, however, has shown to have the opposite effect.

Big data, likewise, has criticisms, but for different reasons. This brand-new field come under fire as being inherently biased or even inaccurate. As with statistics, it is possible to use any mathematical model you wish to derive results, and certain big data companies have been criticized for creating biased analyses that produce the numbers they want.

So does that mean you should avoid using them at all? Of course not. As with anything, moderation is key.

How to Use Both

The best uses of automation are behind the scenes. Algorithmic media buying and automated advertising optimization are necessary automation techniques.

Realistically, data mining can only be accomplished with automation tools. But automating interactions that should be human-to-human, such as social media interactions, usually evokes a negative response. The best way to automate, then, is by automating the back end, not the front end.

As mentioned, big data is like statistics, and when using big data in marketing, results should be the determiner of success. In other words, if an analysis produces results, then keep it up. But there should be a clear causal relationship between the input and the output.

The less concrete and more complex big data analyses become, the more abstract they are and the more difficult it becomes to prove a firm relationship between the analysis and the results. “Vanity metrics” are numbers that look good on paper or on screen, but don’t actually have a demonstrable connection to conversions, sales, or the bottom line. Worst case misuses of big data involve misrepresentation of big data outcomes.

In both cases, separating the hype from the reality is key to successful implementation. Automation won’t solve all your marketing woes and neither will big data. Both are useful and even necessary back-end marketing tools in the ever-changing marketing world, but they should be used with care.

An algorithm, equation, or analysis is only as good as its design, and humans should be the ones to design those algorithms. They cannot design themselves, so they cannot evolve or adapt to changing circumstances.

If big data and automation feed the back end, then humans should work in two places: building the back end and manning the front end. Customer support, technical support, and social media interactions shouldn’t be hidden behind automation.

To stay ahead of the curve, stay up-to-date with the latest developments in big data and automation.

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