How To Stop Marketing Like It’s 2007

Feb 15, 2017

First, there were horse and buggies. Then along came the Model T car. And now, we’re developing self-driving cars. (Though we are still years away from the flying cars promised to us by The Jetsons.) As technology improves, we expect better performance and features from our consumer products.

This is even true for marketing. Over the last few years, martech has advanced rapidly, especially in the realm of eCommerce. For every problem, there seems to be a point solution. Want to offer product recommendations to browsing shoppers to improve CTR? There’s a solution for that. Want to email customers about the items they abandoned in their shopping carts? There’s a different solution for that.

Most companies only handle one or two of the issues at a time, which has meant that many businesses have had to use a multitude of different vendors. This has resulted in “vendor bloat,” confusion, and data from one test or action being siloed off from the others, making it harder to execute marketing campaigns that are integrated across them. There are 3,874 marketing technology solutions listed on the 2016 Martec.com Landscape Supergraphic and the average marketing stack consists of 17 platforms.

The growing marketing stack has also presented a massive data challenge. Rather than residing in one platform, information on user behavior has been stored in silos. As a result, marketers have been losing countless hours just trying to make sense of disparate data.

All of this makes it seem like marketing has gotten more difficult, not easier, as the technology has improved. And that has been sort of true, at least until very recently. With the emergence of SaaS solutions (like Dynamic Yield) that handle all elements of onsite experience, user data from across touchpoints can be collected in one place (read further about omnichannel audience sharing). The result will be less time collecting information and more time personalizing experiences based on it. This will make marketing easier, not harder, in 2017.

In addition to integrated platforms and data, the simplification of marketing will be enabled by machine learning, which will both automate and optimize manual processes that have cost marketers valuable time and resources.

Gone are the days of running manual A/B tests, analyzing data and then serving the variation that drives better results. Machine learning algorithms can dynamically allocate traffic to winning variations based on any KPI, even as user behavior changes over time. But machine learning will move far beyond just testing, powering more precise personalization, better recommendations and more targeted consumer messaging. Automated optimization will handle more of the complex science of marketing, leaving advertisers more time to work on the art.

While marketers can’t exactly fly the plane, so to speak, on autopilot, these technologies mean they will have more time to relax in the cockpit in 2017.

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