How the Convergence of Marketing, Ad Tech Led to Richer Data Insights

Channels like social media can now provide detailed, actionable data points within hours. Marketers can now move quickly–provided that they’re willing to use the data that is now accessible.

Marketers spend most of their time on marketing strategy, budgeting and planning–processes that require collaboration across business groups to analyze consumer data and insights. Traditionally, this cycle of moving from strategy to execution took weeks and possibly months of refinements, all based on limited data points.

This practice is still commonplace today, but it doesn’t have to be. The marketing landscape changed significantly in 2015. Channels like social media can now provide detailed, actionable data points within hours. Marketers can now move quickly–provided that they’re willing to use the data that is now accessible.

To better grasp what’s possible, let’s first examine four key shifts that occurred in 2015 that are shaping the marketing landscape of 2016.

  • Data sources merged: A slew of companies, ranging from multinationals to startups, helped aggregate data from different sources, including customer-relationship management, third-party data, device IDs and cookie pools. This development allows companies like Facebook to “deterministically” target mobile devices through its ecosystem while maintaining consumer privacy. Meanwhile, companies like Drawbridge and Tapad can do the same “probabilistically” for rest of the digital ecosystem.
  • Marketing tech acquired ad tech: Salesforce, Adobe and Oracle all acquired and/or continued to build more third-party data and ad-tech media buying stacks.
  • Big data became standard: Technologies like data-management platforms became commonplace, allowing advertisers to learn from the Twitter and Facebook feeds, blogs and the open web.
  • Social blurred customer service, CRM and marketing: Twitter and Facebook added capabilities, such as bots for Messenger, which allow marketers to interact directly with consumers. At the same time, they have learned to better use organic posts, social likes and comments to inform their marketing efforts.

These four moves all made in-depth data available to marketers and deepened the level of consumer understanding. Of course, consumer insights, preferences, interests and behaviors are moving variables. Hence, a combination of speed and multiple data sources is extremely relevant for marketers looking for actionable insights that can be applied for fast media execution.

In the past, I managed a marketing strategy project for a Fortune 500 financial services company that involved focus groups. This was in 2007, and it took several weeks and thousands of dollars to organize the groups, aggregate and analyze their feedback and then prepare the insights. The kicker was that this was for a housing and mortgage company–by the time all of the focus group and other primary research was completed, the housing market and consumer outlook had started changing dramatically.

In contrast, Facebook, Twitter and Pinterest audience insights are both deep and current. As users spend time on social networks, their interests, attitudes and behaviors are automatically updated, which solves the problem of tracking moving variables.

For example, as soon as I liked the Marine Corps Marathon page in 2012, marathons and related sports activities become part of my personal attributes. In 2013, I posted a picture of running the race, which made my interest in marathons even more specific. Overnight, I became a target for sports brands like Asics, Nike and Gatorade, to name just a few. On the contrary, focus groups or surveys would have taken weeks or months to statistically infer my interest in running, and wouldn’t know that I had actually run the marathon after taking their survey.

Insights are one thing, but they need to be applied to media execution, which largely used to be a black box for marketers. Once marketers develop the campaign messaging and creatives, external agencies or in-house media buyers would spend an allocated budget to target customers and bring back ad performance statistics. Today, ad-tech (programmatic, social, etc.) puts media performance insights at marketers’ fingertips so they can monitor, in real-time, which messaging (ad content) is resonating best with what type of consumer segment, and how that leads to sales.

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