For years, broadband providers relied on a familiar formula for revenue growth: acquire new customers, bundle additional services, and steadily raise average revenue per user (ARPU) through product expansion. Traditional cable operators had a wide menu of upsell opportunities. Existing subscribers could add premium television packages like HBO or Showtime, purchase additional set-top boxes, subscribe to digital tiers, enable pay-per-view services, or bundle home phone lines alongside video and internet service.

Artificial intelligence has quickly become the most overused phrase in modern marketing conversations. It appears in boardroom decks, vendor pitches, and product roadmaps with a frequency that often exceeds clarity. For many organizations, the narrative is framed as a sweeping transformation: AI will revolutionize marketing, replace legacy systems, and render traditional analytical approaches obsolete. That framing, however, is not only misleading—it’s counterproductive.

Marketing automation has fundamentally changed the way marketers do business. To be able to schedule cross-channel campaigns that deliver on time and on target frees up a lot of opportunity for marketers to focus on things like strategy, creative, and feedback loops. Campaigns run with fewer resources, still generating and nurturing leads. But unlike the flawless “set it and forget it” reliability of, say, a crock pot, automation has its risks.

With the advent of big data, media mix measurement and optimization has become a required staple in the marketer’s toolbox. Effectively media mix measurement and optimization is comprised of seven elements:

In Part 1 of this series, we discussed how organizational objectives may change the implementation of a media mix and optimization platform. And in Part 2, we talked about measuring the efficacy of your efforts. Now, let’s talk about collecting and normalizing consumer responses and order/sales data.

In Part 1 of this series, we discussed how organizational objectives may change the implementation of a media mix and optimization platform. Once the objectives have been set, it’s time to formulate a plan around how to measure the efficacy of your efforts.

With the advent of big data, media mix measurement and optimization have become a required staple in the marketer’s toolbox. Effectively, media mix measurement and optimization are comprised of seven elements:

For those of us involved in some capacity in “the industry” – some who can remember as far back as wood-grain boxes that enabled users to watch twenty channels – we have confidently applied a name to the business: broadband.

It’s true digital has taken over a lot of our lives. Whether it’s the all-knowing computers we carry in our pockets, backup cams on our cars, or the way many of us have been doing our jobs for the last year+, digital is clearly integrated in our lives. But when it comes to marketing, digital hasn’t run off the other ways of connecting with customers.

As marketers had to double-down on creative solutions during the pandemic, change has been happening behind the scenes. Whether it’s doing away with cookies or the recent news that Nielsen’s audience measurement tools are being applied to Twitter’s video content, data use is shifting, always.