For our digital marketing campaign, we came up with a solution that put content at the forefront while integrating hard-hitting messaging that DIRECTV considered must-haves, like channel count and price point.

In our side-by-side posts, we aimed to feature the wide spectrum of shows and movies available to subscribers. No matter what you're into, DIRECTV NOW has options beyond options for every taste, style, mood, and whim.

We created a dynamic display campaign that would instantaneously piece together three main components of dynamic content and would be served to consumers based on declared interest or based the theme of the website visited. We defined four groups of TV show types, five offers and four different calls-to-action.

Mr. Mercedes is an AT&T original series based on the novel by Stephen King.

To promote the show and encourage tune in through DIRECTV NOW , we leveraged the show's most compelling asset: A serial killer named Mr. Mercedes. We created a hyper-targeted campaign across Facebook, Instagram and Twitter using various targeting criteria.

Our posts intercepted users with contextual messaging based on location, time of day and weather conditions. This amped up the tension, and gave them a sense of how it feels to be stalked and taunted by the serial killer. Hopefully, intriguing them enough to watch the show.

On Facebook, we scheduled posts for early morning and late night across the six different US time zones. Morning posts were served to users from 6AM-11AM and late night posts were served from 12AM-4AM.

On Facebook and Instagram, we were able to leverage users' current city and the geolocation of any recent posts or Instagram Stories. We developed creative that featured four main weather conditions: rain, snow, hotter than average, colder than average. Paired with local weather data, we served users the posts that corresponded most to their area.

On Facebook and Instagram we were able to target users based on any major event in their life. Any recent Facebook life event post was combined with a matrix of keywords that searched recent Facebook and Instagram posts. That data allowed us to infer if the user had recently become a homeowner, changed jobs, got married or was accepted into college.

On Twitter, we targeted users based on their tweet location. If a user was tweeting from one of the fifty major-metropolitan zip codes we designated, they would be served a promoted posts with their area in the creative. We even created 'generic' creative that targeted the locations of tourist attractions like Times Square or the Golden Gate Bridge.