Case Study: AMC Networks

Where does AMC Networks get its audiences?

AMC Networks discovers what makes viewers want to watch the shows they create. IBM Analytics helps them:

  • Generate insights from audience data in seconds, when before it could take weeks.
  • Adjust their marketing plans by as much as six weeks before a new show airs.
  • Reallocate as much as 30% of their ad inventory into other growth opportunities.

01

Overview

How do you capture new viewers in today’s fragmented world?

Where, when and on what kind of device content is watched has changed. As audiences’ viewing habits shift away from what’s traditionally referred to as “television,” AMC Networks realized they needed to get smarter about how they capture new viewers, better market their content and optimize their advertising inventory.

02

Challenge

Time, extra costs and limited access to data adds up to missed opportunities

To analyze viewership data generated from fragmented audiences in this multi-platform, multi-business world takes a lot of time, money and resources. In fact, AMC Networks’ Business Intelligence team were spending 80% of their time evaluating audience data and only 20% doing actual research, making it difficult to uncover the insights they need, when they need them.

03

Solution

IBM Analytics gave AMC Networks the ability to pull insights in seconds

IBM Analytics helped AMC Networks reverse that stat — now they spend only 20% of their time analyzing audience data and 80% uncovering insights that make significant impacts on their business. Decision-makers across the entire AMC organization can pull meaningful insights from ratings and audience data in-house almost instantly — a task that used to take days and even weeks.

04

Impact

Deeper insights at speed have allowed AMC Networks to better market and predict the success of their shows

The democratization of data throughout AMC Networks, combined with the speed of IBM Analytics analyses, lets AMC Networks uncover game-changing audience insights from trillions of rows of data, when they matter most. Insights that help them:

  • Predict a show’s performance 12 months before it premieres
  • Adjust their marketing plans by as much as six weeks before a new show airs
  • Optimize their reach, CPM and frequency distribution of their own ad inventory
  • Share deeper audience learnings with their advertisers

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