An Introduction to Paid-Owned-Earned Media

Marketers employ a plethora of media channels to facilitate the dissemination of brand information to consumer buyers. In more contemporary times, these channels are considered to fall into three categories of paid, owned and earned media or POEM. In paid media, the media channel is merely ‘rented’ from channels owners at rates that are negotiated in advance. Examples of Paid media include the traditional mediums like TV, print, radio, OOH and also a growing focus on online platforms like SEM Impressions, banner ads, and Pre-roll impressions. Media channels and brand content that marketers own, like websites, newsletters, catalogues, blogs and social media accounts, are termed ‘owned media’. They not only facilitate brand communication but also foster consumer engagement. Brand presence within media, without having to pay for its use, is classified as earned media. Customers are encouraged and often empowered to create and publish content on behalf of the brand. It is this content, emanating from consumers, prospective consumers and others interested parties that create ‘buzz’ and word of mouth for the brand. Earned media traditionally was classified as PR generated by the brand but with the advent of social media, there has been an increased focus by brands to connect with their target audience on social media and SNS platforms.

• Motivation and Objective

  The elements of POEM or Convergent Medium interact continuously among themselves and the marketer is faced with a 2-fold challenge of:

  • Estimating the relationship between the elements of POEM – both direct and indirect relationships

  • Establish synergy premiums that are due to the synergistic effects when two media and used concurrently.

• Methodology

  POEM analysis is a 2-step process.
  Data Understanding – the study of trends in variables and their interactions with each other.
  This is done using Bayesian Networks Modeling – to estimate and quantify the impact of inter-relationships of elements of POEM on key marketing indicators like sales, market share and mind measures such as awareness and intention to purchase scores. This is done through Vector Auto Regression (VAR)

• Hypothesis

  • New Users

  • Existing Users

  Media Inputs
  

  • TV GRPs - PAID

  • Print (data on no. of ads. & spends)

  • Magazine Advertorial - PAID

  • Magazine Thematic - PAID

  • Newspaper - PAID

  • OOH spends - PAID

  • Digital

    • SEM Clicks - PAID

    • SEM Impressions - PAID

    • Branded Search- PAID

    • Viral Video Clicks - PAID

    • iMedia Impressions - PAID

    • Pre-roll Impressions - PAID

    • Brand Site Traffic - OWNED

    • SNS (Social Networking Site)

      • Postings - OWNED

      • Fans - OWNED

      • Mentions - EARNED

  • PR

    • Online Clippings - EARNED

    • Offline Clippings - EARNED

  In this paper we examine the effects of paid and owned media on earned. Our hypothesis is that earned media activity is related to the level of a client’s paid and owned media, whilst the level of a client’s owned media is also related to paid media in a given period. The marketing indicators are number of new users recruited and increase of purchase amongst existing users. We present the results in form of a cast study:
  Brand – A premium cosmetics brand
  Market –Market Group
  1; Market Group
  2; Market Group 3
  Data Vintage – Jan ’11-Oct.’12
  ‍
  Data Inputs:
  Dependent Variable

• Methodology

  Market Understanding

  • Classify the various media into the three groups – paid, owned and earned

  Analysis through Bayesian Networks and VAR

  Grouping of variables based on media vehicle to identify the impact of,

  • Inter-relationships between media vehicles
  • Media on New Users & Existing Users

  The rationale to understand inter-relationships between media vehicles: Digital media is impacted by other mass media (TV and print) as well as inter-relationships with other media (Digital; Social; PR). Bayesian Networks was used to establish the relationships.

  Model Architecture

  Dependent variables: New Users and Existing Users Independent variables: Are constructed into groups TV, Print, Digital, OOH and Competition

  Results

  Group 1 Markets – Network Diagram

  

  Group 2 Markets – Network Diagram

  

  Group 3 Markets – Network Diagram

  

  Benefits

  A holistic understanding of the impact of media in driving New Users Impact of the lead medium of communication i.e. TV has a declining impact across markets – highest at Group 1 and lowest at Group 3.However the indirect impact of TV in driving New Users through its impact on other elements of POEM also identified establishing its importance across all the markets under study Impact of social media identified – SNS Interactions did not have a direct impact on New Users, however had impact on other elements of POEM impacting New Users