AMEC Awards 2015
Category: Innovation Award
Client/Entering Company: PR News
Campaign title: Reputation Rating Factor 2013
Company Name: PR News

Objective/Brief

PR News in 2013 launched the Reputation Rating Factor Study to meet the market demand and client requests to outline key performance indicators (KPIs) that best satisfy the goals of media performance evaluation.

The study was designed to identify 2-3 key trends in the media coverage of top companies which are specific to their industries and have the most effect on their reputation:

The study pursued the following goals:
1) Pick a sample of articles published in the first half of 2013 in Russia about 59 companies engaged in a variety of industries;
2) Develop a method to interpret the collected data;
3) Select statistical methods to process and analyze the collected data which will be relevant to the objective of the study.

STRATEGY:

We used a method based on the general concept of benchmarking – that is of identifying statistically significant differences in coverage of market leaders and outsiders. Market leaders were identified based on industry rankings and media activity.

The coverage sample numbered 48,276 articles published in the first half of 2013 in Russia. They covered five industries: home appliances, IT, cosmetics, automobiles, and finance and investment.

The following characteristics were analyzed:
– Number of articles/mentions;
– Media type/specialty;
– Tone;
– Role of the subject of analysis in an article (lead/secondary/brief);
– Number of company officer quotes;
– Number of headlines containing names of a company and/or its executives;
– Coverage by reach (А – less than 10,000 contacts, В – 10,00-100,000 contacts, С – 100,000-500,000 contacts, D – over 500,000 contacts);
– Topic (new launches/products already on the market/brand stories, etc.);
– Control over media coverage based on the amount of press in a given period of time (monthly in this case), compared with the average monthly amount, and calculated for each company as coefficient of variation.

We hypothesized that media KPIs determining the divide between leaders and outsiders were identical for all industries. And having the most impact on the reputation, they can be extrapolated to other segments of the market.
The novelty of this approach is that the data was statistically processed on several levels to prove the hypothesis (we used the software STATISTICA 10). As the primary statistical method, we used factor analysis (rotation – varimax normalized) which allows to limit the number of variables to look for joint variations. This method was the closest to meeting the study’s goals. At the first stage, we used factor analysis to limit variables to 45 and select the most relevant ones. Then we used regression analysis to identify 3-5 key factors impacting how leaders were covered.

EXECUTION/IMPLEMENTATION:

Stage 1: The statistical analysis of a data array comprising 59 objects x 45 variables using factor analysis failed to prove the hypothesis. There were no significant correlation between the leader and outsider coverage. There were 12 insignificant factors extracted and total variance was under 7%, showing no consistent patterns.


This proved that media KPIs are not identical for all industries.

Stage 2: We hypothesized that media KPIs were specific to each separate industry and its leaders and outsiders.

Separate analyses of the coverage in each of the five industries revealed statistically significant factors with a total variance over 20%, thus proving the new hypothesis.

Below are examples of factors specific to the automotive and home appliance industries.

Automobiles:

We found the following two key criteria specific to car brands:
1) a large share of brief mentions correlating with the topic “partnership/sponsorship” and a reach of 10,000-100,000 contacts;
2) a large share of articles based on press releases, company officer interviews, advertorials, etc. correlating with the name of the company being put in the headline.


Table 1 – Factor Analysis Results – Automobile brands

Factor Analysis Results – Automobile brands

Figure 1 – Factor Analysis Results – Automobile brands – Significant reputational factors

Figure Factor Analysis Results – Automobile brands

Home appliances

Table 2 – Factor Analysis Results – Home appliances

Factor Analysis Results – Home appliances

Figure 2 – Factor Analysis Results – Home appliances – Significant reputational factors

Figure 2 - Factor Analysis Results – Home appliances – Significant reputational factors

The industry’s leaders enjoyed a larger share of articles focused on them and their brands, while the number of brief mentions was small. And both leaders and outsiders received more attention from print publications, as opposed to online media outlets.

CONCLUSION:

The novelty of the approach we used lies in the use of factor analysis with reliance on the ideas behind benchmarking to identify key factors in media performance. The study showed that conducting a successful media audit of an industry calls for a list of factors specific to the success/failure of media policies pursued by companies in such industry to be identified empirically.

A later study for a client proved that the differentiated approach of the method we developed made it representative and valid and would be beneficial for both the outsiders as guidance and the leaders to minimize media risks.

The study’s findings were presented at the 7th PR Russia Forum and attracted interest from PR professionals and companies in the industries which the study analyzed. As a result of the presentation, we signed new clients looking to develop the optimal KPI model and wrote an article on media KPIs for finance and investment companies for the magazine PR in Russia.

Name of contact: Lilia Glazova
Email: lglazova@prnews.ru
Telephone: +7 (495) 789-4259