CASE STUDY: CrossMedia Research

Haircare category in Malaysia

Research Objectives

To understand the impact of individual media on brand perceptions of

HAIRCARE BRAND.

In doing so ascertain :

the medium to long term impact of advertising

the effectiveness and efficiency of online media vis a vis other media

if online media works in synergy with other media

if there are diminishing returns sets in by media and therefore how

best to re-allocate media spends

Research Specifics

• CAWI Methodology • Pre-wave

Sample: 400 interviews (200 online, 200 offline)

Malaysia – Johor Bahru, Kuala Lumpur, Penang

Females Age 15+ Users and choosers of

Shampoo Age and race quotas set

based on city-wise distributions

Pre-wave Post-wave

• CAWI Methodology • Post-wave

Sample: 1000 interviews (500 online, 500 offline)

Malaysia – Johor Bahru, Kuala Lumpur, Penang

Females Age 15+ Users and choosers of

Shampoo Age and race quotas set

based on city-wise distributions

Pre-campaign control allows us to determine how people felt about the brand without effects of media

Contributions to Brand Metric Score

Pre (control) & Post (exposed) analysis of media campaigns allows us to account for

pre-disposition towards the brand

Pre Post

Brand Measure

We can then determine the impact of exposure to the different media channels on uplifts in brand metrics.

We use calculations of each respondent’s probability of exposure to all the different elements of the media campaign (based on detailed media consumption questions). If we are measuring digital media, we would use cookies to capture actual exposure data. We then analyse variations in brand metric scores against media exposure levels for each respondent.

Using this information, we are able to determine which media had the most influence on any observed uplifts and quantify the return for money spent.

Estimate respondents’ exposure to campaign media

Saw ads In NO media

Saw ads in all digital, press

And TV

Saw ads in press and TV

Calculate shift in metric due to media exposure

Uplift in

Consideration

8.0

4.3

0.8

Print

TV

Digital

For illustration only

How we estimate contributions:

The contributions that different factors make to the end of campaign position are derived using a statistically valid modeling technique called multivariate regression.

We build a model based on the respondent level data from the whole survey period to estimate how much each factor contributes to respondents’ brand metric scores

From the model we can then estimate the “end of campaign” contribution from each factor

Campaign

Explaining CrossMedia Research results Core results represent the “End of Campaign Position”

Week: 1 2 4 3 6 5 7 8 9 10 11

Brand Metric Score

Metric building over campaign

period

CrossMedia Contributions

12 13 Consideration

(Top 2 boxes)

1.2%

56.0%

3.4%

The campaign includes 3 media channels – TV, online and print

TV

Print Online

March April May June July August Sept

FTA

Astro

Magazine

Digital

Variant TVC (30s)

Local TVC (30s)

Facebook

Detailed media plan

Display

Pre-wave In-campaign-wave

The overall media campaign reached 89% of the target audience.

Online Only

3.1%

TV + Online

14.3%

Magazine TV Online

Coverage of sample by overall media channel and by combination

TV only

54.6%

Magazine Only

1.2%

TV + Online + Magazine

6.6% Online + Magazine

0.6%

TV + Magazine

7.9% Unexposed

11%

TV reach 83.2%

Online reach 24.5%

Magazine reach 16.2%

Key

Metric

Purchase Consideration

Purchase Consideration

60.6%

Underlying Involvement

Interest

Attitudes

Demand

Involvement

Purchasing

Purchase Consideration

56.0%

Ongoing Influences

Word of Mouth

Previous Campaigns

PR 1.2%

Purchase Consideration

56.0%

Campaign Input

Online

Purchase Consideration

TV

1.2%

3.4%

56.0%

Magazine

Campaign Contribution

Baseline

Ongoing Influence

1 2 3 4

51.0% 56.0% 51.8%

57.3%

4.5% 1.2% 3.0%

3.3% 4.6% 3.4% 2.7%

4.2%

Presence (Av. of 3 metrics)

Functional Image

(Av. of 5 metrics)

Campaign Performance Overview

Purchase Consideration (Av. of 3 metrics)

60.1% 64.8% End of campaign value: 57.6% 60.6%

Emotive Image (Av. of 4 metrics)

Channel Contributions to campaign performance

2.1%

0.9% 1.8%

3.4%

0.6%

0.1%

0.0%

0.5% 1.3%

2.0% 0.3%

0.0%

0.6%

0.3%

0.6%

0.3%

Online

TV

Magazines

TV + Online synergy

Presence (Av. of 3 metrics)

Functional Image

(Av. of 5 metrics)

Purchase Consideration (Av. of 3 metrics)

Emotive Image

(Av. of 4 metrics)

+4.6% +4.2% Total Campaign Impact +2.7% +3.4%

Each channel was able to drive uplifts in a different array of brand measures. Strength of uplifts by channel

Strongest

Measure

Weakest

Measure

Online was the most effective at generating presence and purchase intent!

Online

Online was the most effective at generating presence and purchase intent!

TV Magazine Display Facebook TV &

Online

Online

& Mag

2.1 0.6 1.0 0.3 0.6 0.0

0.9 0.1 1.3 0.7 0.3 0.0

1.8 0.0 0.0 0.3 0.6 0.0

Presence (Average of 3 metrics)

Consideration (Average of 3 metrics)

Functional imagery

3.4 0.5 0.0 0.0 0.3 0.0 Expertise imagery

Media efficiencies

Bulk of the media investments were for TV, and an equal portion for magazine and online.

78%

11% 11%

Proportion of overall campaign spend by channel...

Relative cost efficiency - % increase in brand metrics per $1 spent

3.1%

1.4%

2.7%

4.5%

15.0%

19.8%

5.5%

1.3%

5.0%

1.2%

0.0%

5.0%

Online TV Magazines

Presence (Av. of 3 metrics)

Functional Image

(Av. of 5 metrics)

Consideration (Av. of 3 metrics)

Emotive Image

(Av. of 4 metrics)

Optimising Media spends to

maximise Brand metrics

Estimate effective frequency ceiling for each media/metric

Identify proportion of each media’s GRP’s that are unproductive

Calculate a weekly relative cost for productive GRP’s by week

Step 1

Step 2

Step 3

Step 1: estimating effective frequency ceiling level

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70

TV

Online

Magazines

4-5

% o

f M

ax I

mpact

deliv

ere

d

49-51

Frequency of active exposure

Avg. Freq (as per sample)

TV – 82.2 Online - 2.0 Magazines - 2.0

Effective frequency ceiling for impact on “Functional Imagery”

Step 2: Proportion of weekly TV GRP’s that are un-productive in driving “Functional Imagery”

0%

10%

20%

30%

40%

50%

60%

70%

80%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

% audience over frequency ceiling

% GRPs non productive

Weeks

To drive Functional Imagery 63% of the GRPs would have been sufficient

From week 13 on, over 50% of TV GRP’s are unproductive

Step 3: relative cost index of productive GRP’s by week

0

50

100

150

200

250

300

350

400

450

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

TV - Relative Cost Index for productive GRP's

Weeks

As one would expect, as diminishing returns starts to set in the GRPs get

lesser and lesser productive

Four silver bullets: Recommendations for future campaigns

1. Online was the most cost efficient media, and could sustain

significantly more weight:

Increase investment in online in future campaigns

2. TV & Online synergy was important, but online was only active for last 3rd of campaign

In future try and phase TV & Online together for more of campaign period to maximise synergy bonus

3. TV over delivered in 2nd half of campaign

Down weight GRP weights later in campaign periods to improve cost efficiencies

4. Magazines was cost efficient, but the reach was low

Look to extend reach via additional titles in future