Predictive Modelling of Advertising Awareness - PowerPoint PPT Presentation

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Predictive Modelling of Advertising Awareness

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'Burst and hold' Strategy. ECT higher longer - less variation ... Burst and maintain strategy works best in the markets analysed to date ... – PowerPoint PPT presentation

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Title: Predictive Modelling of Advertising Awareness


1
Predictive Modelling of Advertising Awareness
2
A motivating example
3
Key Questions
  • How do you know you are using your media budget
    to maximum effect
  • Which executions are working best?
  • Are some wearing out?
  • is our sceduling right?
  • What is the best flighting strategy?
  • Does this lead to an increase in market share?

4
How advertisng is modelled
5
How advertisng is modelled...
6
How advertisng is modelled...
New
7
How advertisng is modelled...
8
Adstock Modelling
  • Poor correlation with Ad recall and TARPS
  • Much better correlation with Adstock
  • Adstock gives TARPS memory
  • So Recall and Adstock are comparable
  • Ad recallt Legacy Impact . Adstockt
  • Legacy long term memory
  • Decay rate at which people forget
  • Impact rate of return of recall/100 TARPS

9
How is Adstock modelled
  • . Adstockt dTarpst (1-d) . Adstockt-1
  • where d decay rate usually about 10 or less
  • Initial value taken to be Adstock1 dTarps1
  • Exponentially smoothes Tarps so they become
    continuous
  • Now have a memory component like recall

10
Motivating example revisited.How good is the
model?
400
350
300
250
ECT
200
TARPs
150
100
50
0
9/7/00
6/8/00
3/9/00
28/5/00
11/6/00
25/6/00
23/7/00
20/8/00
17/9/00
1/10/00
15/10/00
29/10/00
12/11/00
26/11/00
date
Modelled NETT ECT
NETT ECT
TARPS
11
Motivating example
Impact Indices
4.5
4.0
Ad A
3.5
Ad B
3.0
Impact
Ad C
2.5
Ad D
2.0
Ad E
1.5
Average
1.0
2/7/00
3/9/00
30/4/00
21/5/00
11/6/00
23/7/00
13/8/00
24/9/00
5/11/00
15/10/00
Ads A E return the best value
12
Future Media Spend - some scenarios
13
Proposed spend until June 2001(1500 TARPS in 10
weeks)
  • 12 low builds slowly to 21 ECT
  • Average ECT 19 after February

14
Alternative Spend Until June(Same Budget)
  • Average ECT 21
  • Burst and hold Strategy
  • ECT higher longer - less variation

15
Whats been happening with this campaign lately?
ECT showing immediate increase following re-start
of campaign
16
Modelled data and prediction
  • Model adjusted to account for actual ECT and
    current spend will see a return to average ECT of
    approximately 20-25

17
Dynamic Adstock Modelling
  • Impact can be evaluated on a weekly basis to see
    if it changes with time. This can indicate when
  • An ad is wearing out
  • Or if some other external factor is influencing
    awareness e.g.
  • Better flight / channelling
  • Increased clutter in the market

18
Ad A - Impact (return/100 TARPs)
Ad wearing out with time.
19
Ad. B - Impact ( return/100 TARPs)
Same spend -different channels.
20
Key Learnings
  • Thresholds of under/overspending exist
  • Avoid 15 second executions
  • Do not run multiple creative executions
  • SOV is critical
  • As executions may appear to be wearing out when
    in fact competition consumers ear has increased
  • Burst and maintain strategy works best in the
    markets analysed to date

21
Advertising modelling can be used to
  • Diagnose the effectiveness and current health of
    each execution
  • Predict potential future scenarios
  • find the optimal media expenditure strategy

22
The Relationship to Market Share
  • Getting awareness up is first base
  • it doesnt necessarily result in increased share
  • however, chances are that the client will notice
    the effects when the ad is not on
  • In other words, it is a composite of optimal
    spending on advertising and what is happening in
    terms of distribution/sales and service.
  • Or -its a bloody hard problem!!!

23
51 of Brand share explained by what we measure
Model Fit
33 of model fit due to adstock alone
10
9
Brand Share
8
7
Execution A
Execution B
0
20
40
60
80
100
Date
24
A Market Share Model
  • BRANDSHARE
  • 5.830053 initial
  • -2.16682WINTER Opposition dumps!
  • 0.547SOVLOTS SOV gt40
  • 0.031Adstock
  • 0.052AdsExA Execution A lifts Share
  • -0.0006AdsExA2 Overspend on Ex A
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