IPA Effeectiveness Analysis
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Transcript of IPA Effeectiveness Analysis
Advertising Success:Lessons from the IPA Awards
Les Binet
European Director
DDB Matrix
“Marketing in the era of accountability”by Les Binet and Peter Field
• Which strategies work best in hard business terms? Which metrics best predict success?
• Research based on analysis of the IPA dataBANK. Largest ever meta-analysis (880 case studies).
• Effectiveness measured in terms of business results, not prizes.
• Key metric: Effectiveness Success Rate. % cases showing very large effects on a range of business metrics, from sales to profit.
• Conclusions: Some strategies work better than others. Much common wisdom is wrong. Much common practise is inefficient.
Campaign objectives
Objectives: Hard vs Soft
• Successful campaigns set both kinds of objectives, and
prioritise them.
• Hard objectives come first. Campaigns that set these are
over 4 x more effective than those that don’t.
• Soft objectives come second. Campaigns that just focus
on these under-perform.
• The most popular objectives are not in fact the ones that
lead to business success…
Business objectives
• Marketers tend to focus on the wrong business objectives.
• Most campaigns aim to increase sales. • But sales targets are a poor way to assess marketing
performance, since they are too heavily influenced by market conditions.
• Market share targets impose tighter discipline. Campaigns that set share targets tend to perform better.
• But the most effective campaigns of all are those that focus on price, not volume…
Price is the key to profit
20%21%
26%
37%
0%
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10%
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25%
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35%
40%
Price sensitivity Share growth Share defence Sales growth
Campaign objective
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% r
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Percentage of campaigns targeting price sensitivity: 4%
Shifting the demand curve
• Supporting firmer pricing is far more profitable than just generating volume, because all the benefit falls straight to the bottom line.
• Arguably price sensitivity is a better measure of attachment to a brand than standard “loyalty” measures.
• The dataBANK suggests that two communications strategies are particularly good at getting consumers to pay higher prices:– Emotional engagement– Fame
Behavioural objectives
Common practice...
5%
12%
22%
0%
5%
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15%
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25%
Increaseloyalty
Increasepenetration
Increase both
Campaign objective
Inci
den
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...is not best practice
24%
73% 88%
0%10%20%
30%40%50%60%
70%80%90%
Increaseloyalty
Increasepenetration
Increase both
Campaign objective
Eff
ecti
ven
ess
succ
ess
rate
Loyalty is hard to change
6%
82%
2%0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Loyalty only Penetration only Both
Which measures increased?
Inci
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ce (
% o
f ca
ses)
The loyalty myth
• Talking to existing customers is less rewarding because:– There are usually fewer of them than non-customers– They are more influenced by product experience than by
communications
• As a result, loyalty campaigns tend to be less effective than penetration campaigns.
• This seems to be true for all sectors – even subscription services.
• Decades of research by Ehrenberg et al on a wide variety of markets yielded exactly the same findings.
• Increasing loyalty is like turning lead into gold.
Intermediate objective
% campaigns
Awareness 61%
Image 55%
Direct 46%
Differentiation 43%
Fame 33%
Quality 33%
Commitment 31%
Trust 22%
The most common intermediate objectives are to build brand awareness,to improve brand image, and to generate some kind of direct response.
Intermediate objective
% campaigns Success rate versus
objective
Awareness 61% 45%
Image 55% 27%
Direct 46% 46%
Differentiation 43% 35%
Fame 33% 37%
Quality 33% 28%
Commitment 31% 26%
Trust 22% 12%
Statistically significant difference(95% confidence)
However, brand image rarely changes.
[Note that commitment rarely changes either – like loyalty.]
Intermediate objective
% campaigns Success rate versus
objective
Awareness 61% 45%
Image 55% 27%
Direct 46% 46%
Differentiation 43% 35%
Fame 33% 37%
Quality 33% 28%
Commitment 31% 26%
Trust 22% 12%
Campaigns that aim for awareness or direct response fare better. The target metric is easier to shift, which makes them seem accountable.
Statistically significant difference(95% confidence)
Intermediate objective
% campaigns Success rate versus
objective
Effectiveness in business
terms
Awareness 61% 45% 67%
Image 55% 27% 68%
Direct 46% 46% 67%
Differentiation 43% 35% 70%
Fame 33% 37% 78%
Quality 33% 28% 73%
Commitment 31% 26% 70%
Trust 22% 12% 72%
But sales data shows that this success is illusory. The three most populartypes of campaign are in fact the least effective.
The most effective campaigns are those that aim to make the brand famous, rather than merely increase awareness.
Campaign strategy
Types of campaign strategy
• Campaigns that work by reinforcing existing consumer behaviour (including many loyalty campaigns) are much the least effective.
• Effective campaigns aim to change behaviour. Some try to do this in a primarily rational way, some use emotions, and some use both.
• Rational campaigns are the most common, but…
Emotional strategies are more profitable
16%
26%
31%
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15%
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25%
30%
35%
Emotional Combined Rational
Campaign strategy
V l
arg
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ain
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% r
ep
ort
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)
Emotional campaigns outperform on almost every metric
Emotional campaigns work best even in ‘rational’ categories
75%78%
67%
55%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Emotional category Rational category
Predominant nature of decision making in category
Eff
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Emotionalcampaigns
Rationalcampaigns
The power of emotion
• Emotional campaigns work particularly well for premium brands, where the purchase decision tends to be more emotional.
• In fact, emotional campaigns are twice as good at reducing price sensitivity as rational ones. This may be one reason why they are so profitable.
• Emotional campaigns are also particularly effective:– for smaller brands (less likely to have product/price advantages)– in more mature markets (fewer functional differences)– when market conditions are buoyant (price is less of an issue)
• In fact, there is only when area where rational approaches work better…
Rational strategies yield bigger direct responses
35%
31%28%
0%
5%
10%
15%
20%
25%
30%
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40%
Emotional Combined Rational
Campaign strategy
V l
arg
e d
ire
ct
eff
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ts (
% r
ep
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ing
)
The most powerful strategy?
72%68% 68%
59%
0%
10%
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30%
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50%
60%
70%
80%
Fame Emotionalinvolvement
Combined emotional& rational
Any rational
Communications strategy
Eff
ec
tiv
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s s
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ss
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te
The power of Fame
Fame campaigns achieve broader business success
39%
58%
8%11%
33%
22%
4%8%
27%
48%
0%
10%
20%
30%
40%
50%
60%
Profit Price sensitivity Sales Loyalty Penetration
Business metric
% a
ch
iev
ing
ve
ry l
arg
e e
ffe
ct
Famecampaigns
Othercampaigns
Fame campaigns
• The most effective of all are those that work by getting the brand talked about and making it famous.
• Such campaigns outperform others on almost every metric:– especially price sensitivity and profit.
• This finding supports the idea that “word of mouth” or “buzz” metrics might be good predictors of effectiveness– A more proactive version of the Net Promoter Score– DDB research suggests that factoring in measures of “influence”
may make such metrics even more useful.
Media
Key findings
• ATL and BTL do seem to enhance one another. Campaigns with both seem to be more effective and more efficient than those with just one or the other.
• TV ads seems to be more effective and efficient than print ads.
• Yet other research suggests print gets more rational attention than TV.
• Further support for the importance of emotional engagement rather than rational attention?
• Contrary to current wisdom, data suggests that TV is becoming more effective, not less.
Evaluation
The balanced scorecard
• The most commonly used leading indicators are brand awareness, brand image and direct responses.
• Yet none is sufficient or necessary for effectiveness.
• Brand consideration does seem to be a better predictor.
• Better still, use a wide range of metrics, rather than any single measure – the “balanced scorecard” approach.
• If you need a single performance measure, make it a ‘metric of metrics’
The more metrics that move, the more effective the campaign
88%
75%68%
46%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 1 2 3+
Number of very large leading indicators
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The number of metrics that move is a better predictor than any single metric.
Measuring advertising impact
• The data shows that “liking” of an ad is a significantly better predictor of business effects than either “communication” or “persuasion” measures.
• This is consistent with the superior effectiveness of emotional communications over rational ones.
• “Standout” measures such as ad awareness turn out to be the worst predictors of all.
• This raises questions about pre-testing methods that work by trying to predict standout…
Does pre-testing (for standout) reduce effectiveness?
71%
44%
0%
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20%
30%
40%
50%
60%
70%
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Quantitatively pre-tested Not quantitatively pre-tested
Research measures in use
Eff
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Effectiveness vs Accountability
• Campaigns with broad effects are more effective.• But those with narrow effects often seem more accountable - the
effect is easier to measure and easier to relate to the campaign.• Thus there is often a tension between accountability and
effectiveness:– Campaigns that aim for brand awareness or direct responses tend to
shift the target measure but little else – accountable, but ineffective.
– Campaigns that aim for brand fame have broader effects, and better business results.
– Rational campaigns have narrow effects and are easier to track – e.g. through communication and persuasion scores.
– Emotional campaigns have broader effects, making them harder to track, but more effective.
Summary
Common practice
• Focus on single objectives
• Generate volume
• Focus on existing customers
• Increase brand awareness
• Rational communication
• Shift to direct response
• Evaluate against single KPIs
• Accountability
Best practice
• Aim for broad, multiple effects
• Shift the demand curve
• Talk to whole market
• Generate brand fame
• Emotional communication
• Emotionally rich media lead
• Use a balanced scorecard
• Effectiveness
Full data available via warc.com
Thank you
Les Binet European Director DDB MATRIX Having read Physics at Oxford, Les took an M. Phil. in Artificial Intelligence at Edinburgh University. His research there focussed on the use of computer models to study the way human beings process language. In 1987, he joined the Account Planning department at BMP (now DDB London), where he turned his modelling skills to the problem of measuring the effects of advertising. He currently heads DDB Matrix, DDB’s in-house econometrics consultancy. Over the years, Les has worked for a wide range of clients, including Unilever, Heinz, Nestlé, Volkswagen, J ohnson & J ohnson, Kraft, Sony, AXA, and Anheuser Busch. He has also played an important part in establishing DDB’s reputation for effectiveness, having won more IPA Advertising Effectiveness Awards than anyone else in the history of the competition. Since 2001, he has served on the IPA’s Value of Advertising Committee, helping to promote effectiveness and evaluation in the wider marketing community. In 2004 he was elected an Honoary Fellow of the IPA, in recognition of his services to the advertising industry, and in 2005 he was Convenor of J udges for the IPA Awards. In 2007, Les Binet and Peter Field published “Marketing in the era of accountability”, a major study of the factors that influence marketing effectiveness. This research is based on the IPA dataBANK, a database of effectiveness case histories, which Les and Peter helped to design and build for the IPA.