Have you no*ced this ad for …
…or did you arrive at this search-‐page without having ever seen the ad?
A few clicks later you have arrived here to choose what to buy, where and at what price.
But the day a@er you are surprised by a similar newspaper-‐ad of another brand.
How confusing.
But confused consumers … compare. (Aren’t we all confused consumers?)
Brands themselves confuse consumers. Deliberately.
http://bit.ly/ZBFHFK
That’s how they do it.
Eventually you ask some car lover-‐friends which used car you should buy. Aston Mar*n or BMW.
That’s the social consumer: he/she buys a lot -‐ not only cars -‐ based on recommenda*ons.
What’s the problem with adver*sing?
“Why now? You interrupt my ac4vi4es”
“Not for me. I just bought my stuff”
“Too many ads. I avoid them”
“So stupid”.
“Nice ad, but so what? Not relevant for me.”
“Haven’t even seen it.”
“I don’t care. Will search when I need something.”
“Don’t trust it. Nothing but lies. I’ll ask my friends or colleagues”
you
you you
Ad agency
Brand
Ads
Media
Your data
“We are not the customers of Facebook, we are the product. Facebook is selling us to adver*sers.”
Douglas Rushkoff
Reviews do the job!
Yelp (2008-‐2012) s*ll loses money.
About 70% of Yelp’s revenue is from ads (!!!) by local businesses listed on its site.
1980-‐1990:Adver,sing +10% = +2.2% marketshare 2008:Adver,sing +20% = +2.2% marketshare
“ …. the authors conduct a meta-‐analysis of 751 short-‐term and 402 long-‐term direct-‐to-‐consumer brand adver4sing elas4ci4es es4mated in 56 studies published between 1960 and 2008. the study finds several new empirical generaliza4ons about adver4sing elas4city. the most important are as follows: the average short-‐term adver4sing elas4city is .12, which is substan4ally lower than the prior meta-‐analy4c mean of .22; there has been a decline in the adver4sing elas4city over 4me.”
Gerard Tellis, PhD Michigan, is Professor of Marke,ng, Management, and Organiza,on, Neely Chair of American Enterprise, and Director of the Center for Global Innova,on, at the USC Marshall School of Business. He is Dis,nguished Visitor of Marke,ng Research, Erasmus University, RoUerdam and has been Visi,ng Chair of Marke,ng, Strategy, and Innova,on at the Judge Business School, Cambridge University, UK. Tellis specializes in the areas of innova,on, adver,sing, global strategy, market entry, new product growth, promo,on, and pricing.
Prof. Dr. Gerard Tellis
One of many brands’ issues: “Adver*sing is too expensive. Grows faster than the economy!”
+7% +3,8% +3,8% +4,6% +5,2% YOY-growth
Recommenders directly influence 20-‐50% of all purchase decisions.
Offline! Thé method of recommenda*on.
The mo*ves of recommenders?
Why do you recommend? And why not?
The difference between a “recommended” beer and a marke*ng beer.
http://www.ratebeer.com/
The difference in family fortune between a “recommended” beer and a marke*ng beer.
€ 270 million
$11 billion
“Friends & family” -‐ recommenda*ons lead.
“Friends & family” are the trusted source. Adver*sing …?
Some buy a lot online and tell it to a lot of people online too.
“… while consumer electronics buyers pay more aZen4on to other consumers’ reviews than to editorial reviews – by a margin of more than three to one (77 percent vs. 23 percent) – a majority are concerned about the authen4city of consumer reviews (80 percent), leading them to conduct considerable analysis before making their decision.”
Who’s influencing? Is all that buzzing trustworthy?
POE: Paid. Owned. Earned.
Recommenda*on measurement started with Reichheld in 2003
88
8
NPS
Not only we ask clients whether they will/will not recommend a brand…
NPS
NPS
We ask non-‐clients too. They too judge, talk and influence. That’s why we ask them.
The actual Holaba B2B-‐dashboard in China
Net Promoter Score= % promoters (9-10) minus % detractors (0-6)among clients.
Holaba Score = % promoters (9-10) minus % detractors (0-6) among recommenders
Recency, frequency, monetary value (RFM) of clients are decisive for investment in marke,ng communica,on. Therefore lots of money spent (wasted) in this group of heavy and recent buyers
RFM -‐ axis
Light and non frequent buyers are o_en “neglected”
From RFM to RRFM to decide about what to invest where.
Recommenda7on axis
+RFM & -‐ REC
-‐ RFM & -‐ REC
+RFM & + REC
-‐ RFM & + REC
RFM -‐ axis
The recommenda*on power of clients becomes the decisive tool to decide on marcom-‐investments
Does not mean they all give posi4ve recommenda4ons
Frequency and intensity of recommenda*on.
To influence these influencers, iden*fy them. Con*nuously. Everywhere.
Jan Van den Bergh 杨⽂文博
[email protected] hFps://www.facebook.com/jevedebe hFps://www.facebook.com/holaba TwiFer:@holaba Skype:jevedebechina
+86 136 2179 9450 (CH) +32 475 427 882 (BEL) A : 上海市新闸路831号丽都新贵13层F室, 200041 13-F, No 831 Xin Zha Road, Shanghai, 200041