The Early Bird (Who is
Your Friend) Gets the Worm
It’s not too radical to claim that people are more like their
friends than they are like other people that fit their demographic or
psychographic makeup. Social psychology
has shown that people tend to develop relationships with those that have
similar interests to them, transcending demographics and psychographics. And those that have a strong relationship
with each other have the capacity to influence each others’ behavior.
Marketers traditionally have put consumers into various
buckets in order to compartmentalize and therefore easily learn and make
assumptions about them. These marketers
lack the Holy Grail social-graphic information: friend connections and
relationship information amongst their consumers.
Past – Demographic Targeting
Looking at John S., for example, he fits in the 25-34 year old, white male from San Francisco, CA bucket; now, marketers will assume that John is likely to respond to offers other people from his bucket generally respond to. In the absence of any other information about John, this demographic convention is the best they can do, with additional information obviously being more useful.
Present – Psychographic Targeting
When it comes to targeting people based on their
psychographics and interests, politicians, especially, have been highly successful. If John S. subscribes to Guns & Ammo magazine, he might be very open to a message from a
pro-gun candidate despite living in an area where the vast majority of
inhabitants strongly support a ban on guns.
This type of psychographic targeting is more successful than targeting
purely on demographics — psychographic targeting is not as broad and can be more
descriptive. Thus, John’s interests in
one area is a good predictor of what he might buy in another area, independent
of the behavior of those within his demographic bucket
Future – Social-graphic Targeting
A more powerful predictor of John’s purchasing behavior is
what his friends are doing and buying. For
instance, people interested in wine tend to hang out with people that also are interested
in wine. And if a company is pitching a
product, its best prospects are the friends of its current consumers: a golden
leads list.
A study by Shawndra
Hill, now Assistant Professor of
Operations and Information Management at the University of Pennsylvania, shows a very strong correlation among friends purchasing the same items. This intuitively makes sense: one cannot pick his demographic makeup, but can and does pick his own friends, often based on similarity in attitudes, values, interests, and personality. This similarity leads to similar behavior and buying patterns amongst those friends.
Implications of Social-graphic Targeting
The problem for marketers and companies is knowing who
someone is friends with since few companies have access to the social graph of
their consumers. But companies with access
can leverage that information for better targeting. By better targeting consumers, companies can
cut down on advertisements, spam, and harassment to consumers and create a
world with more relevance, consumer happiness, and better use of everyone's time.
Companies with this information include telecom providers,
social networks, webmail and IM clients, and search aggregators. As one’s social graph becomes a commoditized way
to do better targeting, these companies (and others) will become increasingly
valuable.
Telecom providers have great social graph data. They know who often calls each other – an
accurate representation of one’s social graph.
These companies can do analysis on this data and even determine type of
relationships based on the frequency, duration, and timing of calls (e.g. most
people tend to call their mom on Mother’s Day).
Similarly, free webmail clients (Gmail, Hotmail) and IM chat
clients (AIM, Yahoo) have a gigantic social graph of everyone that communicates
with each other. In the future, this
social graph data can be used to change the way these webmail and IM clients
display ads based on the behavior and activity of one’s social graph.
Online social networks have a good idea of who people know
and the extent of their relationships.
They could partner with retailers to better pitch products based on what
peoples’ friends are doing. Facebook
already does this with Social Ads (and is what they attempted to do with
Beacon).
Search aggregators, such as Google and Rapleaf [disclosure:
I am an employee of Rapleaf], aggregate public connections data from thousands
of blogs, forums, social networks, discussion boards, and more. These aggregators can enable marketers to
better understand their consumers and provide a more customized experience and
product recommendations based on the consumers’ friends’ interests and buying
behavior. Companies that really want to
better serve their consumers with a more customized experience, can leverage
these friend maps effectively.
It turns out that the obvious is true: birds of a feather
really do shop together.
Auren, very thought-provoking post! Could have implications for the companies such as Lookery (disclosure: I am an investor) that are using anonymized social networking profile information (along with other data) to enable targeted advertising. Though Lookery is starting with the basics (age, gender, location), eventually it could also mine the social graph (again in a non personally identifiable manner).
Great post. The key for marketers and advertisers is figuring out the location of the third rail – that line between pleasantly relevant and creepily invasive. Beacon, at its unveiling, was on the latter side, but with better default settings, it could have been great. Recent Facebook ads have been much more relevant, but appear to be targeted using my profile information, for the most part, which is easy relative to psychographic targeting that uses attention data as the main input.
Context in Social Shopping
My friend Auren periodically pens insightful posts about topics on his mind. He recently shared his thoughts on social shopping. To summarize:Social psychology has shown that people tend to develop relationships with those that have similar interests t…
Great post, Auren. It certainly makes sense and I’m guessing you have the data to back it up. A white paper with some data would certainly be interesting.
Do the same patterns exist w/ B2B purchases? All of your examples are B2C products.
The social networking sites might get thrown off by a recent trend: I’ve reconnected with a lot of people from my past. Just because we share a history does not mean that we have anything else in common. Is there really any relevance to the fact that on Facebook I have links to my friends from West Point that are hunters, republicans, Army officers, and use tobacco? Still, a thought provoking idea, if not entirely new.
@Auren
About three months ago we’ve launched ikki.com, a social networking site where members can manage their business portfolio, create a psychographic profile and network with other members. We use intelligent matching software to match members against each other based on a combination of variables including education, working experience, but also on the pyschographic profile and social network. Companies can use our site for recruitment purposes and can target members based on psychographic and socio-graphic targeting.
So.. have a look and tell me what you think. We’ve launched in the Netherlands, so the content is mostly in dutch.
If you drop me an email (marco@ikki.nl) i’ll create a targeting account for you to test.
Great article, par for Auren. Another implication of more precisely targeted information and advertising that, as a population, we continue to become more stovepiped and less aware of alternative viewpoints, frames of reference, challenges, and pleasures. From a marketing perspective, there’s a strong need for precise market-targeting, but from a social perspective we need networks and information-flows that cross the stovepipes.
This makes complete sense, and I would like to add something for the marketer who is considering using friend data to make a pitch. It’s my experience in direct marketing that context matters a lot and by bringing context into the offer decision matrix the marketer will improve performance.
Consumers tend to have different buying behaviors depending on their state of mind at the moment they hear your pitch. The social graph data should give insight into how the consumer might behave differently in different situations. For example, profile difference for same person between LinkedIn, Facebook and Amazon could reveal professional, social and personal context. If this can be proven, the answer could give the marketer significant predictive power.
As a marketer many times you know the context facing your consumer before you make an offer. I suggest that including this context into the offer decision leveraging social graph and other self reported data will deliver positive results.