Back to the roots — Have product recommendations really been reinvented?
Some days ago I came across an interesting article in a german online journal which reported about a „new feature in online marketing“ — product recommendations. The protagonists: two of the world’s largest companies in online business — Amazon and Facebook.
The fact that Facebook recently changed their terms and conditions captured my interest, especially as this forces the majority of Facebook users (including me) to rise the curtain covering their personal data once more.
As our business primarily focuses on personally driven recommendations, the following quotation let me sit up:
„It is noteworthy, that Amazon itself is considered as the inventor of recommendations. “
Really? Amazon invented personal recommendations? In fact, this is a daring statement which directly leads to the commonly known question: What came first — the chicken or the egg? The personal recommendation or Amazon’s product recommendation?
Johann Wolfgang von Goethe, the famous german poet, used to make a statement about the value of personal recommendations, especially from friends nearly 300 years ago:
„As much as a man (re)commends himself, so much does the recommendation of a friend favor the first moments of acquaintance.“
So is Goethe considered as the inventor of personal recommendations? Certainly not. De facto we all recommend things we are positive about to our family and friends all day long — mostly without even recognizing it.
Additionally, recommendations computed from a user’s individual searching and buying behavior are a feature nearly all larger online stores are currently using. It’s hard to say if Amazon really was the first company who implemented this. And — no less important — do these recommendations really fulfill the requirements to call them „personal“ (as they are created by an algorithm instead of a person knowing the recipient)?
Anyway, in this case, the article covered Amazon’s product recommendations and informed us about a fact that could definitely be described as „the next step to a completely transparent customer“:
„On Amazon’s new Facebook page, users who are logged into both platforms and approved access to their Facebook data will receive notably more personalized advertisements. This does not only include product recommendations related to this user, but also proposals for his Facebook friends – for example if their birthday is coming up soon. “
To be more precise, this literally means that not only the user’s searching and browsing will be factored into product recommendations, from now on his friends’ behavior will also become a source of data (without knowing about this at all)! And the behavior of the friends of his friends. Maybe also of the friends of his friends’ friends. At least in theory — regarding the commonly known „Small World Theorem“ — we could state that also Mr. Gates‘, Mr. Zuckerberg’s or Mr. Obama’s buying behavior would be relevant for product recommendations presented to myself. Weird, uh?
But back to the gravity of the situation. There are some interesting questions arising from these exciting, partially alarming facts:
Who really knows best about my wishes and interests?
In times where a vast number of consumer-related information is traded online, we should ask ourselves who really knows us best:
The personalized advertisement calculated by complex algorithms based on our consumer behavior — or maybe our closely related people who enjoy the smile on our face if the birthday present hit the mark?
We are profoundly convinced that our friends will win the race. If we look on the following example, it seems quite logical why:
Let’s imagine our fridge is busted and we urgently need a new one. First initiative: Google! Checking prices, features and some further facts as for example energy efficiency, we quickly choose our favorite product. As we are short in time, we’re borrowing our best friends‘ Pick-Up truck to buy the new fridge conveniently at the next local electronics store. So far, so good. But what happens in the internet? Advertisement „recommends“ the hottest and newest fridges for weeks. Every different price level, every different producer. Though the new fridge already resides in our kitchen.
By the way: my friend (the guy with the Pick-Up truck) has a much more useful recommendation — a six banger of beer to be cooled in the new fridge.
Are 5-star-based customer reviews really as helpful as we think they are?
The customer reviews — we all know them and we (mostly) read them. But can they be adapted for product recommendations? I will anticipate the answer: We don’t think so!
Basically it’s a good approach allowing everyone to evaluate products and services in a range from very good to really bad so we can get an idea about the quality of the long-desired product. Nevertheless, we shouldn’t ignore some facts in this scenario:
- Do many bad reviews say something about the product’s quality? Or may they not also be written by dubious agencies on behalf of competitive brands?
- Are many good reviews better than a few good reviews? Especially if one product is available from time immemorial and the other one is newly released?
- Do we interpret critical comments in the same way we do this with positive reviews? Or do we push 20 good customer reviews in the back of our mind if we also read two really bad ones?
In our humble opinion, the 5-stars customer review system causes more confusion than it helps. Advertising or customer reviews cannot be in the same street as a personal 1-to-1 recommendation from a friend or a family member. These recommendations are valid and relevant — as they mostly come from the heart. (In fact, we don’t recommend bullshit to friends, do we?)
Recommendations could not be reinvented. We permanently recommend things to each other we’re positive about. Pay attention to it!
We’re just lifting the personal recommendations to the next level:
From word-of-mouth to word of mobile.
But this is another story…
Source (in german): http://t3n.de/news/soziale-produktempfehlungen-amazon-nutzt-empfehlungen-276522/