Chinwag ran a very interesting session last night on the differing (and competing?) roles of search and review sites in retail therapy fulfilment.

Phil Wilkinson has done an amazing job of writing the gist of it up over here (thus absolving yours truly of the need – props Phil). I’d like to comment on a number of the points Phil makes:

1: Recommendation sites need search engines to drive any traffic to them

This one is hard to refute as 95%+ of journey’s start at a search engine and so if you don’t have good content to get ranked, you don’t get the traffic. End of story.

but:

2: Search doesn’t take into account the stage of the purchasing cycle that someone is currently at.

Take the example of typing in “television reviews” – pretty easy to work out what they want but this type of search is tiny traffic compared to words like “televisions” and “sony televisions”.

One of the things we didn’t get round to is the CPM per visit though – one would assume that ads on a review site may be more useful, as you have established intent which is not clear on a search site. Any ideas welcome.

3: If retailers got their acts together, would anyone really need to use recommendation or review sites

A very interesting question. The argument is about where should all the juicy reviews, product information, and recommendations actually sit – at the search engine level, at a product recommendation site, a magazine review site, a price comparison engine, or the end retailer?

This is a very good question – Amazon does its own reviews, probably because of the sheer range it has. But one can imagine specialist retailers, or other large retailers, taking over this role. It is hard to understand what specific benefits a 3rd party site has, especially if the retailer makes completion very easy.

This issue is related to the following:

4: There are other forms of communication that can help in the buying process that miss out both search engines and recommendation sites altogether

Twitter was mentioned as a good example of this where someone asked their friends and followers “what digital slr should I buy made by Canon?” and got a raft of good responses. These ranged from actual product recommendations to pointing them to sites and discussion forums where people were already taking about this kind of thing and helping each other out.

I had a similar experience buying a DSLR camera – the issue being that the review site is just one part of the continually iterating workflow of making a purchasing decision, and Twitter, Flickr and Yahoo discussion groups etc all came into it. Another issue is that review sites are good at the “look at this” but comparing X vs Y is harder. Also, with SLR cameras for example, there is a whole secondary discussion around which lens combinations to use – a multi-factor discussion. I wanted statistical view that you get a glimpse of with Amazon “people also bought”, but all I could get was a few opinions on various sites.

Another point Phil makes is:

5: Do people really care about trust?

So one of the main arguments about why recommendation sites can top results from a search engine, is over the degree of trust they can utilise between sources and people. Google uses it’s algorithm to try and work out which sites are the most relevant and trusted by other “website owners” where as recommendation sites try and show reviews and comments filtered by trusted people in the community or network who have something valuable to say and not just trying to game the system.

My experience of Google product search (in the UK anyways) is the front page is too often filled up with sites that are clearly just trying to grab the traffic, and have no real content themselves but provide a list of other sites to go to (if you are lucky – I’d love to have a button that instantly blacklists those sites).

On the other hand, with review sites:

What would you prefer – 2 recommendations from a friend and colleague or 45 reviews from anonymous people? I haven’t found any data to support either side right now but it’s an interesting question nonetheless that needs some answers.

Actually, I’d probably trust 45 others, its big enough to be a random sample – so long as its not gamed, as can happen – even on Amazon. But people authenticate themselves better on Twitter than Amazon say, so is that a more valuable opinion? It is an interesting game theory / behavioural psychology – how many anonymous users are worth 1 friend? A friend who knows about the stuff vs one who doesn’t?

The other thing that wasn’t really covered was the economics – the tradeoff value of item vs transaction costs of the buying experience. Its just not worth providing the same levels of service for a shirt purchase vs a car, say. A camera is somewhat inbetween. Or how about restaurant selection vs holiday selection?

Phil’s Conclusions:

This entire space about how people choose and recommend products and services to each other is much more complicated than I ever imagined, and luckily I’m not the only one who thinks that!

Thats my impression as well – my instinct is that this whole arena is in very early days, and there are considerable rewards to getting it right – which is of course why its one of the areas we are collaborating with in background research.

I was most interested in the one speaker’s note (from Bazaarvoice? I didn’t catch name or company) that they started off algorithm based, and are now adding social functions to get blended analysis. I suspect thats right – if I look at Last.fm vs Pandora, Last.fm optimises faster initially, but Pandora keeps on long after adding an extra friend to last.fm no longer helps converge to a solution