Who do you trust?

There has been a few reports that caught my attention over the summer. All have to do with trust online and the impact of social media on travel sites.

One of them was the Nielsen Global Online Consumer Survey, which includes an interesting measure of the forms of advertising most trusted by consumers.

90% trust recommendations from people they directly know, 70% trust consumer opinions online and brands. 69% trust editorial content.

Below is the full diagram and the press release can be found here.



"Recommendations from people known" stands very much alone at the top.

Not so surprising. We are far more inclined to listen to these than to those we don't. People we know have a great advantage as information providers. We are instantly able to filter what they say, because we know their taste. We know when to trust their judgment and when to discard their recommendations.

But that doesn't necessarily mean that the information delivered by them is better. I'm not saying recommendations from our social graph (people we know) aren't good, but they are usually too few to be really useful. A few simple reasons for this.
* We need information from people with taste somewhat similar to ours. After all, would you trust your grand parents recommendations to go clubbing?.
* We need a few advices to make an opinion. How likely is it that we know someone with taste similar to ours who's been where we want to go for holiday or more simply diner? The answer is not very likely.

An interesting complement to the Nielsen analysis would be to know the relative usage of these various forms of advertising. The top category is probably very small because of the reasons I've listed above.

And so we have to fall back on editorial content and consumers opinions, which are hard to trust, because we don't know the people who wrote them. While we may develop some level of trust with editorial content (as we get used to read the same person's article and develop what I would call a taste filter), we can't really do this with consumer opinions.

That's of course an area where we are very involved at LikeCube, We're changing the way people perceive User Generated Content (UGC) and we greatly enhance its value, quite a deal for web sites that have invested so much in UGC but are still struggling to see real value out of it.

In addition to providing really accurate personalized recommendations (some users have even qualified them as "quite spooky" in accuracy), our solution helps filter consumers opinions and extract the ones that are from people closest to us in terms of taste.

As a result, our solution can personalize each product page (think of a hotel or a restaurant review page) with reviews from our taste neighbors, reviews we can trust.

This solves a big issue for consumers when they read opinions ("Should I trust this person?") and I wouldn't be surprised if over time the 70% from the Nielsen report for "Opinion" moves toward the 90% from people we know, if not beyond.

Hotel industry in need of data or innovation?

In a recent interview from Sandeep Govil and Natasa Christodoulidou, the author was talking about the need to better understand your customer interaction with the hotel booking sites. Essentially, "hotels have a long way to go in talking to guests about the product, its attributes, locale, etc. in a way that each individual guest wishes to receive that information"

According to Natasa, "the key to working on CRM data gathering approaches in a manner that engages the customer as little as possible while obtaining the information that makes the biggest impact on the goals as a service provider is simply personalisation".

It is clear that there is a lot of value from capturing more data, as long as data is available. However, there is a significant challenge in the hotel industry. One that I usually describe with the number 4.

If users have used a site less than 4 times, then they are unlikely to use it by default for their next booking. They simply don't have much loyalty to the site yet.

Above 4, the users become more loyal to the site and use it as a natural starting point to their hotel research.

Now this is clearly over-simplifying a complex problem for marketers and CRM experts. But I think it's worth the analysis.

So in terms of numbers what does it means. Well the below 4 represent 95% of the bookings. 95%. To give you another representation of the challenge, the average number of bookings per user is below 2... Building user statistical patterns with such a low amount of data is unreliable. Hence the challenge of marketers and CRM specialists.

Now there is an interesting parallel that can be done here. 4 is also the number at which personalization solutions based on collaborative filtering (people who like the same hotels I liked also liked...) start showing interesting levels of accuracy and related impact on conversion rates. Before 4, consider yourself in a cold start situation.

We've addressed both sides of the challenge at LikeCube.

Leveraging our expertise in semantics, ontology and search, we provide very innovative solutions to address the cold start issue. Rather than asking data and trying to profile users as suggested by Natasha, our SaaS solution enables hotel sites to offer a powerful way for users to express their preferences and filter their results accordingly. Conversion rate improvements are expected to be of the order of 10% to 20%.

And for users that have crossed the '4' gap, our state of the art collaborative filtering solution could up conversion rate significantly more. The other key benefit here is that users get the noise filtered out automatically, including reviews and other form of user generated content. This of course results in drastically improved user experience. They will see first the content from their taste neighbors, the people most like them in terms of preferences, as opposed to hundred of reviews, most of which are non relevant to them.

So how are you going to differentiate from your competition to secure the 95% of users that are in cold start? And what are you doing to leverage your investment in UGC? Is data or innovation the answer?

Feel free to contact us at info@likecube.com for your free Site-Matcher evaluation.

Agile programming, god or bad

I was having an interesting discussion with my colleague, Ismael, today about Agile programming. I was arguing the benefits of Agile, and the use of stand ups in the morning, allowing to bring a team together and quickly review the project progress.

Ismael agreed in principle but felt this rigidity of standups was against the whole principle of Agile... and he cited one interesting blog from Steve Yegge

Steve's definitely loving his job a Google!!! I love it I agree there is a lot to learn from Google's way of doing things, just like there is a lot to learn from Academia or the way startups work.

In my previous company, I remember when engineering started to introduce agile programming very much like google's way. The first thing they said to the business is: "forget being rigid about a delivery date. We will launch whenever we are ready to launch".

OMG, be assure a lot of adjustments had to take place. This wasn't well received because it felt that engineering wasn't tuned to the need of the company.

One specific area that was highly dependant on launch date was the launch plan and all the activities around it (training, marketing activities, enablement of partners, trade shows, press releases, analyst briefings, etc).

These activities take up to 2 - 3 months to execute. So the business needs to know in advance when the release date is, so that they can best invest their precious marketing $ to maximize the buzz in the market and attract the most new potential customers.

Clearly Google doesn't have that pb, nor does academia or pre-customer startups.

As Keith puts it in his comment to Steve's blog:

"Yep, and why is that? It's because most of us in our industry are writing sotware for paying customers (who might happen to share an employer with us) who have a "soft real time" idea of the value of the features we build: ie, the value of the features is at a maximum at some time t and declines, perhaps rapidly, after that. These three kinds of development are all quite unlike this.

Google's products and services seem mostly to exist for the purpose of making online advertising through Google more attractive, and that's a continuous process.

My client's projects generally exist to make some business process 1) possible, 2) faster, 3) higher quality before the competition do that. The business sponsors of these projects want to know when the benefit is going to start acruing. So they need schedules. Rightly or wrongly, that's what they need. And that's why (in contrast to the named methods that camed before) the Agile methods tend to put an emphasis on early delivery of business value, and hence the focus on schedule. In XP, though, note that we would rather reduce scope that slip a delivery. "

This said, at my previous company, the business has learned to be more flexible about release date and engineering more accountable about their progress toward a set goal and more transparent about the planned released date. All in all, best of 2 worlds.

I am now looking forward to leverage even more this approach with LikeCube.

The good news about the IPO market...

Todd Kimmel's post, Advanced Technology Ventures, warns that the IPO market will basically remains idle for the next 18 months.

"The IPO window is closed and likely won’t re-open until 2010."

However this downturn will profit a few players in the markets, and these are the very small companies. The reason is that early-stage companies have very small burn rates and can more easily afford focussing on catching up or developping new technologies, while the medium size startups have to downsize and struggle to support an existing customer base.

As Kimmel's puts it: "This is not good news for anyone, except early-stage companies that plan to have their heads down for the next year or more working on proofs of concept and reducing technology risk. Those companies will be in a better position than those in need of capital to scale."

So are we going to see a few Davids out-smart Goliaths in the next 18 months?

Semantics...

I was working on getting up to speed with my new venture, LikeCube, which I am joining this month. LikeCube is a fantastic team combining over 16 years of semantic academic expertise. I have too say I got a lot of catch up to do here. Though my job will be less the technology and more driving the company through first customers and investment

This said, I needed a good refresh and this blog put Semantics in simple words... And I found it quite amazing how much LikeCube aligns with most of the points in this blog.

I am a firm believer that their is a huge opportunity in the market for companies seating between the content providers and the consumers. This is our sweet spot.

The slow rise of social search

There been quite a bit of talks recently around social search growing fast, led by Myspace and Facebook.

As the Wall Street Journal pointed out, online marketing is dominating advertising with a healthy 20% growth, despite the economic turmoil.

Interestingly, simple advertising remains the preferred way, the low hanging fruit as opposed to complexly designed ads.

It also seems that Facebook is under exploiting their search monetization. Even though Myspace has tried to crack the space with their Google deal, it is believed to be under performing as per Google.

So when will the large social networks start leveraging their social graph to deliver better search? This remains a highly complex field to be able to calculate taste neighboors and apply them to do better search result or recommendation. Who will be the first?

Web 3.0. It's all about you.

So back to this Web 3.0 story.

The first generation of the web was all around e-commerce and making your inventories available for sale on the web.. winners: ebay, amazon. All this worked really well because no one except for the companies themselves could modify the content of their sites... so company centric, controlled content were at the core of of Web 1.0

The second generation of the web (The Community Strikes Back) saw the rise of the uncontrolled content generation. Blogs allowed the masses to instantly comment, share, communicate, exchange, express, basically participate in the web content, no longer under the corporate control of the few businesses in charge. Everyone could become a critic as well! Imagine those companies having spent millions on fine tuning their product messaging, and here comes the average student from his dormitory slashing through the product in no more time than it would take to mix your gin&tonic... ahhh... So the Web 2.0 is all about the community and the uncontrolled generation of content

Well here comes the web 3.0, leveraging the 1.0 marketplace, the 2.0 community and focusing on the last bit that wasn't addressed properly so far, you, me, the individual itself.

Today's challenge resides in making use of the amazing amount of unstructured content. And the best way to make use of it is to make it relevant to every single person... And one person trust as much his close friends (in the real world) as well as his digital friends (the communities) as well as the professional critics (cf web 1.0 companies)

So Web 3.0 is all about you, your tastes and what you like.

Who do you think will control the future, the companies with large amount of content or the ones able to recommend the right content to the right person, even if the content they own isn't as large? I bet on the last one.

Hello World!

The easiness of starting a new blog (this one took me 21 sec!) is one of the single most important factor in the pace at which the personalized recommendation industry has been growing. Indeed today everyone can be a critic. Well that's nothing new from the past, you could be a critic to your friends, recommending or not to go see a movie. But the main difference today is that you can broadcast your experience to a far wider audience.

This has started to generate quite a bit of problems with the professional critic industry. Like the music industry, they started rebuffing the underground movement, claiming that because they didn't have any proper credentials, Mr Lambda critics weren't as good as theirs. Well why would they? after all, the professionals have been witting them for years and years, know their market sector inside out, know the trends and fashions, places to be and the one to abandons. They even know what we, the un-professionals, are supposed to like. Hence their professional critics are tuned to a very specific ecosystem of readers, market sector, geolocation etc.

But unfortunatly for the professional, I personally care as much for the professional critic as for my friend's recommendation, if not more for the latter. The trust factor! Why would I trust more someone I don't really know as opposed to someone that I know, that I probably had many smashing parties with, seen fantastic movies and tried the best restaurants in town... according to my taste at least.

Well all this to introduce a topic that I've been interested about quite a bit recently, which is the personalized recommendation market, something fascinating, which is the essence of the web 3.0...

I'll come back to it in my following post.

Cheers.

Manu