Qik Mobile App Install: A Example of Best Practise

I rarely feel compelled to write a blog post because an install process for a web or mobile app is so good, but Qik has triggered just that compulsion. Qik allows you to easily record or live stream video from your mobile phone. The list of supported phones is growing fast; and you can expect the rate of engagement to explode once the iPhone 3GS is cleared for takeoff with Qik (currently you have to jail break your phone to get it working).

The point of this post though was to highlight the process they use to install onto your phone. In brief, you have the choice of being sent an SMS (supporting multiple countries), downloading it and then installing it via your PC (or “side loading” as the industry calls it), or visiting a WAP site (a mobile website) to download from a link.

However, the important bit comes once the install process starts on the phone. I click to receive the SMS, received it immediately; I think clicked the link in the SMS, it started downloading to my phone, but crucially, updated the page automatically to tick the box that install had begun, it then confirmed when install/download had completed and then when I had fired up the app.

Qik have an excellent mobile app install process from their website, closing the loop between PC and mobile & ensuring users complete the install there and then

This might seem simple but it is VERY rare this process is used; normally the site just sends you an SMS and you go on your merry way.  Closing this loop, provided you can guarantee speedy delivery of the SMS, encourages if not subtly forces the user to install the app there and then and to log in – making them feel comfortable and hand-held in the process to confirm that things are happening as they should.

A clever and slick way to help users get your mobile app onto a users handset.  When we have resource to make improvements to the Rummble website, my start-up which takes the vast majority of my attentions these days, we’ll be following this user experience as its one of the best I’ve seen yet. Well done Qik!

Peer Recommendation Is In Fashion, But There’s A Problem

With another article in last weekends Telegraph, with the Head of Bebo saying that peer recommendation is the way forward and the future no less of Social Networks, I can afford to feel very slightly smug that I’ve been barking up the right tree for the last 3 years, or more. Ms Burns says “I know and understand the power of search. However, social recommendations are the future…”

Kate Burns, Bebo Chief says peer recommendations are the future of social networking

My smugness should be short-lived however, as there are still two problems:

Firstly, institutional investors in Europe as yet seem unconvinced that now is the right time to invest in trust network technology or indeed associated consumer facing recommendation service optmised for mobile (Rummble has had lots of interest from VCs but thus far they’re yet to invest).  Business Angels have been very receptive, but the European VCs, in summary feel it is too early. We may yet move across the pond, to the sunny climbs of Silicon Valley, as a consequence.

Secondly and far more importantly, people (even the mainstream media, as the Telegraph article attests) are all talking about “peer recommendation” but forgetting a very important, indeed vital, factor: Trust.

There are a few problems with recommendations from your friends (i.e. your peers). Firstly, I have some fantastic friends whom I love dearly but with whom I do not share the same taste or opinions. That’s not a problem if I want to know from their newsfeed that they’ve gone on holiday, but it’s not so useful if I am recommended the Reiters Supreme Hotel they chose, in Austria, when I don’t golf and hate package holidays.  Secondly, even if ALL my 417 friends on Facebook, the 1400 contacts in my address book and the 500+ contacts on LinkedIn, ALL rated/recommended every place they went, there would still be 100’s of places in the world with no recommendations from them (and that is before you consider that they’d need to all use the same service or services between which recommendations were shared or collated).

While this does unquestionably serve to promote Rummbles trust platform technology as the answer to these problems, it is also the genuine flaw of peer recommendation services such as Geodilic and Whrrl, and of those services that blindly aggregate all data from your streams (e.g. FreindFeed).

Rummble Trust Network technology is not simply a social network, because it connects & infers trust (or lack of) between you and friends but also you and strangers

I am not saying the mentioned services are bad, I am saying simply that the focus needs to shift toward filtering information in a more intelligent way – reducing the noise.

Two of the Rummble team took 10 days out to build an experiment as a tentative step to help make sense of the burgeoning stream of data produced from Twitter; in reality the stream could have been from any social software. Tremors attempts to match Tweets with the venues they are from or referring to, to create a realtime feed of activity in venues across four major cities: London, New York and Austin Texas, with San Francisco to follow shortly.

Tremors is an experiment powered by Rummble

In this very basic first version, you can see what is going on at different venues in the city and it attempts to recognise some basic sentiment about the text. The next step, if we were to invest time in improving the accuracy, is that we could interpret the content as a recommendation (or otherwise) and ally this with content within the Rummble recommendation service.

Ultimately, we’ll be able to construct a trust network between users on Twitter whom may not even know each other, but share similar tastes or opinons, based upon an existing user behaviour. For now, it remains a fun experiment until we can resource improvements. You can read more about Tremors in the Tremors launch blog post.

Kate Burns of Bebo is probably right. Unsurprisingly, technology will evolve to build on and exaggerate existing human behaviour. We cherish personal recommendations because we usually have a basis on which to embrace or reject that recommendation. With social networks, I don’t always know how or whether to trust an acquaintance or a friend who may be outside of my core circle of trust, or whom I may respect but whom I may not know well enough to know if we share the same taste in restaurants or music.

In 2006 I presented a slide deck about “trust networking” and nobody seemed to understand what I was waffling on about; in 2009 I’ve presented a very similar a decks including trust networking and I often get nods of agreement and sometimes even yelps of excitement (see what I did there?

Our lives are built on trust and understanding (or lack thereof). Lets hope the Internet of the future is built on the trust and understanding part, not blind recommendations and lack of understanding.

Remember, “its about the data, stupid!”