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Propensity or influence? During the past months we’ve had several discussions internally and with our customers about virality. Our experience clearly shows that not everything is viral in marketing. Churn virality varies in different networks and there are cases where churn is not viral at all. Product marketing is a more potential case, but it’s become clear that the viral spread totally depends on the attractiveness of the offering.

This week I attended a seminar on how to do marketing in Facebook. One of the success stories was the launch of a new IKEA store in Malmö – a campaign designed by ad agency Forsman & Bodenfors in Sweden (check IKEA Facebook showroom campaign ). They succeeded in creating an incredible viral spread by allowing people to tag IKEA items on the store manager’s profile page, and get the items for free. Obviously a compelling offer – but the point of the designers was that if you want things to spread – it’s all in the offering. Simple ideas usually work best. You are fighting for your customers’ time, to succeed you need to offer them something worthwhile, and your brand needs to be something they are willing to promote. How do you find such ideas? These guys advice was – gut feeling.

This basically means that you are working on a trial and error basis. It also means that finding so-called influencers in your network will not guarantee viral spread. Influence is always context related, and you need to find the first tier targets to get any results at all. That’s why we put so much emphasis on finding the people that have the highest propensity in each context. At the same time we find the ones with the highest influence on others. So, if your gut feeling was right and you have a killer offering, you’ll get both the high first tier pull rates and the virality. But if you cannot find even the first adopters for this particular offering – you’ll have no virality either. Simple.

The good news is that if your offering is relevant but not viral (and you will have lots of these), you need to find the customers with the highest propensity in each case. These revenue streams are what matter for your business and they directly affect your bottom line.

More than two thirds of the world’s mobile subscriptions are prepaid. Yet the marketing discussions mainly revolve around postpaid topics, and the problematics in how to know more about and reach the prepaid customers are left in the background.

Lately, Xtract has worked closely with several large prepaid focused operators on both churn and product marketing. Together, we have found critical issues that we have solved, for instance in churn definitions as part of the analytics process.

At the end of January, our Product Marketing Manager Mikko Röntynen will speak on these topics in Kuala Lumpur, Malaysia, at the IQPC event called Prepaid Mobile Summit 2010. His topic will be:

Driving the value of prepaid customers using Social Intelligence
· What is Social Intelligence and what can it reveal about your prepaid customers?
· Demographics prediction as a basis for targeting in marketing campaigns
· Finding right targets for effective customer retention, product up-sell and customer acquisition campaigning

Improved insight and targeting to prepaid customers is a key strategic focus for Xtract in 2010.

Helsinki, Finland and London, England — 8 June 2009 – Xtract marketing director Arlinda Sipila will be chairing and speaking at the IIR Business & Telecoms Business Intelligence event this week in Amsterdam.

Today, Sipila will chair the pre-conference workshop, “Subscriber data – A goldmine of opportunity for mobile operator marketing.” The agenda for the session includes the following talks:

10.00 Subscriber social networks, social Influence and 3D customer profiling
10.30 Making it easy for the operator to utilise social intelligence for business
11.30 Monetising with social intelligence

In addition, on day two of the conference, Wednesday 10 June, Sipila will deliver a presentation titled “Social network intelligence: Utilising customer data effectively in marketing,” at 10:20am. The presentation will discuss topics including:

• The ‘active’ footprints that users leave behind in social media and how they can be analysed for improved, more individually relevant, marketing and advertising
• Mining the stories that customer data can tell an advertiser, and the sometimes-competing goal of maintaining user privacy

To schedule a one-to-one briefing with Xtract, or to obtain a copy of the presentations, please use the press contact details below.

About IIR Business Intelligence Conference
Held in the Hotel Okura, Amsterdam, Netherlands from Monday 8 June to Thursday 11 June, the conference will include speakers from companies including O2, Orange, Amdocs, Vodafone and Xtract. The programme will focus on practical strategies currently being deployed worldwide to optimise the planning, building and improvement of business intelligence.

About Xtract
Xtract (www.xtract.com) refines social interaction, behaviour and demographic data to create accurate 3D user profiles. These profiles for the first time utilise data as a dynamic tool in the day-to-day marketing for effective and intelligent targeting of campaigns and advertising. Xtract’s Social Links is an automated, self-learning solution capable of analysing billions of mobile transactions with easy to use and actionable tools for operators to define accurate target groups for their marketing campaigns.

Press contact
Emily McDaid
emily(at)hatch-pr.com

I was in the Social Meets Mobile event in San Francisco in the last week. The discussion included many interesting topics how social networking is coming to mobile. More than 50% of MySpace traffic should come from mobile in a couple of years. One interesting topic is also, what is social communications vs. social networking.

Social Networking is now associated strongly to certain type of services like Facebook. But social communications is basically all methods to be in touch with other people. And it is must more than social networking. This is actually something Xtract has emphasized long time, when we have made social network analytics e.g. from mobile communications. And now we can say that a person use at least calls, SMS, Facebook, LinkedIn, Twitter, and IM to her/his daily communications. How to manage all that communications, how to keep relevant contacts, how to find/filter when you get too much, etc.

There is a huge need to manage all this better. Many firms develop tools for web, but e.g. mobile device companies sees that they have important opportunity here, because a mobile device can be the home of important part of the communications. And a kind of meta trend is that internet is coming more a conversation platform than a stable home page platform. That puts pressure also to players like Google that has been the tool to navigate in the jungle, but now we go to a new kind of jungle. I believe strongly that social network awareness come a mandaory component to help users in this new jungle, but also to help marketers and advertsisers to find right people and send relevant messages.

An Alpha is similar to a champion or an influencer. Nevertheless, in addition to having high influence and links in the community, the Alpha also has high probability to buy some of your products, acquire more customers or churn away. So, there are different kinds of Alphas and today I want to tell you how we find the Acquisition Alphas.

For Customer Acquisition, we use highly advanced analytics software that can process billions of data points. This powerful software is highly accurate. We find exactly those subscribers that have the highest potential to recruit new ones from another network. We take into account their influence level and number of off-net (out of your network) friends.

The illustration shows subscribers that have high or low influence and that might have off-net friends. Xtract identifies that the subscriber with the green circle has off-net friends (the ones in yellow) as well as high recruiting influence. This means that she would be the best target for your member-get-member campaign.

Finding the Alphas in your customer base is like finding gold in a goldmine. Remember! You need your Alphas and you need to treat them well.

When I read Jay Alabaster’s article on the Japanese behavior on social networking websites, it made me realise how difficult it must be for some companies to get any customer insight from their customer base.

According to Jay, “the vast majority of mixi’s roughly 15 million users don’t reveal anything about themselves” and keep in tight groups, to which he adds that “fewer than half of Match’s paying members in Japan are willing to post their photos, compared with nearly all members in the U.S”.

Must be so frustrating to sit on so much data and not be able to get any useful insight extracted. I wonder how companies like pixi.jp handle it, considering users have fake profiles, or then companies like match.com considering how differently users behave from culture to culture around the same service.

Xtract is proud to sponsor the 6th International Workshop on Mining and Learning in Graphs that features such keynote speakers as Fan Chung (University of California, San Diego), Thorsten Joachims (Cornell University), Mohammad Mahdian (Yahoo! Research) and Hannu Toivonen (University of Helsinki). The registration is still open; for a discount price for today only. The workshop will be held in Helsinki, our home city, on 4-5 July.

Quoting from the conference web-site, MLG’08

“will be the premier forum for bringing together different sub-disciplines within Machine Learning and Data Mining that focus on the analysis of structured data. Of particular interest is data that consists of interrelated parts or is characterized by collections of objects that are interrelated and linked together into complex graphs and structures.”

Last year our team participated in MLG’07 in Venice with the paper Inferring vertex properties from topology in large networks (Janne Sinkkonen – Xtract, Janne Aukia – Xtract, Samuel Kaski – TKK) and won a prize for distinguished contribution.

Our team has a paper in the workshop this year, too. I’m excited in meeting you all there in a cozy scientific atmosphere and venue for insightful presentations and discussions.

Google has published their mobile and social network platform plans during the last week. Not so many surprises.

OpenSocial is quite natural next move from a company that wants to collect a lot of data. Social networking platform is a valuable source of behavior and social network data. And it is much more than have one or two social sites. The main concept with mobile has similar objectives. Who will dominate mobile usage and social data in the future. And finally who will prevail in digital media marketing.

But is it so simple that one company can prevail all relevant data in the future. Is it even possible that one company can collect all data when there will be more and more data all the time everywhere? I believe they can collect a lot of data. But on the other hand I believe that the services and data will be much more de-centralized in the future.

Intelligence comes nearer users and user devices. Smart analytics, customer profiling, and social intelligence come also to terminals (PC or mobile). The best solution to challenge Google is not to try to collect more data, but to have more intelligence to utilize the data. And this kind of analytics and advertising solutions help media and mobile companies to challenge Google.

Here at Xtract we get to work with data sets which are often in the form of networks. These may be, for example, social network data sets in online forums or links between web pages.

Often it would be useful to draw pictures of these networks, to understand better what their structure is. However, with networks that have millions of nodes, this is in practice impossible.

The problem of visualizing large networks is a common one and many different mathematical and aesthetical approaches have been taken to tackle it. Visual complexity is an interesting website, where a large number of network visualizations are presented.

When Arlinda asked me to write something about my master’s thesis on the company blog, I was stumbled. Thus is not because I wouldn’t have anything to tell about the thesis. Instead, I have been basically living the thesis for the last eight months, which makes it difficult to pick any single viewpoint to the work.

The topic of my thesis work is Bayesian clustering of huge friendship networks. It discusses methods to find structure in large networks, such as networks of friendships and presents an algorithm for this purpose, originally devised by Janne Sinkkonen, the chief researcher here at Xtract.

The algorithm finds overlapping group (i.e., cluster) structure of nodes. In each group the nodes are expected to possess similar traits and each node may belong to multiple groups.

The method studied in the thesis uses a Bayesian model of friendship formation, which is based on the theory of homophily studied by sociologists since 1950’s. What is nice about the approach is that it not only tells into which groups each node belongs, but also about the certainty of the group assignments.

It was interesting to do the thesis for a company, because there was a real need for the algorithm: The algorithm and its implementation are now being taken into use in customer projects. This is different from the academics, where the developer may often be the only one to ever use a reference implementation.

You can read more about the algorithm from the abstract we wrote for the MLG’07 -workshop: “Inferring vertex properties from topology in large networks”.