Although we should have taken a break after finally launching the new improved user interface last week we got stuck right back into it! Check out the new features and enhancements we released this week as well as the respective screen shots below.

There seems to be an increased buzz around cross-channel media attribution from many vendors lately and although we posted on the subject of attribution before we never really got into the nuts and bolts of the different platform options so here you go.

Check out the below slides we recently pulled together for one of our clients - the 1st part is a recap on cross-channel media attribution best practice in case you're new to the topic but the 2nd part goes into the detailed pros and cons of the various different technology platforms we've had experience with.

• Google Analytics multi-channel funnels
• Adobe SiteCatalyst Cross-Visit Participation JavaScript plugin, Light Server Calls and DoubleClick/Mediamind Genesis integration
• Atlas, Mediamind and DoubleClick ad server based purchase path tracking plus custom media attribution modelling
• Specialised ClearSaleing media attribution platform and out-of-the-box reports

Finally, it's important to make a distinction between media attribution and purchase path tracking, one is necessary to enable the other but they are not the same. Tracking the complete purchase path, i.e. every paid and organic campaign touch point leading up to a conversion is a necessary requirement to be able to actually do media attribution or the allocation or conversion credits back to those touch points. The purchase path tracking is the data collection if you so want and the media attribution the actual analysis or modelling part - given attribution modeling is only as good as the underlying data the below slides are focusing manly on the data collection aspects of the different options.

Have you seen our SuperTag tag management platform yet? If not, check out the below screen shots. We think it looks much better now with the brand new re-designed user interface (based on the Twitter Bootstrap framework).

Apart from improving overall usability and design, the whole front-end was actually re-vamped which you can't actually see but lead to a significantly improvement in performance - the app is really snappy now. Contact us for a demo if you think your company could benefit from a container tag!

If you are a website or database developer (or an analyst with exceptional technical skills) with anywhere between 1 to 4 years of work experience (ideally in a digital agency environment) who would like to get into marketing analytics then you should apply. More experienced developers are welcome to apply as well.

+ Keen interest in all things web analytics and online optimisation
+ Basic understanding of marketing principles provides a head start
+ Entrepreneurial spirit, business or marketing degree would be good 

+ Strong JavaScript and SQL coding skills, PHP and HTML a bonus
+ Experience with other database related technologies another bonus 
+ Experience with Omniture and Google Analytics would be fantastic
+ Experience with Google Web Site Optimizer would also be useful
+ Basic understanding of HTTP and FTP protocols an absolute must
+ Flexibility, lateral thinking and attention to detail are crucial
+ Ability to respond to client deadlines when necessary
+ Basic Excel, Word and PowerPoint skills

+ Exposure to a growing list of interesting blue chip clients

+ Highly flexible working hours in a dynamic team environment
+ Young start-up with a "work hard, play hard" company attitude
+ Training on industry leading analytics and marketing platforms
+ Freedom to experiment with emerging technologies and new tools
+ Plenty of development and career opportunities in fast growing business
+ And of course you get a salary, maybe even a bonus plus other perks

If the above sounds interesting, please email us at jobs@datalicious.com so we can have a look at your resume and arrange a quick initial phone interview to ask you a few questions before we meet for a proper interview.

Amazon have turned on access to Dynamo, which runs much of the infrastructure behind Amazon Web Services and provided the inspiration for Cassandra. All your data is hosted on SSDs (Solid State Drives) which means it should be pretty damn fast.

In tech terms this is a tuneable-consistency and throughput key-value store. That means you can dial up or down the resources (and cost) depending on your performance and consistency (whether or not the very latest data is available in your query) needs.

This kind of thing is useful in applications where you've got unknown and changing volumes of data turning up that you want to mine in real time, that will eventually grow to enormous volumes that you still need to be able to store and mine quickly. Web analytics is a good example: you don't know how many people will be hitting your web site, so you start with the default "5 writes/second" but can dial it up and back when there's peaks of load. If you use something like NodeDB to do the data collection and inserting, any backlog of data writes will just queue up until it gets in if there's momentary peaks in demand.

Querying these key-value stores isn't as easy as with relational databases, which have had over 40 years of development and can be very flexibly queried. The advantage they hold over relational databases is that they scale linearly. If a query on 100 records takes a second, a query of 100000 records will also take a second provided you throw 1000x the hardware at the database server. Relational databases are very hard to scale this way once you grow past small clusters of machines. With relational database clusters, ensuring each replica of the data is consistent takes up ever-increasing fractions of the resources, meaning the scaling curve is anything but linear.

The full blog post from Amazon.