Archive for February, 2012

28
Feb
By Stephanie in Interactive marketing on February 28, 2012
   

On a recent webinar, Rob Bronson from Forrester Research pointed out that 45% of Big Data implementations are in marketing.  One of the use cases we most hear about for customers is the need to move from single-touch attribution methods like last-click and first-click to multi-channel, multi-touch attribution.  Today we announced an extension of our Digital Marketing Solutions to deliver multi-touch attribution. 

When I speak with customers about moving to multi-touch attribution it feels like hearing about HDTV for the first time.   More clarity, more detail, and a richer experience that is more like the real-life experience of consumers.  So, multi-touch attribution is basically the HD equivalent of single-touch attribution.

What’s different?  First of all, consumers interact across many touch-points, social, mobile, search, websites as well as offline channels.  Most existing attribution solutions look at multiple touch-points within a single channel, like an ad network or web visitors.  With a Big Data Analytics approach it is easier to blend more channels into the mix and find customer connections.

This is critical today, because it better reflects the customer journey.   To be customer-centric, it is critical to be able to look at your brand through the eyes of the consumer.  A few years ago, this was impossible or at least difficult and expensive.  Now Big Data marketing analytics makes it possible to see the multi-channel journeys with incredible clarity.

As consumers dynamically adopt new technologies, keeping up with them is one of today’s marketers biggest challenges.  To do that, you can’t be stuck in legacy single-touch or annual reviews of attribution.  Big Data Analytics makes it possible to discover new patterns, test new programs and iterate to optimize in the time scales that the market demands.

An additional value is that Big Data Analytics can deliver a 3D-type enhancement to attribution.  Teradata Aster gives you the ability to use different measures for each touch point so you can use uniform, variable or exponential weightings in your model in order to test and iterate to get the right approach for your business.

Another big difference using Teradata Aster to analyze attribution is to be able to link to additional data in a Teradata Data Warehouse to include Revenue, Profit and Lifetime Value which extends attribution beyond conversion to real bottom-line performance.

Lastly, the ability to integrate into the Aprimo marketing platform makes this insight actionable.   With Aster and Aprimo being part of Teradata, it becomes possible to operationalize your Big Data Analytics more effectively.

The infographic above highlights why some marketers might feel like they have an attribution problem.  You can download a PDF of it here. On the same page, you will also find a white paper we created with Aprimo to go into more detail around what attribution looks like today, and an On-Demand webinar with Forrester and Razorfish that looks at attribution in some depth.  For those who want to read more, check out an addition to this Delicious stack.

So my question for this post is – Do you have an attribution problem?  And if so, how can having multi-touch, multi-channel attribution model make it better?



21
Feb
By Tasso Argyros in Analytic platform, Analytics, Analytics tech, Database, MapReduce on February 21, 2012
   

It has been about seven years since Aster Data was founded, four years since our industry-first Enteprise SQL-MapReduce implementation (first commercial MapReduce offering) and three years since our first Big Data Summit event (the first “Big Data” event in the industry as far as I know). During this whole time, we have witnessed our technology investments take off together with the Big Data market – just think how many people had never even heard the word MapReduce three years ago, and how many swear by it today!

As someone who was caught in the Big Data wave since 2005, I can tell you that the stage of the market has changed significantly during this time – and with it, the challenges that Enterprise customers face. A few years ago, customers were realizing the challenges that piles of new types of data were bringing – big volumes (terabytes to petabytes) and new, complex types (multi-structured data such as weblogs, text, customer interaction data); but at the same time, the opportunities that the new analytical interfaces, like MapReduce, were enabling. Fast forward to today and most enterprises are trying to put together their Big Data strategies and make sense of what the market has to offer – and as a result there is a lot of market noise and confusion: it is usually not clear what use cases apply to traditional technologies versus new; how to reconcile existing technologies with new investments; and what type of projects will they give them highest ROI versus a long and painful failure.

Teradata and Teradata Aster have a high interest in customers being successful with Big Data challenges and technologies, because we believe that the growth of the market will translate into growth for us. Given Teradata’s history in being the #1 strategic advisor to customers around data management and analytics, we only want to offer the best solutions to our customers. This includes our products –which are recognized by Gartner as leading technologies in Data Warehousing and Big Data analytics– but also our expertise helping customers how to use complementary solutions, like Hadoop, and making sure that the total solution works reliably and succeeds in tackling big business problems.

With this partnership, we are taking one more step towards this direction. So we are announcing three things:

1. Teradata and Hortonworks will work together to jointly solve big challenges for our customers. This is a win/win for customers and the industry.

2. Our intent to do joint R&D to make it easier for customers that use products from Teradata and Hadoop to utilize these products together. This is important because every enterprise will look to combine new technologies with existing investments, and there is plenty of opportunity to do better.

3. A set of reference architectures that combine Teradata and Hadoop products to accelerate the implementation of Big Data Big Data projects. We hope that this will be a starting point that will save enterprises time and money when they embark on Big Data projects.

We believe that all the above three points will translate into eliminating risks and unnecessary trial and error. We have enough collective experience to guide customers to avoid failed projects and traps. And by helping clear up some of the confusion in the big data market, we hope to accelerate its growth and the benefit to Enterprises that are looking to utilizing their data to become more competitive and efficient.