Hadoop: the bid daddy of big data?

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Just read a great article from Dan Woods in Forbes : “a quick guide to choosing the right way to use Hadoop”.

Normally, I would declare myself unfit to write or comment about technology but the eruption of Hadoop in the  enterprise software world is remarkable.  Every vendor is now grabbing a piece of the open source Apache based framework like if it was the new pill to cure the headaches of Big data.

But what does Hadoop offer to marketers?

  • Clickstream Data.  Just like the best analytics solutions out there, Hadoop can be tasked to analyze visits of a web site or mobile app and reveal how users engage with products and services and converts.  Big deal right? Wait! there’s more:    Hadoop can link clickstream data with other data sources like Call Center activity, CRM data on customer engagement and demographics, sales data from off line POS systems etc… CMOs of any brick and click corporations should already be riding the elephant.
  • For the record.  Remember the last time you were ambushed in a meeting? “How do this promotion fared this year compared with 2011?” Well, Hadoop scales easily so you can store years of data at low cost, then perform “archeological” digging. Imagine decades of clickstream data stored on cheap machines ready to be unhearthed… Ambush become a thing of the past and best of all ; when you dig up old data  you might discover a missing link in the evolution of your marketing campaigns.
  • Social media posts, blogs, online product reviews and customer support interactions provide the messiest data available to marketers. Sentimental or emotional data always come unstructured yet we absolutely need to analyze it to understand how consumers engage with our brands. Hadoop can be used to assign a score of positive, neutral or negative to every little piece of comments about your company or your products. By scoring and aggregating millions of interactions, Hadoop can scale sentiment and emotions in real time.
  • Easy and reproducible integration with existing BI or CRM systems even with a simple SQL database via proprietary frameworks. Messy anonymous or semi-anonymous social signals can be attributed to a particular customer or segment of customers.  Combine signals together to spot new trends in customer demand.

I am just scratching the surface here… Hadoop can also be the pill to cure marketers anxiety attacks when it come to big data. I strongly advise you to take a long and hard look at the yellow elephant. Maybe it will end up on your Christmas list this year.

Frederick Buhr

Great read about Hadoop:

The three most common ways data junkies are using Hadoop

Apache Hadoop in Theory and Practise

Customer segmentation on a pauper’s budget

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You read it on every blog, in every marketing book, at every industry conference: Segment! Segment! Segment! But what to do when you have no budget and very little time?
To add to this daunting mission, you discovered that your company legacy systems are disparate and they don’t talk to each other. Each department holding a crucial piece of the customer data like Milton was holding his stapler in “Office Space”.

Before you run to the hills and find another job selling granola to sheep shavers, there are concrete steps that you can take right now on the path toward full digital intelligence.

All you need is planning and some smart implementation decisions using low cost or free tools

5 steps to get started with segmentation:

1. What campaigns do I want to launch?
2. What information do I need to know about our customers?
3. How can I collect this information?
4. How do I deliver my campaign to a specific customer segment?
5. How do I Optimize my campaigns

Step 1: define an initial set of campaigns:
• Map out the customer cycle on your site
• Brainstorm for opportunities at every stage of this cycle
• Draft campaign ideas and messages

Step 2: What visitor data do you need to support your campaigns?
• Go over each of your drafts and find the underlying data you need to properly execute them.
• Identify data sources
• Compare the set of data you need with the data you already have in your systems. Identify gaps.
• A single visitor identification is important, especially if you are merging new with old data.

Step 3: design and implement a data collection and consolidation strategy
• Determine where the data will be stored and aggregated
• Tag your digital properties to collect the required data
• Use Tag management solutions to abstract the data collection logic from your legacy systems

Step 4: implement the campaign delivery processes to your customers segments

• Create specific business rules,
• Evaluate message delivery options: email, on-site, off-site.
• Create message templates and content
• Launch your campaigns from easiest to execute to more difficult

Step 5: Optimization
• Harvest customer’s emails early in their buying cycle in order to have more opportunities for retargeting (off site) or remarketing (email, on-site)
• Implement “lazy registration” design pattern to collect customer behavior even when they choose not to register
• Test various messages to find the winning mix of offers and/or discounts

Frederick Buhr

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