Big Data Technolo...
Find tag "reporting"
15.6K views | +61 today
Big Data Technology, Semantics and Analytics
Trends, success and applications for big data including the use of semantic technology
Curated by Tony Agresta
Your new post is loading...
Your new post is loading...
Scooped by Tony Agresta!

Big Data, Analytics And The Future Of Marketing And Sales

Big Data, Analytics And The Future Of Marketing And Sales | Big Data Technology, Semantics and Analytics |
By Jonathan Gordon (@JW_Gordon), Jesko Perrey, and Dennis Spillecke (@dspillecke) Big Data is the biggest game-changing opportunity for marketing and sales since the Internet went mainstream almost 20 years ago.
Tony Agresta's insight:

Digital data can translate into higher sales with the right automation and analysis in place.   Thirty five percent of pre purchase decisions in the B to B space are made through online research.   Those interactions can be used as leading indicators and potentially trigger points to engage with personalized messaging.   In the B to C world, predictive algorithms have been used for years.  For example, Banks can determine the next most likely next product purchased and retailers can prevent defection with special discounts offered in real-time.  


When applying these types of solutions, the dimension of time can be critical. Are transactions slowing down for a specific customer?  Is website access accelerating?   Are downloads of valuable content happening more rapidly?  Are your customers starting to visit competitive sites more frequently? 


There's no shortage of data available to answer these questions.  But the variety of techniques (and the complexity of some) to address these issues can be daunting at times.   Analyzing trends over time to isolate important milestones in the customer lifecycle is one way to begin.   Organizing your customers into small sets of homogenous segments is one way to begin.  Are there segments that buy from multiple product categories frequently?  Are there other segments showing a decline in transactions?   Once these segments are identified, isolating patterns of behavior within the segments could lead to a set of rules and event triggers used to personalize messages, improve customer service, introduce new products and offer discounts.  


Big Data platforms that allow you to ingest massive amounts of data, classify the data in real time and take action right away can be applied in game changing ways.   Sales and Marketing professionals should focus their attention on customer behavior leading to retention, upsell and improved customer service in a world where competitive pressures are not going away anytime soon.

No comment yet.
Scooped by Tony Agresta!

HSBC to Pay $1.92 Billion to Settle Charges of Money Laundering

HSBC to Pay $1.92 Billion to Settle Charges of Money Laundering | Big Data Technology, Semantics and Analytics |
The announcement of a settlement on Tuesday came after state and federal authorities decided against indicting the British bank in a money-laundering case.
Tony Agresta's insight:

If you read this, notice one of the last paragraphs - 


"HSBC has since moved to bolster its safeguards. The bank doubled its spending on compliance functions and revamped its oversight, according to a spokesman. In January, HSBC hired Stuart A. Levey as chief legal officer to come up with stricter internal standards to thwart the illegal flow of cash. Mr. Levey was formerly an under secretary at the Treasury Department who focused on terrorism and financial intelligence."


Big Data Analytics is one way to do this.   But HSBC may have fallen into the trap where they focus on one form of analysis to detect money laundering.  Predictive models used to identify transactions that may be fraud or money laundering can be a useful way to detect this type of activity.   But all models contain some amount of error.  When network analysis, geospatial analysis and temporal analysis are also applied, money laundering schemes can be revealed using data visualization that show unusual patterns of behavior, linkages between people and events, fund transfers that take place at odd times and more.   Most of these institutions need to combine descriptive reporting, alerts which are triggered when outlier transactions are ready for approval, predictive models and interactive data visualization including link analysis to explore hidden relationships in data.   Without this comprehensive approach, this problem will continue to occur.  The data is all there.  Now it needs to be integrated (including unstructured data in the form of notes) and analyzed using all of the major techniques.

WebMarketingStore's comment, May 2, 2014 1:59 AM
Staggering: $1.9b is the 'settlement' amount? How much might the damage have been, full-tilt?