Big Data & Digital Marketing

Digital Signage allows marketers to convey more emotions and it gives more chances to attract and engage customers.

There a couple of relevant points that I would like to add to this article:

1. the possibility to -deeply- tailor contents;

2. one should look to *measurable* Digital Signage, i.e. one should never forget to include deal management when developing a Digital Signage plan.

Big Data is everywhere and everyone is interested in Big Data.
Businesses, Governments, Health, Science, they all look at Big Data as a way to dramatically improve.

A key point in extracting meaning out of Big Data is visualisation.
In this very interesting article data visualisation is presented in an innovative way.
Traditionally plots, charts and other visualisation tools tend to be as simple as possible to use and to see.
Data visualization should be revelatory instead of just reductionist — not simply a way to convey information or find answers, but to generate and cultivate questions.

Megacorporation General Electric has just announced a new big-data and analytics platform named “Predictivity”, whose main features are providing real-time insight and analytics.
 
GE also firmed up partnerships with Pivotal, Amazon, and Accenture. The EMC-backed Pivotal partnership might be the biggest of the three. Pivotal is the recent high-profile spin-off of EMC and VMware that got $105 million in funding from GE in late April.

Some marketers have already embraced the Digital Revolution.

Luxury brands understand the potential of digital engagement better than any other fashion retail segment and they are aware that mobile devices will overtake personal computers as the primary device for commercial transactions in under five years.

They bring emotions into a digital device, not advertisements.

This engage people and eventually turn them into (happy) customers.

What is Big Data made of?

Big Data is not just some abstract concept used to mystify IT specialists, it is the result of an avalanche of digital activity.

With every website browsed, status shared, or photo uploaded, we leave digital trails that continually grow the mass of Big Data.

This nice infographic gives some examples of how much data is created every minute.

10' video on how Apple is planning to use Big Data for their new streaming music service, and how they are already using Big Data for understanding how people use their products.

Big Data's main role is Personalisation, both for suggesting new music, and for doing targeted advertisment.

According to previous history, purchase history, songs in the iTunes library and general feedback, data analytics can suggest the best music for every person.

However, too much personalisation can be bad. It could take away the joy of discovery from the music experience...

Another example of how Data Anlytics can help to burst conclusions based on common sense.

It makes sense that buying more expensive products requires longer conversion lag. However the second plot in this example shows that this is not the case.

Large conversion lags (e.g. 10 days) are seen for both low and high price orders (e.g. $40 and $400), and actually the price-orders range looks the same for both the short and the long time lag peaks.

Some suggestions on how to see structured and unstructured data as parts of the same plan.

Today's enterprises collect both structured and unstructured data and those two source types have to converge into one analytic system.

SQLStream is a real-time streaming Big Data software company headquartered in San Francisco.

SQLstream provides a relational stream computing platform for analyzing large volumes of service, sensor and machine and log file data in real-time.

Unlike a traditional relational database management systems (RDBMS) SQL query, which returns a result and exits, streaming SQL queries do not exit, generating results continuously as soon as new data become available.

I believe that the focus should move from the amount of data to the insights one can gain from them.

Company should go after Big Data not because it is cool and trendy, but only because it can improve their business in so many different ways.

State your goals, and then you decide to keep only the data you need, be it huge, big, or 'slim'.

And when it comes to privacy (about which data to collect), my suggestion is: always put the interest of the customer first, and you will be largely rewarded.

That's a fact: nowadays there is a lot of talking about Big Data, even from people having no clue about what it really is.

Here is another fact: Big Data can make you leapfrog the competition.

You don't need to make a lot of buzz on Big Data, just get involved, even silently:

1. Create your Big Data group (including IT and marketing specialists);

2. Start brainstorming to define your plan;

3. Choose a single responsabile for the plan;

4. Execture the plan;

5. Measure its effectiveness, and iterate.

Here is my personal answer to this question.

If used well, Digital Signage can:

1. ATTRACT your customers (tailored content, dynamic content)

2. ENGAGE them (interactivity)

3. Improve the COMMUNICATION (integration with mobile devices)

4. Collect relevant DATA for real time-analysis (centralised and measurable Digital Signage)

IBM launches a new Big Data architecture acceleration: BLU Acceleration.

Bob Picciano, IBM's general manager, claims that BLU Acceleration is 10 times faster than other database systems, and that in some cases the runtime dropped from minutes to milliseconds.

I am sceptical about having queries running _thousands_ times faster than before, but I welcome innovative solutions from IBM.

Most of the power of Big Data lies in its predictive capability.

1. Big Data provides the information,

2. domain experts provide the structure for how to set up the data for modeling,

3. predictive analytics provides the muscle to open the doors to what is hidden in the data.

Because Big Data is not just a buzz word ;)

Here comes the definition of Big Data according to the Oxford English dictionary.

- I find it strange that there is no reference to "digital" or "analytics".

- I find also misleading that the challenges are related only to manipulation and management, and not to the analysis of the data.

- Finally, I would have included also a "positive" side in the definition. The size of Big Data allows to find hidden statistical relations.

The big-thinkers call that “messy data” because it’s difficult read, but that may be where racing should dig in, just as happened with baseball when some new metrics were introduced. “If you look at the things that actually count in the long run statistically, then you can predict much better"

When you are dealing with Big Data, it _always_ looks messy at the beginning.

You then need some Big Brains to turn the mess into a gold mine.

This video is for Big Data beginners, and those business people who hear about it all the time but they don't really understand what it is.

First of all Big Data is big and growing fast. Whenever something happens in the digital world, it gets bigger.

Then, Big Data is actually simple. It is based on just four pillars: (1) data sources, (2) data storage, (3) data access and (4) business intelligence.

Finally it can answer very relevant questions as "who's ready to buy?" and 

"does inventory match demand?"

Take a step back, look at the big picture and ask yourself what can Big Data do for you?

After acquiring Lucky Sort (to help analysing huge data), Twitter now has a strategic partnership with WPP, leader in marketing communications.

The social media company is doing important steps for exploiting its potential.

I hope they realise the importance of real time and will address that with adequate resources.

Know your customers and your competitors is always very important.

In this article they are seen in the context of pricing.

According to Forrester pricing models should be based on the 5 C’s, which are customers, competition, commercialization, costs, and communication. 

Big Data can help you get actionable insights for all of them.

I do like unconventional approaches, they help to keep your mind open.

Although the old traditional marketing and the new digital marketing might not have any difference in terms of ideas, they are very different in terms of what they might achieve. Just like cars of today still have an engine, 4 wheels and a steer, but they are also safer, faster and nicer.

For example, "know your customer" might have been a pillar of the old traditional marketing too, but the level of knowledge that one could achieve back then has no comparison with what one can get now.

In addition, customers are changing, not just because they use websites or app instead that phonebooks, they have different habits and the purchasing process is very different too. Therefore marketing has to follow a different path.

84% of chain executives see a significant impact og Big Data on their company's performances.

The top three expected benefits are:

1. Improve supply chain efficiency

2. Reduce supply chain costs

3. Possibility of real-time decisions

Retailers are leading the way in Big Data supply chain analytics.