Big Data & Digital Marketing

Great article, really.

 

Big Data is really Big, and it does not scale! You need clouding, but that's not enough; you need time, but you will never have enough time to dig into all of the data.

 

You need Big Brains, to make plans and hypotheses to filter and analyse the data in a smart way, in the smart way _your company_ needs.

After Walmart, also Carrefour aims at exploiting Big Data for improving their business.

 

The approach here is different, and more traditional in a sense.

Keywords are: retail site selection, competition analysis, optimization of direct marketing activities, enhancement of store performance (through a better understanding of sales territories and customer needs).

An interesting innovative part concerns the usage of Galigeo's Geodashboard which, by representing and displaying data on interactive maps, identifies hidden trends that are not discernible in tables, charts, or other traditional solutions.

Mobile devices will outnumber human population in 2013

 

There will be 24 billion connected devices by 2020

 

The World needs smart people to take advantage of this network.

This is a great chance to make our World an awesome and better one.

Yet another device able to collect Big Data.

 

The watch will understand where you are, what you have eaten, how many calories you have burnt, how well you have slept etc.

 

These "intelligent" wrist watches will permit monitoring of an individual's heart rate, calorie intake, activity levels, quality of sleep and more

 

Will Apple revolutionise also the watch world using the power of Big Data?

Don't let your salesmen in the dark, they will fail.

Extract insights from your data and use them to shed light on your salesmen's path.

 

Selling more effectively means targeting the right accounts most likely to purchase at the right time with the right messaging. Ultimately, marketing needs to enable this without further blocking the sales cycle.

Just like Facebook, Twitter is strongly heading for Big Data. Twitter acquires Lucky Sort hoping to "make huge document sets easier to analyse, summarise and visualise by building elegant and user friendly tools for text analysis." More or less the Holy Grail of Big Data Analytics.

A great example of a company that didn't care about Big Data at the beginning, but later developed a good plan and strategy to improve company's value.

 

Not only can MailChimp now handle spam, but it does also give its customers valuable information on how to increase their revenues.

 

Their first Big Data project was to break down their silos and connect together all of the databases that they had. As I always emphasize, integration is one of the key to success in this field.

The top points highlighted in the study are four optimization challenges in the Digital Media industry:

1. Audience Optimization, 2. Channel Optimization, 3. Advertising Yield Optimization, 4. Content optimization / Ad targeting.

One year later these four points are still very relevant, although important results have been achieved.

Companies have and are increasing their budgets on Analytics and Digital; Integration is helping to create consistent metrics to help making marketing decisions; real time analytics is being addressed more seriously; ... we are moving up in the maturity curve.

Probably the biggest difference is that now we know that social is not just "sexy" ;)

Technology should be focused to innovate the way the world works. Private companies as well as Governments and Hospitals should leverage on the newest technologies and methodologies to improve normal people's everyday life.

 

Smarter Planet by IBM is going exactly in this direction.

What people do online provides an increasingly accurate picture of their customer profile, including lifestyle choices, buying preferences and brand perception. 

Social media provide companies with an almost endless supply of data to help them better understand and respond to the needs of consumers.

Here is a series of suggestions that will help to:

1. define a baseline and determine your focus,

2. build a plan,

3. execute the plan and

4. measure its effectiveness

"We want to make mobile tools that become indispensable for our customers while shopping in our stores and online"

These guys are going to rule the world of retail.

The store of the future does speak the language of modern customers. It is digital, it offers interaction, it uses big data to tailor the content.

Customers want to shop "on their terms".

Two fundamental points are missing in this list of key questions for choosing the best Digital Signage for your needs.

 

One is: Interactvity -

Marketers need to be interactive in some way, they need to engage the customers

 

The other one is: Data -

If you have a network of digital devices, do not waste this chance to create collect data (and store them in a database). For example: install webcams with the screens, so you can see how many people are looking at your ads all the time.

 

Digital Signage is not just showing content on a digital screen, it is the door to a measured marketing. Couple it with Big Data and don't let your IT specialist alone, integrate them with your marketing experts.

How can Big Data affect sports? More than what one might think. here are two examples.

 

1.

Professional sports has started to implement Big Data analysis into player evaluation processes. 

 

The MLB, for example, is using a new technology, called FIELDf/x, that tracks and digitally records the position of all players and hit balls in real-time, thus allowing teams to sift through data and better analyze the defensive efficiency of specific players.

 

2.

Can you imagine a system that automatically follows your favourite sport events? That gives you real time reports, that posts on the social media that you actually care about, that personalises the text only on the event that you follow, that sifts through more than 100 years of stats?

 

Stop imaging, Automated Insights is doing just that, and more: the content sounds like a human wrote it.

Facebook is one of the largest database in the world: more than 1 billion users sharing their life experiences, including what they are spending on now, and what they would like to spend on in the future.

Facebook is now trying to make an intelligent use of its data. No surprises then that 3 out 6 key highlights of the first quarter are about Big Data!

I hope, for Mark Zuckerberg and all shareholders, that they have built a good plan for their data analytics. I hope that they have considered not only integration and real time analysis, but also an intuitive and yet powerful user interface, to let marketers easily gain some/correct insights from the huge dataset.

 

Above all, my warmest advice would be "to keep it clear".

Don't miss the following 5 rules

 

1. Start with the applications

While big data is a hot term, it doesn't mean much unless you can use it to build your company's bottom line.

2. Think physical

Despite all the talk about the "Internet of Things," and the Google self-driving car, the physical world remains largely disconnected from the digital world.

3. Go simple, but big

Creating simple queries over huge data sets can provide insights much more quickly and with more accuracy than trying to create sophisticated algorithms narrowed toward smaller samples.

7. Discerning the signal versus noise

the executives thinking that a big data dive is all they need to reform their business are mistaken.

8. Dealing with a new model of application development

Instead of a lengthy and expensive development process, use several companies to develop a simple app and pick the one you like the best. Once you have found the best app, go on to iterating on the next app.

What I find interesting in this article is the idea that performing simple queries over extremly large data set can actually produce better result than using complex analyses over not-so-large data.

 "Creating simple queries over huge data sets can provide insights much more quickly and with more accuracy than trying to create sophisticated algorithms narrowed toward smaller samples."

On the basis of this idea business intelligence is shifting from making better use of the data inside one's own company to using those vast pools of data outside the firm (big data if you will) to capitalize on customer sentiment, buying patterns and economic indicators.

Many businesses are struggling with the personalisation of the web in terms of their video content: it is not scalable to create a video for each and every person that we want to target.

 

Here is an interesting example on how to use digital technologies and some analytics to make a successful decision.

 

The next step is to use the knowledge acquired in this process to study a larger database of data, looking for more and better customer targets (maybe also some you couldn't think of).