Big Data & Digital Marketing

Predictive analytics, or the ability to make accurate predictions, is based on good data and good algorithms. Every sensible data scientist knows this. It's good to see that this knowledge is spreading. Data alone, no matter how big, cannot give the right answers.

I believe that useful predictive analytics gives *accurate* predictions, not *exact* predictions. Predictive analytics which gives exact predictions is used in Science, not in Business.

Here are 6 possible trends in Big Data in 2015. I mainly the following 3:

1. Big Data will go mainstream -

so much that we might start dropping the term "Big" and just talk about "Data"

2. Everything with go on the cloud -

this will simplify the usage, cloud is simple, cheap and, above all, flexible

3. Analyses will become faster -

thanks to improvements in big data tools and technologies

Predictive analytics are gaining in popularity, but what do you—a manager, not an analyst—really need to know in order to interpret results and make better decisions? 

The quantitative analysis isn’t magic—but it is normally done with a lot of past data, a little statistical wizardry, and some important assumptions. Let’s talk about each of these.

1. The Data: for good predictions you need good data;

2. The Statistics: regression analysis is what is usually used;

3. The Assumptions: every model has some assumptions, beware that assumptions can be invalid sometimes ...

Great piece with lots of information and links about Big Data's new frontiers on images.

Takeaways:

1. According to an IBM survey, 70% of CMOs feel unprepared to deal with Big Data

2. IDC predicts data tidal ways keeps increasing, with social media being leaders

3. Machine learning and AI are more and more commonly applied to marketing, not just for text but also for images

4. Targeted advertisement is expected to benefit the most out of data mining

Top retailers are using Big Data to gain a competitive advantage:
predicting trends and preparing for future demand.

Synchronize prices hourly with demand, inventory and the competition.

Pinpoint customers who will likely buy your product and contact them as they wish to be reached, when they are in the right location, and engaging them with personalized real-time offers.

Retailers using big data technology are able to provide a smarter shopping experience to influence purchase decisions and edge out the competition.

Collecting lots of data isn't just about making more accurate Netflix recommendations.

Rather than just judge us on what we say in an eight minute consultation with our GPs, maybe they'll be able to pull up our health data and analyse it properly?

Scientists would be able to more easily identify the effects and side-effects of different treatments, and more quickly develop and bring new treatments to patients.

Of course - there is one awkwardly massive downside to this. Privacy concerns.

Using Big Data to make prediction is quite normal.

However this is not about guessing your _next_ purchase, or next next.

This is about where you will be _years_ from now. If you will be planning for a trip to Europe, or going for a running workout, or just buying some cheese at the grocery downtown.

Probably the reason why this is possibles lies in the following comment:

"No matter how spontaneous we think we are, humans are actually quite predictable in our movements"

Do you agree?