“The future will be owned by Data Ninjas”

A good friend and colleague made this prophesy years ago when I created the Digital Shopper Marketing Center of Excellence at Coca-Cola.

He went on to describe his vision for the future of marketing – and commerce in general.

His point was simple.

The future will be won by who can best understand and take advantage of ever-increasing information.

6+ years since that time, data – and specifically the term Big Data  has entered our lexicon in a big way.

There are multiple definitions for Big Data.

And, multiple platforms for extracting value from Big Data.

Let’s start with a few of the top definitions:

SAS: “A term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis.”

Wikipedia: “Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. Challenges include capture, storage, analysis, data curation, search, sharing, transfer, visualization, querying, updating and information privacy.”

IBM: Big data is being generated by everything around us at all times. Every digital process and social media exchange produces it. Systems, sensors and mobile devices transmit it. Big data is arriving from multiple sources at an alarming velocity, volume and variety. To extract meaningful value from big data, you need optimal processing power, analytics capabilities and skills.”

All of the definitions are correct in their own way.

However, there are a few elements of the IBM definition we should explore.

Big Data

A Deluge of Data

“Big Data is is arriving from multiple sources at an alarming velocity, volume and variety.” 

In our mobile and social society, data is being created at an unfathomable rate.

And, it won’t stop any time soon.

It’s like trying to take a single sip of water from a fully-turned on fire hose.

Or maybe a sip from the Mighty Mississippi River.

Our future is a connected one. Thanks to the Internet of Things.

This means that this deluge of data will only increase.

separatING the wheat from the chaff

“To extract meaningful value from big data, you need optimal processing power, analytics and skills.”

This is a critical part in Big Data.

The Data itself is not the thing.

The value comes from actionable insights gleaned from sifting through the data.

The capabilities, systems and skills needed to extract the value are what my colleague meant when he said “The future will be owned by Data Ninjas”.

I am just not sure he thought of the Ninjas as the mathematicians and programmers or the Artificial Intelligence and Machine Learning applications.

Shopper Marketing data leads to insights & action

Data – of any size – is important to better understand what people buy versus what they say.

Unearthing actionable insights allows marketers to differentiate based on the data .

Over the next decade, Shopping will become more personalized and less mass media.

The shift from “Communication” to “Engagement” and “Measurement” is happening today.

And, it’s being led by data of all kinds.

Promise vs Reality of Big Data for Shopper Marketing

The promise of Big Data is still hard to deliver.

Yet it offers a strong future.

We’re just now starting to turn the corner on implementation of these tools (especially for traditional brick-and-mortar retailers).

Many retailers are addressing this topic in a way that has added significant value.

And, there are many great vendors and partners leading the way, too.

Keys to Success when applying Big Data to Shopper Marketing:

  1. Don’t wait for everything to be fully wired together to start
  2. Early learning is critical – adopt a ‘Test, Learn & Reapply’ mantra
  3. Strong ‘go-to’ partnerships are needed
  4. Addressing ROI is a key imperative
  5. Privacy issues must be understood and addressed

The implications from the data and insights may challenge long held corporate beliefs.

It can – and has – certainly led brands astray.

So it is important to let the business strategy drive inititaives in Big Data for Shopper Marketing.