Big Data…It is all about Hyper Personalisation

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With Big Data emerging as a major field, the era of hyper-personalisation has been ushered in across sectors.

Addressing an exclusive gathering of eminent people on the topic – Big Data Is Not Big Data – recently in a talk organised by the Australian Consensus Technology Association (ACTA) at the Sydney Town Hall, Founder of BigInsights Raj Dalal said the buzzword these days was Big Data. Be it business or IT or Retail. Its growing importance could also be guaged from the fact that on any given day, there were a dozen articles on Big Data in almost all the leading global publications – Financial Times, Forbes, Fortune or BRW.

Raj told those gathered, “You can draw parallels with Internet, e-Commerce and e-Business that made a fuss about 15 years ago. As in those days, there are the usual skeptics today who say Big Data is nothing but a waste of time, and so on. In the same way that Internet has transformed industries, Big Data techniques will transform industries and companies in the next 15 years or so.”

The Principal at BigInsights then delved upon some of the points associated with this emerging field like:

  • Is Big Data misspelt, misconstrued or misunderstood?
  • How BIG is data to be Big Data?

In Raj’s opinion, no one wanted Big Data but the Big Insights that come from the data, which us actually needed to operationalise it to really have an impact on any organisation. That was also the reason why he had decided to name his Big Data firm as BigInsights.

Raj then went on to spell out some of the uses of Big Data. One of them, he pointed out, was for political purposes. “Imagine you could accurately predict or influence the outcome of nation election? This is what happened during the Obama 2012 campaign,”said Raj.

At a recent conference in Sydney, Riyad Ghani, Data Scientist for the Obama campaign had talked about how one could use Bigdata techniques without having lots of Data. For the campaign, the insights into a potential voter’s profile was not the end goal but operationalising the insights and taking action by their army of volunteers to court the persuadable voters was the key success factor, he had said. Approx 65% of eligible voters in US do vote in an election there compared to about 95% in Australia. The challenge, thus, was to figure out the 125 million likely to vote, and then focus on the people who are “persuadable”. This is where data science comes, Raj explained.

In the same manner, said Raj, imagine when a business or enterprise knows when their customer or prospective one was browsing their physical or online store so that it was then able to recommend and make offers to the latter which they would find helpful. That was the magic of Big Data.

The question that thus comes up is – What would you like to predict in your organization and how can you monitize it?

According to Raj, a Big Data expert himself, there was the need to create a predictive model of those customers who were “persuadable” and give it a score of 1-100. Then make that information available to all volunteers of a political party or employees of a company so that they can call, email, etc. With Social media, it had become easy to connect with say an Obama volunteer and then get him to like his party or poke them..thus treading the fine line between harassment and gentle persuasion. This, said Raj, was called hyper-personalisation.

“How did we get here?”

Raj told the audience that the genesis of Big Data lay in the Internet…every click, every search, every tweet, every post, all contribute towards generating data. With Smartphones the amount of data generation grew further. The challenge was to find meaning in all this data and actionable insights, Raj added.

“Imagine if you are a boutique store owner servicing 100 customers in a small town 50 years ago. I imagine you would know a lot of that customer, like..dislikes..who their friends are would be able to recommend things and give them very personalized service.

Supersize it to a large Australian retailer…100s of store 1000 of staff and millions of customers that go to one of many store and also buy online. How do you achieve the same level of personalization? With great difficulty. In the Australian context we had activity going on with Woolworths buying into Quantium (Data Analytics company) for reported $20M for a 50% stake in the company.

Target Case Study

If you are a Lexus, Lululemon, Country Road you can build brand loyalty easier that if you are a of mega retailer like Target in the US – how can they build loyalty and not just convenience.

Target marketers wanted to know if they can “predict” when a customer may be pregnant based on her spending at Target. They figured that if they know that in the 2nd trimester and you can “win” them have their loyalty/spend for few years..

They were able to identify about 25 products that, when analyzed together (ie unscented lotions and soaps, supplements, soaps, cotton balls) allowed him to assign each shopper a “pregnancy prediction” score. More important, they could also estimate her due date to within a small window ( approx 2 weeks). Now Target could send coupons timed to very specific stages of her pregnancy. A holy grail for marketers..Story sounds to good to be true..

There are negatives offcourse as per a customer complaint to Target Store manager shows…

“My daughter got this in the mail!” he said. “She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?”

Later when Target Store manager called to apologise “I had a talk with my daughter,” he said. “It turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.”

Battle of the Commerce Titans: Walmart v/s Amazon


$60Billion in sales – All online..not bad starting off by selling books and now sells everything. While growing their e-commerce engine..they have also redefined the cloud computing paradigm.


$ 470Billion of sales/4000 stores/$9 Billion in ecommerce.

Walmart has innovation labs in Silicon Valley called @WalmartLabs. Redefine the retail landscape..Walmart was slow to get to online selling..But in the last 3 years spent >500M buying companies that will give it the edge in ecommerce, social and now mobile using bigdata as the backbone. One of the companies they have purchased is in fact a Australian company called Grabble 18months ago originally founded in garage in Wollongong!

Latest acquistion ,Inkiru have developed an active learning system that combines real-time predictive intelligence, big data analytics and a customizable decision engine to inform and streamline business decisions.

Inkiru‘s predictive analytics platform will enable them to further accelerate the big data capabilities that have propelled @WalmartLabs forward at scale Their solutions including site personalization, search, fraud prevention and marketing. Walmart’s data scientists will now be able to work with big data directly and create impact faster than ever before.”

“If you think about the last 20 years of retail, how people shop in a store has not changed,” The question Walmart’s asking is, how do you bring to a store the capabilities that have made e-commerce successful? With 200 million customers a week, if you can increase the average basket size by a dollar–that’s billions of dollars every year.” In fact, it’s more than $10 billion–more than its projected annual e-commerce revenue this year.

Their mobile strategy is as simple as it is audacious. They want to make mobile tools that become indispensable for our customers while shopping in our stores and online.

They want to make if easier for customer

1) Plan before they come to the store

2) Make it easier to find goods when in the store

3) Make real time offers when they are in store for upsell/cross sell

It is like having a personal shopper with them throughout their shopping experience. Now that’s Hyper Personalisation..

“Our goal is to create shopping tools that become second nature to the customer, providing assistance with every part of the retail experience from pre-store planning to in-store shopping and decision making to checking out.” Big data is key to power these tools.

With mobile-influenced offline sales expected to reach $700 billion by 2016—according to Deloitte—it’s is doing everything it can to get its mobile strategy in order, including harnessing the power of big data to drive tools and services.

One big-data feature Wal-Mart is working on to include in its app is an improved shopping list function.

“By leveraging big data, we are also developing predictive capabilities to automatically generate a shopping list for our customers based on what they and others purchase each week,” he said.

Another way the company is working to harness big data is by applying it to when the customer is actually in the store.

Wal-Mart’s app already has a geofencing feature that senses when a user is in a Wal-Mart store in the U.S. and prompts the user to switch to “Store Mode,” which is a setting that allows users to scan QE codes for prices and discounts. Working to take this even further and use big data to provide shoppers with useful information on demand.

For example, if an app user was in the toy aisle searching for a toy under $30, the user could use a voice feature to tell the app its request, prompting the app to generate a list of the best-selling toys in that particular store that meet the requested budget requirements.

With more than 50 percent of its customer base equipped with smartphones, Wal-Mart has already seen significant growth in the number of its customers using the Wal-Mart app on their device while shopping in the store

The Project budget questions

It may take a decade or more for Walmart to be a successful digital retailer. “Somebody at one of the board meetings asked the Niel Ashe, SVP @Walmart, ‘How long is this going to take, and how much is it going to cost?'” Ashe recalls. “‘It’s going to take the rest of our careers, and it’s going to cost whatever it costs. Because this isn’t a project, this is the company”

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