The power of data: What does it mean for your business?

“Data” evolved from a being a mere synonym for ‘facts and statistics’ to becoming the most overused buzzword of our time. We tossed the word “Big” in front of it and everyone is scrambling to get their hands on it. Why? It has the answer to most of our marketing woes: Why will buy this? When do they want it? The journey data takes from being a statistic to becoming a campaign requires understanding a few basic facts.

Deepika Nikhilender lead the first presentation for this month’s IAB Training on The Power of Data. The CtrlShift CEO gave the audience and overview of how we collect data, categorise it, and what we can do with it.

There are lots of different types of data. It’s confusing and overwhelming as to how to handle the material. How do we capture it? How do we identify it? How do we store it? What do we do with it? These are the challenges we are now facing, so let’s first break down the four ‘Vs’ of data:

Volume – scale of data. The amount of data received and normally comes in petabyte, exabyte or zettabyte.

Velocity – frequency of incoming data.

Variety – the type of data received – structured, semi-structured or unstructured.

Value – is the usefulness of data received.

Understanding the data journey

  1. Get it: The journey starts with data assessment and figuring out how to acquire it. Only then do we determine where and how to properly store, manage and harmonise the collected material into a sensible and consistent manner.
  2. Use it: Marketers visualise data and learn patterns. Then they ask, ‘How can I relate to it? How do I analyse the data and take action from it?’

Capturing data

Store transactions, social media, messaging platforms are all rich sources of data that can be used to study behaviours. It’s essential to determine every opportunity there is to capture data  and structure a business plan.

Types of data

Historical: Data coming from the past is hugely valuable for predicting behaviours from the future.

Real-time: Created right after collection. Moves fast.

Slow moving: Studies and research done over a long period of time.

Quantitative: Specific facts and numbers

Qualitative: Anecdotal, observation-led, not measureable by numbers

Offline: Information obtained from physical transactions or listings such as customer service calls, point-of-sale transactions, home addresses, phone numbers. While this data is great for traditional marketing segmentation and
targeting, it doesn’t address the digital needs and behaviors of your customers and prospects online.

Online: Consumer ID and browsing data are some ways to collect data online. This can include Twitter handles, Facebook logins, cookies, device IDs, IP addresses.

Open: Data that is open for anyone to use freely, reuse and redistribute, such as maps, weather, medical data, bioscience, census data, and population. It’s often facilitated by governments and world forums, and is made available in designated data centers and the open web or API ecosystem.

Evolution of data

Over time, data has moved from being static to dynamic, structured to unstructured. At some point, we started receiving data in real-time and it has gone from rearview reporting to constant prediction of the future with the help of machine learning. Data was once something we used to claim the behaviour of others, but now it’s telling us the actual behaviour of consumers.

How data is being used today

Case #1  

Tracking supply and demand: Rain + Taxi Shortage

Oliver Senn, a senior research engineer in Singapore, spent five months working on a joint initiative to figure out the reason behind why it’s impossible to get a cab during a storm. By using combining quantitative and qualitative data. Sean sifted through the data and saw a vast fleet of more than 16,000 taxicabs, but a strange pattern emerged: taxis weren’t moving during rainstorms.

In fact, the GPS records showed that when it rained (a frequent occurrence in this tropical island state), many drivers pulled over and didn’t pick up passengers at all. Senn confirmed his findings by sitting down with drivers. It turns out the lack of supply is actually caused by a driver’s fear of getting into a car accident.

Drivers get involved in accidents on rainy days, hence the cutdown of taxi supply by 75 per cent. The company owning most of the island’s taxis would withhold S$1,000 (about US$800) from a driver’s salary immediately after an accident until it was determined who was at fault.

So when it started raining, they simply pulled over and waited out the storm.

Case # 2

Tracking conversations: Location + Allergies

Well-known antihistamine brand, Benadryl launched Social Pollen Count in the UK after collecting data through social media behaviour that proves many people suffer from hay fever during summer. Essentially, the campaign used the location data from Twitter conversations about pollen to track how pollen is behaving in a certain area s
The call-to-action of course, was that the app also shows the nearest stores where you can purchase Benadryl.

Case # 3:

Consumer behaviour: Pregnancy + Products

By studying consumer shopping habits, Target was able to determine which of their shoppers were pregnant.

Their analysts noticed a pattern that pregnant women buy large amounts of lotion during the second trimester, and in their 20th week, they start loading up on vitamins. With 25 other products, Target’s AI predicted if a shopper is pregnant. With this data, the retail giant was able to tailor their ads and include coupons (mixed with other non-baby related coupons) that will entice soon-to-be-moms to visit their stores. Since then, Target’s Mom and Baby section showed higher profits.

The lesson? Habits matter

Data has caused a paradigm shift in the marketing world. Insights have become integral to the success of any business. If you’re not investing in data, keep these key points in mind.


  • Is an effective enabler for business success
  • Has created a new industry
  • Highly coveted
  • Traditional companies are using it to survive in the modern world
  • Companies are scrambling to organise it

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