Why as a Marketer I ask for Data?

How to approach your target audience?

Where would you find your TG?

When can you connect with your TG?

How much budget I allocate for a Digital campaign?

What is the idea cost per user acquisition?

Best bid for CTC/CTR/CPM?

….and many more questions haunt a marketers mind.

In a traditional & conventional marketing scenarios, all these questions where answered with a vague amount of guess, prediction, case studies, intuition, assumption, try & error mechanism.

Well, in todays time with so much investment in big data analytics, marketers are on the right track when they decide to use a targeted and intentional approach to analysing their data. Big Data has become a marketing buzzword. All that marketers need to do is ask the right set of questions to get measurable results.

As a marketer we have access to social media analytics data, sales date, internet searches, cookies, CRM, thus we should ask some interesting questions to Big Data:

Which is the untapped market segment?

Nike saw big data as a portal into an entirely new market. As strong as Nike’s position has been, the “just do it” inspiration of its brand and the quality of its products was likely not enough to strengthen and grow its highly valuable and profitable customer relationships in the future. The data and information streaming from performance tracking and health monitoring wearables was potentially more valuable, providing a closer, more sustainable and constant connection to customers (not to mention loads of high-value data). Big data – a great complement to Nike’s current product portfolio and market positioning was both the ends and means of Nike’s innovation into a new market

When are consumers leaving us?

When T-Mobile set out to decrease its churn rates, it looked to big data to tell the story of customers who jumped ship and went to another company. The company noticed that customers who left shared similar behaviours across billing cycles, web logs, and social media channels.

Having identified several markers as risk factors, the company was able to effectively intervene when some of these markers popped up, decreasing churn rate within a quarter.

How effective is our social media?

Whirlpool, the largest manufacturer of home appliances, wanted to discover what their customers and consumers were saying about their products and services on social media platforms.They used Big Data to monitor and analysis conversations across popular channels such as Facebook, Twitter, and Youtube, review and blogger sites, and mainstream news. Analytics findings were incorporated into Whirlpool’s decision models to accurately predict customer churn, loyalty, and satisfaction. This process enabled the company to listen, respond, and measure on a scale unobtainable by manual methods. The results revealed that Whirlpool improved its understanding of its overall business. There was increased satisfaction, faster responsiveness, and overall, more satisfied experiences with customers. 

Do our customers want us?

Finding the commonality in what your customers like can be eye-opening and can prevent you from making big investments in products or services that no one is interested in. Netflix proved this point when it optioned the wildly successful series "House of Cards."

Execs weren't originally sure whether to move on the series or not. Sure, it was good, but would Netflix audiences like it? Luckily, Netflix had more than enough data at its disposal to help make a pretty educated guess. Do viewers like Kevin Spacey? Yes. Do they watch gripping, cynical political dramas? Yes. Do viewers watch material like this all the way through? Yes! Then, does it follow that they will like this series? Yes! And so it is that "House of Cards" fans have big data to thank for hours of enjoyable TV watching.

How effective is you're marketing?

Nissan have a whole host of localised websites designed to help consumers determine which Nissan is ideal for them. They wanted to go further than just simply measuring conversions, but instead delve into the car types, models and colours that customers had been looking at online.

They did this through a ‘request form’ that a potential customer has to fill out following their completion of a brochure or test drive request. By aggregating these data points from individual customers, Nissan were able to paint a vivid picture as to the vehicles which were in demand throughout a particular region – this means that advertising campaigns and production can be tailored to suit the needs of a region instead of just a country as a whole.

What will WOW a customer & gain a competitive edge?

It’s hard to talk about analytics success stories and not mention Amazon. They were one of the early adopters and are the only company that have a patent that allows them to ship goods before an order has even been placed. Their ‘customers who bought this…’ feature was revolutionary at the time, but compared to the company’s current offerings, it pales into insignificance. Now, the data points are wide-ranging and far more indicative of what a customer is likely to be genuinely interested in.

Today’s recommendations are based on. their wish list, the items they have reviewed and what similar people have purchased – this creates a very rounded profile of a customer and is a great example of predictive analytics being used to its full potential.

So to get the most from your Big Data investment, focus on the questions you's love to answer for your business. But remember, while there may be good and mediocre questions, the worst mistake you can make is being too afraid to ask your data any questions at all. The process may be challenging, but it can create an incredibly targeted and effective strategy.

Data-driven decisions are better than intuition-based ones. Happy Questioning!