What You REALLY Need To Know About Big Data And Your Marketing Strategy

Big data is watching you.

Well, not really, but doesn’t it seem like big data is everywhere these days, touted as the next big thing in marketing?

But let’s face it, a lot of business people who hear the words ‘big data’ probably don’t know exactly what the term means, so they pretend to be in on the trend without understanding what a powerful tool it can be as part of their overall marketing strategy.

So what is big data?

In a nutshell, big data is just a new way of referring to data collection from a number of different sources that provides your business with information such as customer behavior, social network tendencies of your prospects, information derived from products and services customers bought, and information derived from customer experience.

In general, there are two types of data that would benefit companies: structured and unstructured.

Structured data is data that is easy to fit into a spreadsheet and easy to calculate. For example, number of products bought in the summer months is structured data.

Unstructured data is data that does not fit easily into a spreadsheet or database, but is often even more important to business growth.

For example, social media branding is a type of unstructured data that is not always specifically measurable, but is extremely valuable to the success of your company.

With that said, let’s take a deeper dive into how you can use big data in your business, referencing some examples from big brands.

Use Predictive Analytics To Meet Your Customer’s Needs

Predictive analytics is a type of big data in which current data and data from the past such as customer insight and customer purchases is used to predict future events, trends and potential problems.

While predictive analytics does not guarantee that specific events will occur in the future, it provides you with a reasonable expectation of what the future holds relative to your business, and how you can make adjustments now in preparation for what is likely to occur.

Walmart has used predictive analytics to help improve customer experience at checkout, by identifying what hours its stores are more likely to be crowded and deploying more cashiers at those times to ease congestion.

Predictive analytics also helps Walmart supervisors decide whether it is more efficient to install self-service checkout lanes, or increase the number of checkouts manned by cashiers.

So the question you must ask is this: How can predictive analysis make one of your work processes more efficient?

For example, if you discover that certain products sell more during a specific month or season, you can then adjust your marketing to ensure that you have enough of those products on hand to meet demand.

You can also design your social media campaigns ahead of time to take advantage of the increased sales during that time period.

Use Big Data To Target the Right Customers

Big data also gives you a wealth of information about your customers, which can in turn help you better optimize your website as well as your products and services to meet specific customer wants and needs.

When you analyze the buying behavior of your customers, you not only gain insight into what they like, you can also gain understanding into what they MIGHT like based on their prior behavior.
Netflix is the perfect example of this type of targeting.

The streaming giant is committing billions into creating original programming over the next few years, and has quickly become a go-to company for some of Hollywood’s biggest power players.

But Netflix’s rapid ascent did not occur overnight.

Unlike entertainment companies such as HBO, Showtime or FX, Netflix relies almost exclusively on big data, analyzing a complex series of algorithms to drive major decisions.

For example, Netflix analyzes the viewing habits of subscribers to determine what type of content to create that would appeal to its targeted customers.

But the secret many people don’t understand is that Netflix isn’t concerned about appealing to every single subscriber.


Because those who run the company understand that different content appeals to a different targeted customer based largely on cultural differences.

And because the content on Netflix is streamed to a global audience, the company has more than one type of targeted customer.

That’s why Netflix gave comedy star Adam Sandler an exclusive four-picture deal worth $100 million several years ago, despite the fact that every other film studio in Hollywood had soured on his appeal.

The deal was predicated on data that found that while subscribers in the U.S. and the U.K. did not watch Sandler’s films, subscribers in Latin America were going crazy for the comedian’s work.

As a result, Netflix knew that producing four Sandler films would significantly expand its reach in Latin America, generating millions of new subscribers who would be attracted by the idea of watching Sandler’s films. And that revenue would more than offset what the company was paying Sandler.

Because the deal was exclusive, the Latin American audience could only watch Sandler’s new films on Netflix, meaning that Netflix was cornering a targeted market that was primed for the comedian’s material.

Similarly, big data can help your business identify the customers who are most likely to want your products and services.

This can help refine your marketing strategy, because the data will tell you what those customers want based on their buying behavior as well as their responses through surveys and questionnaires.

You can also gain insight into what other types of products and services would appeal to your customers, which can help with your product development.

Finding Ways To Reduce Waste

Are there areas in your business process that are inefficient, which is causing your company to lose money as well as customers?

Most business owners will answer ‘yes’ to this question, and using big data to identify why you are losing customers can help you stop the bleeding.

Xerox learned this lesson a few years ago, when it set out to learn why so many of its call-center employees were quitting, which was costing the company millions and lowering the quality of its customer interactions.


After crunching analytics, Xerox learned something amazing: prior experience was not the important quality in hiring a call-center representative.

In fact, analytics found that personality was the biggest determinant of whether a call-center representative would stay on the job long enough for the company to recoup the cost of training new hires.

The data showed that employees with creative personalities were much more likely to remain at a Xerox call-center than employees who were had more inquisitive personalities.

That’s likely because creative personalities are more easily able to adapt to different customer temperaments, and would thus be more equipped to handle the pressure of satisfying customers.

Inquisitive personalities on the other hand, are more likely to question what a customer is asking for, especially if that ‘ask’ is outrageous.

As a result, call-center representatives with questioning personalities would likely generate more conflict with customers that could increase stress levels and lead to more attrition.

Using this information, Xerox was able to change its hiring practices and hire a pool of call-center workers who had a greater chance of staying on the job.

And not surprisingly, Xerox cut attrition at its call-centers by 20 percent, which was significant given the fact that it costs the company $5,000 to train each call-center employee.

So where is your business losing money?

Chances are, big data analytics can identify those areas and provide you with strategies to plug the leaks and reverse your money-losing trend.

And that’s true even if you can’t identify the problem areas at first glance, because one of the cool things about big data is how it makes correlations between what may at first seem like disparate facts or trends.

Big Data Will Continue To Grow

What makes big data likely to remain an important tool for marketing is that trends, statistics and customer behavior are always changing. That means that what was true about your business and its impact on customers may change from one year to another. As a result, big data will continue to identify those changes in a way that can help you adapt, reiterate and re-brand.

By remembering that big data is not simply about figures and numbers, you can open your business up to the possibilities of information in a way that is fluid, adaptive and best of all, responsive to the challenges of the digital landscape.

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