Executive Education

Get more out of BIG DATA: 6 effective ways to know what your customers want

The moment you decided to move out of your garage, and find a real office space is the time that you realize your business is growing. Pulling right customer to your business is must; after all, you need funds to keep your startup alive, getting strong, and growing. So, what draws the right customers? Before that you have to identify “Who is your ideal customer?” The customer who is going to buy from you.

To find your ideal customers, it is important for you to engage in sound data mining and filter out buyers from potential consumers.

Track their details: demographics, transactions, emails, social media, photos, and videos. Figure out what their likes and dislikes are. Use analytics to make sense out of the data; get the technologies that could tell you how they are reacting to your marketing campaigns. According to Forbes Insights survey “brands and agencies are relying on a range of technologies to further their customer engagement efforts.”

So, we have reached at the doorstep of Big Data.

Let’s knock the door and allow me to walk you in. Here, you will find a vast and complex, structured and unstructured datasets, if sorted accurately and used well, soon you will need a bigger office space.

Harnessing the Power of Big Data

This emerging phenomenon, Big Data, is growing like a beast. We create data every second. Google alone processes over 40,000 search queries every second on an average. There are many others in the row.

Now, considering you as an organization, how this statistic is useful to you? By only knowing all those “Ws” (who, what, when, and where) of people’s search queries, you can get the idea of their preferences, demographics, and other details that might help you to create your “ideal customer” personas.

Big Data removes guesswork and strengthen the decision-making process.

The most challenging part of the job is to capture the relevant data from all the sources; imagine the volume of the data, keeping in mind the per second search queries on Google. It requires technology and resources to process the data from numerous (relevant) sources, so that it can be later turned into information. Remember that data is available in both structured and unstructured forms. It is the job of an enterprise to get significant information from it.

Types of Big Data

Every company has its own data warehouse. The warehouse contains a database of your customers and provides you information like: email IDs, transaction details, location, channels through which they reached you, when they prefer to contact you, and more. Big Data is broadly divided into: Structured Data and Unstructured Data.

Structured data is a well-crafted data that businesses purposefully create to generate information. Unstructured Data is scattered on various channels, technological platforms; this data organization needs to capture and generate information to understand their customers better.

Here are the types of Big Data:

Machine Generated Data: Machines have been developed to capture, measure, and store the events to process it further for extracting information out of it. Data from sensors, mobile phone locations, satellite images, and computer systems are the structured form of machine generated data that is processed using a computer. Before you wander elsewhere, go to your website, and analyze every click. Check out the details of the visitors and identify the customers and prospects.

Premeditated Business Data: This type of IT managed and processed data every business monitors and records for reference or administrative purpose. Data generated from transactional activities from your customers can provide you better information about their shopping habits and route they followed for online checkout. Survey data, credit cards, banking and stock records are the data that could help you in predicting the next move of the industry and your customers.

User-generated Data: Track your customer’s social media activities. Create a user base and keep checking the amount of shares, hits, likes and figure out what goes well with the customers. Try to develop a relationship with your customers to figure out their likes and dislikes. Follow the influencers of the industry, track the reaction of their audiences, analyze and create a value from it. Internet search is common way to get user-generated data.

These types of data can be accessed easily, if you use advanced technologies associated it and indulge in rigorous data-mining.

Assuming that you have these datasets with you; structured data like transaction details, semi-structured data in the form of Javascript Object Notation (JSON), XML, and unstructured data in the form of text, images, and videos, the next step would be how you are going to use it.

Are You Asking the Right Questions?

Before you take a plunge into the ocean of data, you must know what you are going to take out from it. Knowing everything is so tempting. But don’t just waste your time knowing everything and delivering nothing. To make your data mining successful, you must ask right question.

Data in itself is not information; you have to generate information out of it.

What you interpret from data depends upon the question you ask, and what data you have processed to gain the predictive insight. Information technology can generate Big Data for you; Big Data analytics can process the data and provide information, but what information you require and what you will make out of it are the decisive factors for your business growth.

What You Need To Know About Your Customers

People, Technology, and Data; find a relevant connection to your business and deliver an outstanding customer experience. Perceive your data bank as an insight generation tool. Understand your customer behavior, recognize their preferences, and make sound decisions.

Who are they?

Focus your machine learning tools and data analytics to generate information like age, gender, and income level of your customers.

What they do?

They are in school or on a job. How do they spend their time? What are their activities, passions, hobbies and interests?  What they do online: shop, search, learn, or read?

Where are they?

Find their location: global, national, and local. This will help you determine your target market.

What appeals to them?

Information about this will help you drive your marketing campaign efficiently. What they like: Free information, coupons, discounts, prizes, free shipping, or others.

How they are connected?

Try to track the technologies they use, like smartphones, laptop, desktop and tablets. Understand their social media habits. Collecting their email IDs.

Now, after all the gears set let’s find out using Big Data what your customers want?

6 effective ways to know what your customers want using Big Data

In the past few years, customers have become more tech-savvy and social. Technologies have provided them various channels to gain insight, and to express and share their views. Enterprises have now better chance to identify their customers and make decisions based on their preferences. This can be done through efficient data mining. But to do that, you should know where and what to look at. Below are the 6 effective ways that would help you to determine your customer’s preferences:

  1. Track your Network Traffic: Your website, social media, and emails contain valuable information about your customers. Knowing who visit your site and what is the conversion rate will help you understand the efficiency of your marketing channels. It is important to understand your customer’s requirement to deliver an outstanding customer experience. This information is available on various channels. Information, like at which page of your website they stopped browsing or what appealed to them while navigating your site will help you understand them.
  2. Filter customers from consumers: Big data can help you analyze the strength of your market. Not just customers, you also need to know what consumers want. Once you will identify their choices, you can easily turn your consumers into customers. Prepare customer-centric strategies based on the information you churn out from the Big Data.
  3. Average Purchase Size: This should be among your top priorities to determine the purchasing habits of your customers. How much they spend on your product, like are they buying in bulk or in small quantities. When they buy? Get their transactional data and seek out the information of their purchasing habits.
  4. Platform used by customers: Identify what technological platforms your customers are using to reach you. Suppose, most of your consumers are Mac users and your website or product is not iOS compliant. Avoid these blind spots. Use big data to know what technologies your customers are using and make your presence felt by optimizing your product for those platforms.
  5. Infrastructure is critical: Make your infrastructure smart enough to capture all the details about your customers. Check that your business process and infrastructure is capable of taking significant action required to generate optimal user experience.
  6. Integrate your marketing campaigns: Use Big Data to see what channels your customers are using and then identify your customer’s likes and dislikes. Integrate your marketing campaigns, right from your brick and mortar shop to online platforms.

Once you know your customers, drive your decision-making process to reach them quickly, in an effective way.

The Big Data industry is growing at a fast pace; there is a need to capture all forms of data to understand the customer’s preferences. Technologies and services are emerging to help businesses process the massive amount of data and generate information out of it. But it is important for the companies as well to maintain high-end infrastructure and IT facilities for data and information management that can help interpret data into useful customer-specific information.


By Hammad Akbar.

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Hammad Akbar
Hammad Akbar is a tech entrepreneur who loves writing about Marketing, Entrepreneurship and SaaS. He has bootstrapped several tech startups to multimillion dollar businesses.