Develop a Successful Big Data Strategy for Your Business

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The following excerpt is from Think Bigger: Developing a Successful Big Data Strategy for Your Business, the new book by big data strategist Mark van Rijmenam. The author is presenting a webcast on Tuesday, June 17, about how to combine customer, mobile, and social data to increase revenue. Data Informed is hosting the event. Click here for more information and to register.

Mark van Rijmenam and book1 300x224 Develop a Successful Big Data Strategy for Your Business

Mark van Rijmenam, author of “Think Bigger: Developing a Successful Big Data Strategy for Your Business”

Big Data has the potential to benefit organizations in any industry in any location across the globe. Big Data is much more than just a lot of data, and combining different data sets will provide organizations with real insights that can be used in decision-making and to improve the financial position of the company. Of course, for each industry and each individual type of organization, the possible uses will differ. There are however, a few generic Big Data uses that show the possibilities it has for your organization. In Chapter 7, I will discuss different industries in more detail, including some examples.

1.    Truly get to know your customers, all of them in real time.

In the past, we used focus groups and questionnaires to identify customers. This information was outdated the moment the results came in. With Big Data, this is no longer true. Big Data allows companies to completely map the DNA of their customers. Knowing your customer well is the key to selling to them effectively, but implement these strategies carefully so as not to cause privacy issues. A famous example of this is when Target found out about a teenager’s pregnancy before her father even knew. The daughter received advertising for pregnancy products, which outraged the father. Later, they learned that Target knew this private information by analyzing which products the 16-year-old teenager bought at the local Target store.²⁰

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If companies ensure that the privacy of customers is not threatened, Big Data can deliver personalized insights. Using interconnected social media data, mobile data, web and other Big Data analytics, it is possible to identify each customer, as well as what he or she wants and when, all in real time. Big Data enables a complete 360-degree view of all your customers, even if you have millions of them.

The benefits of such knowledge are that you can tailor recommendations or advertising to individual needs. Amazon has mastered this to perfection, as its recommendation engine determines what products a user has bought in the past, which items users have in their virtual shopping carts, which items they’ve rated and how, and what other customers with similar profiles have viewed and purchased.²¹ Amazon’s algorithm gives each customer a different webpage. And, this strategy pays off. The company reported a 27 percent sales growth to $13.18 billion during its third fiscal quarter in 2012, up from $9.6 billion during the same time in 2011.²²

2.    Co-create, improve, and innovate your products in real time.

In the past, consumer panels discussed what they thought, what they wanted, and why they wanted it. Companies also used panels to show consumers new products and find out what they thought of them. If they did not like a product, companies could potentially have to start all over again. With Big Data, such panels belong to the past.

Big Data analytics can help organizations gain a better understanding of what customers think of their products or services. What people say about a product on social media and blogs can give more information than a traditional questionnaire. If it is measured in real time, companies can act immediately. Not only can the reaction to products be measured, but also how that reaction differs among different demographic groups or people in different geographical locations or people expressing views at different times.

Big Data also allows companies to run thousands of real-time simulations to test a new or improved product virtually. By combining scalable computing power with simulation algorithms, thousands of different variations can run and be tested simultaneously. The simulation program can combine all the minor improvement tweaks into one product.

3.    Determine how much risk your organization faces.

Determining risk is an important aspect of today’s business. To define the potential risk of a customer or supplier, a detailed profile is created and placed in specific categories, each with its own risk levels. Currently, this process is often too broad and vague to be helpful. Often, a customer or supplier is placed in a wrong category and thereby receives an incorrect risk profile. A risk profile that is too high may not be that harmful, although income will be lost, but a risk profile that is too low could seriously damage an organization. With Big Data, it is possible to determine the proper risk category for each individual customer or supplier based on all of their data from the past and present in real time.

Especially in the insurance business, predictive analyses are used to determine how much money a customer will cost a company in the future. Insurers want to identify the right customer for the right product at the right price and lowest risk in order to ensure reducing claim costs and fraud. Using Big Data techniques, such as pattern recognition, regression analysis, text analysis, social data aggregation, and sentiment analysis (via natural language processing or monitoring social media), a 360-degree view of a potential customer is formed. This complete and up-to-date representation of a customer can lower risk significantly. Such an analysis can, of course, also be used to determine the potential risk of a new or existing supplier. For many financial institutions, this is a top priority in the coming years.²³

4.    Personalize your website and pricing in real time toward individual customers.

Companies have used split tests and A/B tests for some years now to define the best layout for their customers in real time. With Big Data, this process will change forever. Many different web metrics can be analyzed constantly and in real time, as well as combined for additional results. This will allow companies to have a fluid system, in which the look, feel, and layout changes reflect multiple influencing factors. It will be possible to give each visitor a website especially tailored to his or her wishes and needs at that exact moment. A returning customer might see a different webpage a week or month later if his or her personal needs changed.

Big Data can also affect prices. Yield management in ecommerce could potentially take on a whole new meaning. Orbitz experimented with this by showing Apple users more expensive hotels than PC users.²⁴ Orbitz had learned that Mac users spend $20 to $30 more a night on hotels on average than PC users.

Algorithms make it possible to react to events in the market or actions of competitors in real time and adjust prices accordingly. Companies that started using Big Data to personalize online offering toward individual needs are enjoying an increase in sales and profits.

5.    Improve your service support for your customers.

With Big Data it is possible to monitor machines from a (great) distance and check on how they are performing. Using telematics, each part of a machine can be monitored in real time. Data will be sent to the manufacturer and stored for real-time analysis. Each vibration, noise, or error is detected automatically and, when the algorithm detects a deviation from the normal operation, service support can be alerted. The machine can even automatically schedule maintenance for a time when the machine is not in use. When the engineer comes to fix the machine, he or she will know exactly what to do because all the information is available. A good example is the construction company Nick Savko & Sons, Inc., a Columbus, Ohio, site-development company, that already uses telematics to improve the efficiency of its operations.²⁵ It uses GPS devices to monitor data, such as idle time, cycle times, productivity, and more. These devices were installed on the equipment required to complete work on the SX Railroad’s $175 million transshipping terminal. All information could be monitored from a distance; it allowed the company to complete the project a month ahead of schedule.

6.    Find new markets and new business opportunities by combining your own data with public data.

Governments around the world are making their datasets public in an effort to stimulate innovation. In 2011, the European Union organized the Open Data Challenge,²⁶ which was Europe’s biggest open data competition to stimulate startups to devise innovative solutions using the massive amounts of open data generated by governments. For example, the Dutch government focuses actively on stimulating the reuse of open cultural datasets and organizes hackathons to come up with new solutions.²⁷ ²⁸ By combining various datasets, companies can give new meanings to existing data and find new markets, target groups, or business opportunities.

Companies can also discover unmet customer desires. By doing pattern and/or regression analysis on your data, you might find needs and wishes of customers of which you were previously unaware. Big Data can also show companies where to market a product first or where to place a product. Vestas Wind Systems, a Danish energy company, used Big Data and analytics to select the best locations for wind turbines.²⁹ With that information, the company was able to harvest the most energy at the lowest costs.

7.    Better understand your competitors and, more importantly, stay ahead of them.

What you can do for your own organization can also be done, more or less, for your competitors. Big Data will help organizations better understand their competition and where they stand relative to each other. It can provide a valuable head start. Using Big Data analytics, algorithms can determine if, for example, your competitor changes its pricing. You can then automatically adjust your prices as well. Organizations can also monitor the actions of the competition, such as following new products or promotions (and how the market responds to them). It can also track how the response changes over time. Remember that much that is done by you or your competitors is available as open data.

8.    Organize your company more effectively, and save money.

By analyzing all the data in your organization, you may find areas that can be improved and better organized. For example, the logistics industry in particular can become more efficient by using the new Big Data source available in the supply chain or during transportation. Electronic on-board recorders in trucks can tell how fast they are driving, where they are driving, and so on. Sensors and RFID tags in trailers and distribution help on-load and off-load trucks more efficiently. In addition, combining information about road, traffic, and weather with the locations of clients can save substantial time and money.

Of course, these generic uses are just a small indication of the massive possibilities of Big Data, but it shows that Big Data provides endless opportunities to add business value and help you stand out from your competition. Each organization has different needs and will require a specific Big Data approach.

A complete list of sources can be found in the book.

Excerpted from Think Bigger: Developing a Successful Big Data Strategy for Your Business by Mark  van Rijmenam. Copyright © 2014. Published by AMACOM Books, a division of American Management Association. Used with permission. All rights reserved. http://www.amacombooks.org.

Visitors to this site are granted permission to download or print out one (1) copy of the AMACOM content from the website for personal use only and agree not to reproduce, retransmit, distribute, disseminate, sell, publish, broadcast or circulate this material without prior written permission of the copyright owner (AMA).

Mark van Rijmenam is the founder of BigData-Startups.com and a big data strategist who advises organizations on how to develop their Big Data strategies. As such, he is a well sought after speaker on this topic. He is presenting “Correlating Sales Data with Customer Behavior Data to Improve Sales and Customer Interaction,” a webcast hosted by Data Informed, on Tuesday, June 17.


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