Success Stories: How Successful Can A Business Be, By Using Big Data Analytics?
Biz & Co

Success Stories: How Successful Can A Business Be, By Using Big Data Analytics?

There are many success stories about the implementation of Big Data analytics, around the business world. By now, almost every business owner and marketing strategist are aware of this revolutionized concept of capturing Big Data in its raw format (called data sets) and receive well-formatted meaningful visualizations (graphs, charts) which can summarize the various data points from customers (and the market as a whole). This summarization can then be used to change and formulate policies or business plans which are more customer-oriented.

The Big Data technologies are making their way in every business domain – private or public sector, small or large-scale businesses, sole proprietary or partnership organization, service or product industry. Some of the businesses, however, are still not sure if they are in the right place to implement this competitive technology due to non-support of the following, in integrating Big Data into their workflows:

  • Their fields of operations,
  • Current infrastructure,
  • Market position
  • Or operational budgets

Their concerns are not wrong. But there are solutions and answers to each of their doubts. They can research for the usability and cost of in-house implementation of Big Data analytical technologies or alternatively, they can opt for third-party Big Data solutions by Onaudience.com and like companies.

The following success stories are compelling enough to motivate any business.

Transport for London

Transport for London (TfL) is a local government body responsible for the transport system in Greater London, England. It operates millions of buses, cabs, subway trains, ferries, Oyster London Transport cards, roads and traffic lights systems. Nearly 10 million Londoners can commute using these transport services and more than 31 million journeys are made in the capital each day.

At the backend, there is a huge amount and variety of data that is collected on a daily basisto understand concerns like what kind of passengers commute locally, who has long routes, what roads and bridges carry the maximum load and which transport medium faces heavier traffic. Such analysis of data is required to allocate more buses to reduce load on busy routes, to minimise the time spent in commuting, to improve the traffic flow, to adjust the traffic lights on heavier traffic regions to avoid traffic jams and many more similar activities. The Big Data analytics helped TFL in many instances, like900,000 passengers were rapidly informed about the closing of Putney Bridge for emergency repairs and were also guided for alternate routes and adjusted traffic lights. This swift action (any many others) helped them in serving the citizens with greater efficiency and convenience.

Carnival Cruises

Carnival Cruises operates more than 100 ships under 9 brandsand is one of the leaders of the cruise business. They are active users of Big Data technologies and use the integrated data-collecting system for more real-time and dynamic adjustments in the pricing on items across their inventory. This is to ensure the better-tailored offerings to the needs of their passengers. Even an addition of one more dollar in their item’s price can increase the corporation’s bottom line by $80,000,000, annually. With the analysis from Big Data tools, the structured and unstructured data can be used in making decisions that would help in achieving their objective.

Telstra

Telstra is an Australian telecom operator.They have deployed a Big Data analytical system to improve their customer service. Using predictive analysis and sentiment analysis techniques, they are using the vast data stores to determine the normal performance parameters of the network. The smart alerts and customer requirements which are produced by the Big Data analytics toolshelp them in improving the call handled at their support center, optimizing delivery truck schedules, providing more efficient infrastructure operations, etc. This has helped Telstra to achieve the current rankings on Forbes list

Xerox

Xerox is an American global corporation. It sells print and digital document solutions, and document technology products in more than 160 countries. For many years, the company struggled to understand what is causing their experience professionals to quit, regardless of the HR efforts of additional perks and bonuses. It is their Big Data solution which revealed that it is not the experience of staff that is required but it is their personality to work as a team and mutual collaboration that are necessary more than their experience. This led them to reorganize their hiring paradigm and lowered their support personnel attrition rates by 20%, which directly saved millions of dollars in the long-term.

Avis Budget

Avis Budget, the world’s leading car sharing network uses Big Data technologies in collaboration with their IT services provider. To become highly reputable in terms of customer services, they invested in the development of an integrated solution, which analyses the lifetime value of their customers, based on their rental records and service issues. This data is captured from within the Avis Budget database and from public sources, like demographics, customer feedback, corporate affiliation and social media activity.

The final visual values led the company to list their loyal customers and provide them with an exotic customer service experience with additional discounts, on-demand attention, troubleshooting and personal promotions. In return, this approach helped Avis Budget to:

  • optimize their resource spending,
  • better forecast the demand for their vehicle fleet allocation
  • and optimize the pricing.

Avis Budget is doing, what every business domain must do.

Competition is fierce and only those can have their profit chunk who are sensitive to the trends and demands of their beloved customers. No one else but Big Data solutions can help in achieving these for your business.