Marketing and sales objectives have grown since the arrival of Big data when the internet became live about 20 years ago. B2B marketers are pioneer in data-driven marketing. They perform analytics in their marketing strategy in order to increase productivity and profit. A report from forbes says that one with analytical marketing approach have increased their throughput by  rate of  5% to 6%  than their competitors who don’t use data.

 

Organizations whose marketing and sales are data-driven not only improved their marketing methods but have also achieved a higher return on investment (ROI). While good big data experts are hard to come by, companies are solving this problem by enrolling their employees in an online Hadoop training.

To make efficient use of data to reshape your marketing efforts, make sure you have the required tools in place as well as the right manpower. Their paucity will make data a collection of random numbers and thus render the whole exercise useless.

There are multiple tools available to mine pertinent data such as Google Analytics, Salesforce, Marketo etc. They also offer you the service to hire experts analysts to effectively analyse data collected from these applications for better marketing decision making.To explain how data analysis in marketing works, here are three ways to use data to improve your marketing strategy.

Leverage Social Media Marketing

As social media and data share a strong bond, it becomes important to use big data through social media. Most organizations develop an effective strategy to mine data as social media generates large amounts of consumer data. There are some real life application of social media in marketing driven by big data.

Improved Customer Service:

Successful organizations understand the potential of data that tells them who their leads are, where their customers are, what the trends are, what they expect and search for. From Twitter accounts to Facebook advertisements, everything tells you about consumer behavior.

Engage your Employees:

Job hunts become easier with data used in social media. You can find the right recruiters and consultants to help you land the job of your choice. LinkedIn is an important site to post jobs and attract consumers towards your product. Finding a skilled employee is the first step towards success. Additionally, the higher your employees’ engagement rate, the more productive will be the workforce. The field of human resource is confidently using Big Data and analytics to choose the right employees by making better hiring and management decisions.

New Predictions:

Social media data facilitates the prediction of trends. This means you can keep up with customers and stock your shelves with trending products. Rather than depending exclusively on past performance to improve your workforce, allow them to look at real data that describes the effectiveness of your marketing strategy.

Manage your data:

Big data helps you evaluate patterns and current market trends and this helps predict user demands in the future.  It becomes important for an IT organization to maintain their old data as well as the new data. Effective usage of data and storage of existing data may require some extra storage space, which is easy to manage through data refining.

Removing old data is important to reduce chances of any doubtful activity over your current data. Data destruction and data cleaning services are available worldwide and can be trusted for permanent data destruction.  A recent statistic reveals that there are some incidents where old data of organizations was hacked by rivals, which result in losses.

Anticipating Customer Service Needs:

The frequency and volume of quality performance data combined with always-on connectivity lead to improved customer service. Machine-to-machine automation results in the real-time gathering of performance data from various devices. This results in the faster deployment of OTA ( over the air) application updates to check error codes and cyber threats, or to provide better services depending on real usage.

Easy access to their service, account, and delivery information has become a priority for most customers. A quicker response of brands to anticipate and meet customer expectations generate better experience.

Communication systems that deliver personalized or automated messages for customer service or product updates lower inbound customer service calls and keep up overall satisfaction.

The expensive and often risky process of product research and development enhance when quality-of-performance data, consumer data, and predictive analytics are integrated throughout the marketing, product design, testing, and manufacturing phases. Companies can streamline marketing by enabling concurrent engineering and advanced modeling of product usage while enhancing product quality and increasing adoption chances.

As a concept, Big Data is easy to deal with — moreover, a bulk of data usually lends itself to simple data analysis techniques. However, messy data is not easy to handle: data from different sources that do not fit together properly. Though the big social media outlets help advertisers use messy data, it’s still vital for marketing teams to discover ways to integrate all of their campaigns in a way that allows the use of new marketing channels with the focus on ROI.