Businesses these days gather massive amounts of data. Usually, from the day these companies are incepted, they begin gathering and compiling data, which can be of various types ranging from, transactions, sales, customers service data, and more! The data collected can increase in volume exponentially, making it quite difficult to manage and store, which is why prominent organizations develop and implement a big data strategy and provide data science training to their employees to cater to these organizational needs.
The advent of social media and most modern technologies such as smartphones and sensors, and how companies use the data they gather has changed considerably. In fact, the data gathered has increased in variety, volume, and viability. With so much data being gathered, one does wonder what all this data is used for. Companies and organizations use this data to track customer behavior, generate insight, and create strategic milestones.
Using data to create and identify new opportunities is exciting, which is why companies invest in big data strategies to help leverage valuable data into actionable insights. If you're envisioning your company doing the same, you may want to seriously consider implementing a big data strategy across your organization.
4 Steps to Create a Lasting Big Data Strategy:
As the impact and success of big data increases, so do the improved new ways of deriving further use from the data collected. While the benefits of Big Data are tested and proven, business leaders are quite concerned about how to successfully transition to big data and are still figuring out the best way to incorporate it.
Here we'll discuss a 4-step approach to implementing and maintaining a successful big data strategy, which along with data science training for your employee would have you up and running in no time.
Identify What You Want
The primary goal of any big data strategy, broadly speaking, is the maximum impact on your achievement of organizational goals and overall improved strategy. However, you need to decide which key areas of your business you'd like to improve first. You may wish to increase the effectiveness of your customer representatives, increase revenues, improve operational efficiency, or perhaps provide a better experience for your customers. The goal you set should be precise, direct and certain. Once the goal is set, you can then choose the methodology to achieve it, hire relevant staff, and collect precisely the data you need to drive these changes.
Leverage a Proven Big Data Strategy
There are multiple proven ways to develop a data strategy. Based on the availability of data and your goal you can choose one of the following to obtain successful results:
Performance Management: Performance management is all about utilizing transactional data such as inventory levels, turnover, segmentation, targeting, and purchase history to make critical money-saving changes to your store operations and management. The data for this endeavor is usually available and provides usage insights for short-term decision-making as well as planning for long term. It works best with organizations that have large databases of historical data that can be easily leveraged.
Data Exploration: This particular approach requires heavy research and data mining to correlate data and find solutions that aren't obvious with a proper stream of data. This strategy is used primarily by firms focusing robustly on inbound marketing, by generating valuable insights from customer behavior on their websites. Allowing identification of new customer preferences, further segmentation of the market using insights from the data gathered.
Social Analytics: This approach is by far the most common, using social analytics companies to measure data from various social mediums like such as Twitter, Facebook, and SnapChat to gain further insight into customer behavior and preferences. The use of this data is based on analysis of customer reviews and conversations from these platforms. This provides three primary analytics, namely engagement, awareness, and word of mouth. It provides customer opinion and brand identity on new services, predicting a spike in demand for different products.
Identify Infrastructural Changes:
To use Big Data the right way, especially historical data compiled by your company, you may need to create a few changes to the infrastructure of your company. For instance, if the data is stored in outdated formats, it won't be able to facilitate running complex analysis and algorithms. Moreover, if you wish to bring other operational departments into the fold, you would need to implement data gathering capabilities there as well, upload it to the main server and streamline it. If your departments aren't interlinked properly you will need to prepare them for a few infrastructural changes so you can drive big data strategy within your company.
Obsess Over Customer Satisfaction:
The primary use of Big Data is generating insights so that companies can better serve their customers. This is known as customer-oriented marketing and is a new approach to increasing your market reach as well as revenue. At the end of the day, what companies need is to find out what goes inside the heads of their customers, their mindsets. This approach lets you better communicate with the customers and solve any issues that might arise, essentially allowing to you adjust your current marketing strategy. When gathering and analyzing customer data it is easy to get carried away, which is why firms have an ethical duty to create a fine line between gathering data and abuse of customer privacy. If your customers ever feel as if their privacy has been violated, that is something a company rarely recovers from. It would be in your best interest that you tread lightly when gathering consumer data.
These are 4 steps you can use get started on the right food with implementing big data strategy in your organization. However, you should note that this big data mindset should not only be with the management as your employees also need to understand what they are doing. You can ensure that by providing data science courses to your employees so they are on the same page, and can better help you in achieving big data goals. Additionally, certifications and online courses such as Analyzing Big Data with Microsoft Power Bi and Microsoft R can help teams get more accomplished at big data analysis.