Big data seems to be the new buzzword on the block, and small businesses are taking notice.
However, big data is more than just the flavor of the week. In short, big data represents massive amounts of information: try to imagine trillions of terabytes of data, for example. Companies can then analyze big data to discover trends and unlocking new ways of doing business.
The Power of Big Data
Big data can have huge implications for SMBs, especially given the evolution of technology and the emergence of data-driven decision-making. For example, consider some mind-blowing statistics about big data such as…
- More data has been generated in the past two years than in all previous years of existence.
- Google alone garners over 40,000 searches per second, meaning that new data is constantly being generated, which has search engine implications.
- Approximately 73% of companies have already invested in big data or are planning to
So, what does all of this mean for your business? Is investing in big data just another instance of hopping on the bandwagon?
Not at all. The sheer number of companies who are already looking at big data is incredibly telling. Meanwhile, businesses today understand the importance of analytics, such as Google Analytics and SEO metrics, to make decisions and understand our customers. Why wouldn’t we want to do that on a larger scale?
Consider the benefits of investing in big data, whether you’re already considering big data training or are curious about the hype.
Breakdown Your Users
Understanding user behavior is essential to making an informed business decision, whether it be changing a product’s price point or redesigning a website. Knowing the in’s and out’s of our customers is the holy grail of commerce; however, what’s big data’s role in unlocking what buyers want?
Simply put, big data breakdowns can segment your users to help you understand…
- Who is purchasing your products, segmented by demographics such as age, gender, and location
- What users want from your business based on your sales figures
- When users are buying from you, signaling that you may have a seasonal product or a time of year when your buyers are especially hungry for what you have to offer
- Why visitors were compelled to buy from you versus a competitor
- How you can improve your products, services, and marketing in the future
If you want your business to head in the right direction, you need to understand where you’ve been. Big data provides an incredibly detailed breakdown of your userbase so you can make more informed decisions.
…and Supercharge Your Sales Strategy
By segmenting your marketing and understanding your users’ wants, needs, and dislikes, you can ultimately craft a product pitch and marketing message that speaks to them. Big data can also be used as a means of competitive analysis to see how your data stacks up against the competition. Don’t pursue big data blindly: instead, use it as a means of building the product and business that your users can get behind.
Some questions can be answered simply by the art of asking; however, the information gleaned from big data is much more complex and beneficial than a simple survey. Big data may represent the tipping point for SMBs looking to rise above their competition and truly get inside their users’ minds.
Harnessing The Power Of Big Data For Your Business
In the same way that NBA coaches and players can leverage the power of data to lead them to victory, your company can—and should—collect, evaluate and act on customer data to enhance the way you market your goods and services. But with countless data points to track and analyze, it can be difficult to know where to start.
• What kind of data are you expected to record?
• How do you calculate and analyze the data?
• How does data analysis help to build a more robust bottom line?
Build an expert team for big data.
Marketers need to set up a team of Big Data Experts, Big Analytics Experts, and Customer, Brand, and Segment Experts to create a solution that will help their company get ahead of the competition. Ideally, this team consists of three groups of individuals:
• Data jockeys: a starting lineup that can plan and manipulate massive data sets for study.
• Data scientists: the top draft picks who understand modern computational techniques and construct basic and complex data models.
• Business consultants: all-stars who can link the company’s questions and priorities to the right analytical methods.
Build a playbook for the project.
Working together, the team can build a playbook—either for ad hoc analytical projects or for organizational monitoring and utilization applications.
• For major ad hoc analytical projects: once the business issue has been identified and formulated, the first step for an ad hoc project is to ensure that the data (its source, consistency, and periodicity) are fully understood before it is applied. It is normally necessary for a few individuals on the marketing team (e.g., marketing operations) to understand the data. The majority of the marketing team (mid-level managers and individual contributors) just need a top-level understanding of this. Marketing executives need a more thorough view of the use of data and where possible pitfalls might be in the entire company’s context.
• For operational monitoring and use applications: Marketing executives also need a clear understanding of the data in this field, trusting that experienced subject matter experts (marketing operations) understand the data in all areas. This is particularly relevant if organizational monitoring and use affects major company decisions. Summaries of data through easy-to-understand visualizations are important for the marketing team to easily understand the data applications and make the right decisions. Lower-level marketers need a thorough understanding of the particular field in which they work and a high-level understanding of other data and its possible effect on their area of operation.
If your project is ad hoc or operational, your data team should be able to:
Identify your final goal.
If the data and analytics are not specifically associated with a significant business issue that leads to greater profit, brand awareness, or market share, efforts, and investments would be in vain. Doing this best (choosing the right play for the circumstance) is key to success. The goals may include:
• Use media data at the zip code level to assess media coverage for the target community in the target zip code
• Using geospatial time data to help retailers increase their share of footprint for established shoppers in their category;
• Use comprehensive data on the customer profile to better target possible purchasers
Capture and track the correct data.
Identifying, collecting, and monitoring the correct data is the first step in creating a credible data model. Many CMOs say that the greatest challenge for their teams is to catch the right online data. Site visits, email clicks, and video views are not necessarily the best measures of marketing success. Many new online data points are becoming easily accessible. Capturing and effectively using them would make it possible for the business to participate in highly useful marketing tactics. Here are a few examples of this:
• Customer geospatial data will increase customers’ footprint at grocery, restaurant, and branch locations and away from the competition.
• Sentiment monitoring helps capture the brand’s views of the market based on a consumer social media survey. Your brand will use this approach to consider how your brand’s customer views are shaping up against the competition.
• Click monitoring and advanced assignment will help your brand recognize the sequence of clicks that took the user to your website and contributed to a conversion.
• Search analysis helps marketers understand and search words are most applicable to your product category, helping your content management team build SEO-friendly site copying, social media posts, and other indexable content.
Apply the right analytical methods.
If the data has been captured, the relevant analytical methods must be implemented. Data analysis specialists may help determine the statistical or machine learning approach that is most important to your business, turning your company’s big data into insights and operational value quickly and precisely. Some of the analytical techniques that can be used include:
• Marketing mix modeling is used to optimize the marketing mix of media outlets in order to achieve the maximum ROI.
• Customer life value is a perfect match for businesses who have a direct relationship with their customers. This approach will help your company assess which customers are likely to produce the most sales (at the least cost over time.
• Propensity analysis shall assess which consumers are most likely to buy the product during the next month.
• Attribution analysis is mainly used to leverage online media to assess which online marketing platform (e.g., search, social, paid digital) is most cost-effective in producing incremental revenue on a dollar-for-dollar basis.
Establish specific guidelines and recommendations.
Be sure that your analysts will produce outputs using easy-to-understand visualizations and straightforward guidance on when and how to target marketing expenditure and where to trim back.
With foolproof data analysis and enforceable directives, the business will soon see nothing but the cloud.
See i am not sure about the Simplive Hadoop course but i have done Hadoop course from KVCH Institute and they have a very good faculty and they have a tie-up with the IBM, so for the course as well as the placement is confirmed.
Hope it helps you!