There is simply no denying the immense reach of Big Data analytics across multiple industry verticals. With the acceleration of information generated and analyzed reaching an all-time high, it is imperative to know how to best use this information to help ensure a more profitable future. This is where predictive analysis shows its true forte as the tool for ramping up your business minus the uncertainties of the future.
How data looks like today?
In the older days, data was in limited form and its analysis needed at the max a “superior” software such as MS Excel. This was enough to sift through information such as leads, market information, competitive analysis and trendspotting. However today the scenario is different. Not only the volume but also the source of origin has expanded exponentially today. Blend in the rise of smartphones, decreasing costs of internet bandwidth, and social media penetration, and what we have is a far more complex system of content and information. The cherry on the top is that no longer traditional databases or spreadsheets are sufficient to gather information and extract insights from these sources of data.
So, what other tool or specialization is available to us to ensure that data scientists and decision makers can get near real time and highly targeted information of mission critical parameters such as upcoming trends.
Well, how about predictive analysis?
Predictive Analysis is a big data analysis strategy that seeks to answer key queries
- Past – What happened and why it happened?
- Future – What will happen in the future?
Why is Predictive Analysis an appealing proposition?
Working in an environment of uncertainty is the biggest drawback of confidently marching ahead of competition. If there is no guideline support from tools such as predictive analysis it will be difficult to gauge market trends and customer perceptions in the near future. And if you don’t know what sells, how will you produce it?
The good news is that the technology ecosystem as a whole, is moving in the right direction to make predictive analysis more powerful and more efficient than ever before. Right from data explosion, better computing power, to better buy-in from management, there is no better time than now to utilize predictive analysis to power up your business. Along with these enablers, is the rise of big data technologies such as Hadoop, massively parallel processing databases, in-memory databases, MapReduce, and search based features. With these technologies data scientists and business analysts alike can get insights from structured and unstructured data, and present it to decision making leadership in form of interactive data visualization.
Why is Predictive Analysis needed in business?
Here are 4 key areas where your business can gain tremendous competitive edge with help of predictive analysis.
- Interactive conversation and better business processes – Companies can use predictive analysis to elevate their business practices. An example is the retail sector. Companies in this space can use predictive analysis to enhance fraud detection at PoS counters in supermarkets.
- Tangible insights – This is the key USP of predictive analysis. With help of dashboards and helpful reports, provides accurate diagnostics for a particular action and assess the type of trigger needed to bring about improvement in chosen KPIs. Predictive analysis’ power comes across from the fact that these cause-findings and patterns would have remained hidden if not for predictive analysis.
- Inspire and innovate – Are you scratching your head to come up with better ways of interacting with customers and drive conversions? How about turning to the power of predictive analysis? For instance, mining social media data of your target market may reveal a yet unanswered need. This opens up a whole new avenue of opportunity to upsell, cross-sell, or add a totally new line of product offering to serve this unmet need.
- Aid in decision making – Today’s CMO is expected to be no less than a magician in building customer engagement and enabling high value conversions. In such a challenging scenario, predictive analysis comes across as the magic wand to help the CMO see the future to a more accurate degree and tailor marketing campaigns that spell success. Remember the famous Target experiment? The retail chain devised a pregnancy prediction algorithm that figured out which of their customers were newly pregnant. They then used this information to send out targeted discount coupons on pregnancy/baby merchandize.
Interested to take your business to the next level with high powered yet easy to understand big data predictive analysis technologies? Then it will be worth every dollar to connect with us at CIGNEX and know about Panoramyx – our very own proprietary Big Data and Analytics Platform. It comes with a powerful yet flexible architecture, scalable data integration, data management, and intuitive data visualization. This open source platform is ideal for businesses, irrespective of scale, size, or complexity of the big data analytics needs of your organization.