Big data can change startups and will make a huge difference in terms of efficiency and otherwise. So, here are some great tips for new companies looking to utilise it.
- Focus on quality instead of quantity alone
Your focus should be on insights, and not only on the immensity of data. Instead of just focusing on the velocity and volume of data that may be gathered, go past that to demonstrate the insights that may be gathered. Answer the questions of ‘now what’ and ‘so what.’ Although Big Data can be used to be more responsive to the needs of customers, make sure you don’t provide them with too many choices – choose the best choices possible, since too many choices is almost as bad as not having any. Abundance of data shouldn’t result in scarcity of insights for customers and managers.
- Identify what the sweet spot is
When it comes to the generation and application of Big Data, the top three sectors appear to be telecommunications, banking and retail. In terms of experiential analysis, all of them are able to leverage Big Data well. However, there are also other sectors that can learn as well from the successes of Big Data in those sectors in activities like optimization, real-time planning, sense and respond, risk management, precision targeting, personalized engagement, visualization, rapid simulations and unified analysis. It’s best do this soon as big data is becoming increasingly central according to this post from Capita ITR
- Work on your pain points
So when can you tell that a company is ready and can benefit from Big Data solutions? Whenever it takes an entire day or longer to get data inputs as well as analysis on critical business activity. The delay may impact how effective business decisions can be and have an adverse affect on revenues and returns. Industries where there are adjacent industries harnessing Big Data already, or where the game is being changed by disruptors or industries faced with data deluge, are all ripe for leveraging the new techniques. As the intensity and velocity of competition has continued to increased, it is resulting in companies adopting Big Data faster and sooner. Precision analytics with Big Data helps with ‘nowcasting,’ rather than just simply forecasting.
- Find the cast of characters and story
Big Data enable to you to dig deeply into customer profiles and activities in order to build detailed personas. This makes it possible for you to trace customer journeys and build a detailed story out of behavioral choices and data points. Markets are now able to build customer profiles that have 10 to 15 trait categories for each type, or even more. That allows for new insights in real time into needs and wants, tastes, preferences and affinity. Anonymization of data helps to deal with customer privacy concerns.
- Hit your numbers
Real numbers should be shown not only in terms of Big Data volumes, but also the impacts and analytics that are derived from the data. For instance, demonstrate how insights from Big Data can help to increase sales volume for e-commerce sites, make improved cross-selling recommendations and improve conversions. Show how insights can be obtain not only from what customers do on a website, but also what they don’t do – in real time. A better business case can be made for Big Data from ROI figures in the long term and near term.
- Learn from various case studies
There are a number of different case studies that are available that show how to be successful with Big Data. For instance, industrial applications within the oil sector include having the ability to predict from sensor data when drill bits might fail. Big Data is used by social media sites and e-commerce companies to drive sales and traffic. Banks utilize Big Data for cross-selling financial products and for risk management. Big Data is used by bottling companies to better ship and route products in various seasons. Cattle farmers are even using sensors for tracking the walking speeds of their cows to help them detect possible illnesses in their animals.
- Move from reactive into prescriptive mode
Companies can move from reactive and descriptive modes into prescriptive and predictive modes with the help from Big Data. A good place to start is understanding chances, it is even better to be able to predict what might happen next, and the best is knowing what the best actions are to take to help shape the future. That involves Big Data being a focus of the company’s CMO and not only the CIO.
- Create your Big Data culture
Creating a Big Data culture involved bringing together business leaders, UX+UI communities, visual interaction designers, customer engagement specialists, data scientists, operations research practitioners, marketers, statisticians and computer scientists – a complex mixture of occupational cultures that need to be able to work in real time together. There is management bandwidth shortage as well as talent shortage for juggling Big Data. In needs to be dealt with both through long-term investments into organizational design and on the fly as well.