With enormous quantities of Big Data available for Business Intelligence, marketers need to be wary which of it to incorporate and which not to trust completely. The top management often asks the executives to prove using data which products are working and which aren’t. However, blindly using Big Data for the same may not be a good idea as there is just too much of it and making sense of it all is not possible. If one product is doing well and others aren’t, that does not mean that others ought to be discarded, as stopping promotion will create trouble in the future. Marketing automation is something that all firms must initiate. Hubspot is one tool which enables the same. Finally, the old fashion A/B Testing must also be executed at times to physically test which products are doing well or not.

Knowledge management has an innate connection with social collaboration, yet it’s connect with Big Data is less clear. The field of knowledge management typically struggles with low end data, and Big Data  involves a lot of data that extracted at process levels, unsuitable for sophisticated business analysis. Extracting business value for knowledge based organizations thus becomes a challenge. Thus the context needs to be understood in order to convert the knowledge to actionable insights which will eventually lead to organizational learning.

The Internet of Things has already proved to be a revolutionary aspect in business and it is transforming major processes. Added to this is the use of analytics which firms are utilizing for conducting business analysis. One of the major changes expected is in the design sphere which will never again be static. Data of seemingly disparate needs is now being correlated as collaborations are taking place across unusual sectors such as weather data having correlation with movie going crowd’s data. Artificial Intelligence is increasingly sieving out enormous chunks of data out of conversations. Software algorithms are no longer being protected to save them from damage, instead they are being maintained with periodic consistency. Also seemingly chaotic data can be given more meaning using cognitive or self explanatory systems. Finally everyday problems will now get solved using gigantic computational strength.

Keurig which manufactures coffee brewing machines recently had a disappointing spell in the market. It was not doing well and its corporate strategy was not aligned to market needs. In fact the biggest mistake that Keurig did was to ignore signals driving out of data analytics. Once Keurig started tracking data to conduct business analysis, it became clear that Keurig’s strategy was not in line with what people want. To rectify, they started focusing on words such as natural or organic for the coffee as this is what people are geared towards now. The design being sleek was highlighted and in keeping with the environmentally conscious theme of present day users, the reusability of cups was also focused upon. Thus data is not meant for the lab alone, but to actually be used for practical business purposes. Part of this was discussed during a recent summit in Boston. Business research conducted shows that about 90% of executives polled name Big Data analytics as being among their top three priorities. 

Amdocs is among the leading players globally among customer service software solutions. Amdocs’ General Manager for the Big Data and Strategic Innovations unit Gary Miles provided candid answers over a recent interview. Large number of telecom companies are leveraging their strong brand names and entering the financial services sector especially in the developing world. Amdocs runs a business innovation  foundry at AT & T for whom it is among the largest vendors. Cyber security, video bill presentation and network virtualization are among core target areas for Amdocs now. Agile technology startups are being partnered with for such ventures. They are especially keenly tracking innovation in Israel as they feel that is an important market.

According to Accenture Study Challenges to becoming a customer-focused digital enterprise include digital strategy ownership, organizational readiness, and establishing metrics to measure digital success Customer experience has become the heart of the digital transformation drive of companies. Key findings of Accenture Interactive ’s study titled “Digital Transformation in the Age of the Customer” suggests that “Improving the customer experience and satisfaction” is the one of the top business priorities of companies along with “growing revenues,” “improving differentiation,” “accelerating speed to market” and “increasing profitability.” Till now, most of the businesses have not focused on differentiating themselves from others based on the digital customer experience they provide. In fact, only 5% of the companies may be exceeding the expectations of their customers with respect to digital customer experience. The study suggests that there is still confusion in organizations with respect to who should establish the digital vision, whether they have the right people and how can their digital initiative be measured? The study has revealed some interesting and useful recommendations for those who are keen to focus on improving their digital customer experiences to achieve differentiation including the need for all departments to work together like a well oiled machine as digital transformation of a single department will certainly not give the desired results.

Predictive app marketing is the process where real time and historical data is analyzed to come up with predictions on business processes and requirements in the future. This form of business analysis can actually provide insights on the data source from where the most valuable consumers are likely to originate from. It also provides us with inputs on which leads are worth following up as they may be close to final conversion. Finally, this system also warns us about users who may soon depart the scene due to excessive churn.

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