SUMMARY
The Analytics in SMAC model
Velocity in Big Data – The real deal
Building consumer loyalty and reducing churn
About five years back, one of the concepts which became the talk of the town was SMAC – Social, Mobility, Analytics and Cloud. While businesses have done significant leg work when it comes to the first two and while the jury is still out on Cloud, it is analytics which has now captured the imagination in myriad different ways.
For business in the 21st century, staying away from harnessing the true potential of analytics is almost akin to the kiss of death. From understanding consumer behaviour to analysing derivatives data for identification of stock trends, analytics is fast becoming the cornerstone to which critical business decisions are tethered.
Effective analytics, in turn, is hinged on the solid four V’s of Big Data – Volume, Variety, Velocity & Veracity.
Talking About The Four V’s
While it is true that the amount of information being captured and/or collected is growing exponentially, the advancement in cloud storage has eased off the pressure of volume to a large extent as the business no longer have to keep worrying about their storage infrastructures.
Variety is one of the most interesting developments in technology as more and more information is digitised, but, it’s still in its infancy to be a major source of worry. Similarly, veracity or trueness of the data is still provided scope for managers to intervene and take the right call. So, for several businesses, it essentially boils down to dealing with the velocity of data or in more laymen terms, the frequency of incoming data that needs to be processed.
What makes velocity an extremely crucial component is the fact that several extremely crucial decisions from fraud detection, IoT-enabled devices, to sending OTP over SMS has to be carried out at real-time and even a lag of few milliseconds could result in catastrophic damages.
The analytics engines have to be robust enough to handle data as they stream in and spit out the decisions with no delay. This dimension of big data is so significant because the faster data can be acquired and processed, the more is its utility and longevity. So, the system businesses use to analyse such data must be up to the task or business run the risk of being left behind.
Can Analytics Be The Key To Success?
We can pick up any industry and the general trend of consumerisation of services and democratisation of information can no longer be missed. From Uber to Netflix to Fitbit, unicorns are leveraging the power of data analytics to understand their consumers better and provided them extremely curated, personalised and persuasive contents.
Even from consumers, all over the world look to be more connected with their brands and that their brands should talk back to them with precision and timeliness. A business which has failed to adapt to this shift have already started falling behind.
Once powerhouses such as Nokia, Compaq and Kodak are classic examples of business failed to get the drift because they were so disconnected from the consumers. Their data systems were inefficient in guiding them towards the right market sentiments.
Same time, ventures like Amazon and Samsung have thrived due to their well-oiled data analytics engines, which lets them always be in touch with their consumers and in all the right ways leading to higher retention and loyalty.
In Conclusion
Business can no longer shy away from or delay investing in building a robust data analytics engine. To stay relevant in the minds of today’s consumers and build a competitive moat, they need to invest in analytics engine which helps them understand consumer behaviour and purchase patterns to the minute levels and helps them make real-time business decisions, driven entirely by what data suggests and devoid of all human bias and subjectivity.
By going down the analytics path and harnessing the power of big data, businesses would not only be benefitting in the short term but, maximising their objectives in the long run and in the most effective manner.
