Originally Published On TechRevolve . Predictive analytics helps businesses be wary of customer’s future issues and fix them at the earliest. Life of a within the tech industry exists more around and . With all these being taken care of in a day or a week (based on the size of the company), the storytelling kicks off from here. storyteller data mining data analysis Having heard several about and all those insights we were exposed to, it essentially boils down to a , which is… TED talks human behavior single yet solid theory Why storytelling matters? How can data do it well? Watch taking us through the functioning style of today’s consumer minds. Joseph Pine Few such speeches from and the had changed our perception overall. Ideas and belief we had upon data. data experts day-to-day storytellers Now, to us, “Data are not just the numbers but pages from each of our online biography.” Also, it’s not only the work of a to understand humans/customers. It is the job of a too. The more a marketer indulges oneself into dissecting data sets, the more h/she learns human psychology. data scientist marketer That’s quite deep. Essentially, with enough amount of data we deal with on a daily basis, the next set of becomes more natural. Understanding the purpose of specific human behaviors shall help us identify each of our quests. predicting user behavior “Having someone along, to deal with one’s quest is what every human wish they had.” The quest is always unknown. Hence, here we’re trying to understand what users might need for a better future and a better life. With , we can help each other fulfil our purposes. Visualizing the trail our users leave online, we can come up with a potential solution. unique data sets For keyword/jargon maniacs, Do predictive analysis (just use data) Circle out the problems customers might face in the future Design the wireframe of your solution/product Run it with the existing customers (do it with no fuss created) Establish 95% statistical significance (can’t bid on the rest 5%) Go global 2 Steps To Doing Sensible Predictive Marketing Analysis In 2 points, performing predictive analysis means, Decoding user behavior Optimizing features/products/campaigns Decoding User Behaviour Understanding user behaviour will help build a better product We no more live in a world where just the seems enough. Right from identifying user’s demography to examining one’s clicks and focus region, everything has grown old. primary user behavior analytics Now it’s time we derive insights from data and with the help of (ML), deliver solutions before the problems may arise. machine learning Which has now grown into techniques like, deep personalization Advanced segmentation Hyper-personalization Giving omnichannel experiences Cross-device betting Predictive segmentation Will be more relatable if shown an example. Let’s take a look at and its personalization knacks. Adobe Usually, a new user on the Adobe website will see a homepage like this, Adobe’s webpage before playing with the inside features And after watching enough of videos, scrolling through multiple interest based features, blogs, and tutorials, something highly personalized like this shows up. This is how work. user behavior analytics By predicting the user’s interest like how one browses across the website, the features one opts for, videos they spend more time on, products can specific . And plot down each of their niche interest addressing their online activity. visualize user map It’s called just in case if you think it’s creepy AF! web analytics intelligence Optimizing Features/Products/Campaigns Make changes with the derived insights/data Based on the insights acquired from , change the poorly performing content. And if the data describes more about product’s dysfunctionality or feature wise blunder, go for internal agile testing and arrive at some real fix. real-time tools Further with the advanced tools like , , predictive analytics and similar, extract precise user behavioral data and tweak the existing model. RapidMiner GraphLab IBM It applies to enterprise level services to B2C products. Many times, conducting for BETA products shall work wonders. For this to happen, pick out the most reliable customers from your user base and ask them to try out your product. external user analysis Sending out smaller tweaks to the may work too. free trial users Investment Tip: Report from recent Gartner’s survey says, by 2018, 50% consumer product investments will be relocated to customer experience innovations. Hey, Users are not going to settle down for or anymore. To fall off such saturated radar, we must build something straightforward, coupled with problem-solving pills. copied innovations boring products Always build tools that may solve user’s complex issues, instead of making product itself as one heck of a thing to deal with. GOOD LUCK. Originally Published On TechRevolve .

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Predictive Analytics — To Paint The Holistic Customer Picture

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