As we enter the new year, it’s always an exciting time to reflect upon the previous year and ask “What new things will happen next year?” Over the past year, it’s been really cool to see how executives at companies are realizing the value of using big data instead of just collecting it. Because of this trend, 2016 should bring about disruptive changes in the big data and internet of things markets.
Some of the top trends in 2016 that I see happening are
Customer satisfaction levels will be influenced by an automatic personalized experience
As consumers become more tech savvy and more millennials have discretionary income, more consumers will continue to adopt and use mobile apps such as Target’s Cartwheel or PriceGrabber while they’re shopping. These consumers are looking for a personalized experience that will give them some benefit, whether it’s a lower price or targeted advertising or coupons based on past behaviors, when shopping. Consumers have many options to choose from when shopping both online and in-person and will ultimately pick the store that gives them the most value and the best shopping experience.
Additionally, with the increase of internet shopping and the multitude of stores available to consumers, companies will start relying more on what an individual is clicking on and posting on-line about products and her shopping experience. In the past, companies have had challenges making sense of this information in a timely manner and then reacting. However, companies are starting to discover solutions that can help them not only react in real-time to a customer’s shopping experience but also personalize the customer’s shopping experience based on past behaviors or trends. These proactive actions should lead to higher level of customer satisfaction for the customer.
Using ROI in big data
Executives are pushing for the adoption of big data solutions however, many executives want to see a measureable ROI and meaningful use cases before they make a large investment in a solution. In 2016, solution providers will start partnering with their users to determine the ROI of using a solution. Many times these measurements can be straightforward, such as calculating how much revenue is saved when using data sensors to predict when parts will wear out. However, calculating the ROI on other solutions that combine structured and unstructured data will be more challenging to determine.
Data in the Internet of Things will start to be used instead of just collected
Sensors on many devices will help companies predict when parts need to be serviced and can also predict anomalies in the overall system. However, many companies have yet to realize the full potential of this data. In 2016, more companies who collect this type of information will no longer just store it but start to use this information to help prevent down time and achieve better customer service. Also, with the increased adoption of personal healthcare devices, such as Fitbits and smart watches, more consumers are going to start tracking their own healthcare. Companies that provide solutions that monitor and make recommendations on a consumer’s heart rate, blood pressure or fitness activity will grow.
The need for simplified Big Data
Currently, many of the traditional big data solutions that make real-time decisions require users to be very tech-savvy and require substantial coding. However, in 2016, we will probably see more companies purchasing tools that can be easily used by non-technical users. This is because there is currently a shortage of data scientists and the average salary of an entry level data scientist is quite high compared to that of an entry level analyst. Many companies just can’t afford to have data scientists on staff. Also, customer facing groups want to be able to see results in real-time and not wait for the IT or data science group to get them the information they need. Solutions will still need to be set up by data scientists and software engineers, however, once the solution is set up, non-technical groups such as marketing and customer service will be the ones accessing the data and writing simple queries to find the information that they need in real-time.
2016 will definitely be an exciting time for big data! The Entrigna team is looking forward to working with companies in the next year to discover how we can help them make and achieve their big data goals! For more information on Entrigna please e-mail email@example.com.