Speed of Adoption will matter more than ever
It’s been a while since businesses have been debating over investment into data and analytics. Some people have already done it and it is working out. We are over and above the apprehensions of whether Data investments work or not, now, the questions is how soon you can make it work. It has to be strategy first and a top down push on getting the data investments to execution and results. It is a herculean task but by now there are already best practices and open source tools to help adopt the data solutions. You cannot do it half-heartedly, you must determine before 2019 starts on how much are you going to be data-led and then be true to yourself as an organization.
Machine Learning will still be a buzz, Platforms will rule the world
Machine learning and Deep learning buzzwords are here and they will be here for a while. Automation is a no brainer, whether it is making processes efficient or models. Unsupervised learning has been proving its application in every single area of technology utilization for good. As the human interactions with technology becomes more and more multi-faceted leading to complexities in understanding the patterns in usage, it is imperative to expect more and more need for abstraction and automation of algorithms to decipher the insights. Scalability is another important aspect and platforms bring just that. We all will see a huge surge in rise of the platforms that solve specific marketing and customer problems with the use of algorithms, across industries
Open data and connected data will be the key for data economy
Data Co-ops and partnerships are a reality. No one owns the customer and only way to complete the puzzle is for the companies to come together and share the information. Data Privacy and security will be a constant challenge but that’s what make the technology interesting. I foresee the advent of many innovative companies to solve the challenges in secure and anonymized data sharing for good of all
Data Acquisition will be a priority for businesses.
The sample bias is still prevalent, and the meaning of analytics has gone beyond “Crunching your customers’ past behaviors”. The internal data is not enough and there is a happy realization by companies to focus on getting external data and more data about their existing and prospective customers. Companies will spend more in 2019, on acquiring data- from 2nd party to 3rd party to government data.
People based marketing will replace data-based marketing
The omni-channel complexity needs to be solved and the time is now. Advertising spend spills, less precise targeting, probabilistic view on customers and inaccurate attributions will be more heavily challenged, considering the rise of technology that can solve this problem by resolving customer identities and help identify real people and not just cookies.
Buy Vs. make strategy will skew towards “ Buy and Make” Stratgey
It is going to be a hybrid play for setting up analytics capabilities. Companies have long realized they can’t just build CoEs on their own, neither it is wise to just depend upon consulting firms to make the magic work for them. The future trend is going to be taking help from experts and build your own capabilities faster. Specialized strategic consulting companies can help teach how to build the capabilities and the platforms will help reduce the dependencies on creating data scientists vs grooming business guys to help drive data led transformations
Digital transformation will get real, Marketing Automation will speed up
With all the consolidation and investments in Martech/Adtech, it is well proven that Digital transformation is now more real than ever . We have come past the education mode and now it is execution mode. Companies really want to achieve marketing automation and many are half way through it.
Data Scientists will transform their role into solution evangelists & Story tellers
The constant challenge of data guys being too technical or objective has now been understood by traditional data scientists. With the help of great visualization tools and aid of data processing platforms, now is the time for data scientists to be more business savvy and tell their stories more effectively.
The most promising data opportunity will be to educate people about data
There is still a huge gap in terms of business guys or marketers being completely convinced to harness the power of data, to an extent of transforming culture. There will an uptick in the number of “educators” coming out to educate people through open platforms, Linkedin, Meetups, internal company platforms and paid events. You will have more data conferences, Seminars and gurus in 2019 and we need them.
