Over the last few years, the way analytical tools have proliferated the market is phenomenal, especially in the world of marketing. These tools have gained supreme importance mainly because they have given marketers the power to precisely identify the factors that drive growth and return on investment. There is no question about the need for analytical tools, but about the clarity on what to measure, why and how.
However, there are lots of analytical tools available in the market today such as Google Analytics, Kissmetrics, and more and we are only spoilt for choice. Often when you talk of marketing analytics, people tend to think of analysing data from the information they have collected from campaigns, websites, social media platforms and more.
For example, if we are talking about the effectiveness of a website, people tend to look at the bounce rate (the percentage of people clicking on a search result, and getting into your web page, but then immediately decide to abandon the page as they don’t see what they came looking for), website hits over a given period, unique visitors, etc. But analytics as a domain has much more to offer than this kind of a short sighted approach. To an extent, I would blame some of the tools that exist in the market today for the short sighted approach.
The reason I say so is because most tools serve as a source of information as to what has happened. Say for example, where is the 80% of my web traffic coming from or which of my products are being downloaded the most from whatever source. But they don’t exactly show you the cause as to why it exactly happened that way. The situation becomes trickier when you have carried out four or five marketing activities in parallel. It becomes hard to identify what actually worked for you because you can only see which channel got you the maximum result. It is important that analytics help you identify the strategy that has worked for you more than the communications channel.
In fact, it doesn’t end there – analytics isn’t just about a post-mortem, it needs to drive decision making. The analytics industry in itself is in transition from predictive analytics to prescriptive analytics. It refers to moving away from predicting the future based on the past occurrences to identifying the most advisable decision given the situation, calculating the odds. I think, very soon augmented intelligence will have a huge role to play in the evolution of analytics. It will boost analytics by combining the power of machine learning with human curation and intuition.
The combination can result in an amazing synergy which would be way greater than the sum of its parts. By doing so, it would make it easy for anyone in the organization to interact with data. As more and more companies are becoming data-driven in their decision making, it will be better to combine the power of algorithms with human curation. As a staunch believer of Darwin’s evolution theory, only the fittest combination will survive, thereby ensuring better business outcomes.