Marketing analytics is the study of data to evaluate the performance of a marketing activity. By applying technology and analytical processes to marketing-related data, businesses can understand what drives consumer actions, assess big-picture marketing trends, determine which marketing programs worked and why, monitor trends over time, refine marketing campaigns, optimise return on investment (ROI) of each program and forecast future results.
Regardless of business size, marketing analytics can provide invaluable data that can help drive growth. Enterprise marketers at first may find the process too complicated, while small and mid-sized business (SMB) marketers assume a company of their size won’t benefit from implementing metrics, but neither perception is true. As long as marketing analytics is carefully curated and properly implemented, the data collected can help a business of any size grow.
Frequently, marketers talk about activities instead of outcomes – for example, how many campaigns they ran, how many trade shows they participated in, how many new names they added to the lead database, etc. Unfortunately, these are metrics that reinforce the perception that marketing is a cost centre, when in fact marketing is actually a revenue driver. Some of the technology tools deployed in conducting marketing analytics are website analysis, digital marketing analysis (SEO), marketing dashboard analysis, etc.
Marketing analytics helps to answer questions like these:
In an era when interactions through social media platforms are rampant and in abundance, it is humanly not possible to decipher the data and information residing in these public media and social media domains for meaningful marketing interpretation for decision-making. Not only is it physically not possible, but it will also mean a huge investment of time, money, and energy that cannot be afforded by organisations at any cost. Therefore, the use of technology has to be resorted to in these instances. One such example of the use of technology for business and marketing purposes is Sentiment Analysis.
Sentiment analysis is an artificial intelligence technique that uses machine learning and natural language processing (NLP) to analyse text for polarity of opinion (positive to negative). It’s one of the hardest tasks of natural language processing, but with the right tools, one can gain in-depth insights from social media conversations, online reviews, emails, customer service tickets, and more. It helps the marketer in understanding an opinion about a given subject from written or spoken language. By understanding what the target audience is thinking on a scale that only sentiment analysis can achieve, the marketer can tweak a product, campaign, and more to meet the customers’ needs and let the customers know that the company is listening. Sentiment analysis has become an essential tool for marketing campaigns because the marketer is able to automatically analyse data on a scale far beyond what manual human analysis could do, with unsurpassed accuracy, and in real time. It allows the marketer to get into the minds of the customers and the public at large to make data-driven marketing and business decisions.
Through this analysis, multiple tasks can be accomplished. The customer sentiment of a company can be analysed and compared against its competitors. The trends in the market and the emerging topics can be followed. The perception of a brand in new potential markets can be checked out, since the public offers millions of opinions about brands and products on a daily basis, on social media and beyond. Traditional metrics, like views, clicks, comments, and shares, just aren’t enough anymore – they don’t tell the whole story. Some of those reactions could actually be negative. The marketer needs to know exactly what the public/customers/target audience is saying, and then figure out the reasons to properly diagnose. And machine learning allows a company to perform the sentiment analysis automatically and on a regular basis, with almost no human interaction needed. With constant, real-time sentiment analysis, the marketer will always be prepared to make quick decisions and also take corrective actions as and when necessary.
While the marketing and business decisions increasingly will become technology dependent in the ever-dynamic business ecosystem, the decisions, however, still have to be taken by human beings at the end of the day, applying distilled wisdom and leveraging insights. Therefore, the use of technology for marketing and business decisions is just a means to an end, but not an end in itself.
