The last five years have witnessed an incremental shift in the mindset of what Artificial Intelligence can do to optimise marketing efforts for corporations globally. We’ve seen how more recently, Big Data has progressed from being a mere competitive advantage to a prerequisite that is now an integral part of the marketing circle – from developing creative campaigns, running them through the right channels and measuring the impact.
The availability of inexpensive analytics tools based on machine learning methods is driving marketers to pump out extensive datasets and colourful reports. It’s akin to outsourcing the simpler, repetitive tasks through intelligent automation to let the marketers make decisions based on machine learning, preconfigured rules and algorithms. From a work standpoint, this means a significant amount of the decision-making executives’ time is freed up to do more important tasks that require human input and focus. Strengthening customer relationships through human interactions and coming up with enhanced creativity in marketing being the two focus areas.
The Power Of Big Data
It is amazing to know what you can do with data now – something that was truly unimaginable just 10 years ago. While Big Data is not a new phenomenon, it is only now that we have begun to recognise the possible power of data-driven approaches to marketing related decision making. Big data allows you to collect and analyse more information and offers marketers the ability to focus on informed targeting for greater efficiency. The billions of fragments of data can be analysed through algorithms to suit an advertiser’s needs. Data and analytics have expanded our understanding of the consumer, allowing us to make quicker decisions thereby optimising the marketing efforts. It provides a single platform for data from multiple sources to be viewed in one place so that one can see what’s working for them and what’s not. Further, it enables the user to manage resources in a productive manner, in terms of appropriately spending the time, money and effort in the right direction to guarantee results. Needless to say, this also means more accountability across the board.
The Changing Consumer Story
Globally, the consumer behaviour is increasingly getting influenced by AI-powered tools and devices. By 2020, people around the world will generate 50 times more data than they did just six years ago. Although consumers may not still be fully comfortable handing over their need to make decisions to machines yet, they are invariably compelled to ride this wave. Product recommendations or price comparison websites for instance – which are more reliable and powerful than ever before. With this, the wealth of data created for advertisers can be used to find leads, generate relevant content and figure its impact. This will help better the marketing strategies and measure the success of advertising spend with real conversions and in-store revenue data. In a way, it converts marketing-qualified leads into sales-qualified leads to speed up the sales funnel.
The Web Of Things
In the current marketing technology landscape, there are a plethora of tools, data sources, analytics platforms and marketing technology software available. The key is to integrate the insights received across all of these tools so that they don’t operate in silos. One needs to have a meta-analysis approach where an integrative analysis is conducted of the results from multiple studies – because it is important to know that marketing analytics, when used judiciously, empowers; and when used incorrectly, it has the power to negatively impact the sales numbers. In the larger scheme of things, some marketers are far less capable with their data, being unaware of the goldmine available at their disposal and its utility. It isn’t a surprise then that despite the multitude of data and the availability of analytics and engagement systems, their organisations score extremely low on the customer satisfaction scale. At the end of the day, data interpretation is not an easy task. The idea is to deliver real-time, data-driven engagements across both physical and digital touchpoints, which requires investments in training and reskilling of staff and not just tools alone. You need a smart workforce that is equipped to analyse and use data, and who understand that AI is needed to help integrate across tools, datasets and platforms.
What’s interesting to watch is how the future will evolve in a world where both marketers and consumers are both influenced and managed by intelligent, data and analytics-based software applications. For this, the marketing teams need a higher level of digital literacy and a deeper understanding of how to use data to answer important questions such as how to advertise?; how to handle customer relationships?; and how to look into after-sales support? Data Science is interdisciplinary and it incorporates elements of mathematics, analytics, computer science and statistics. Therefore, the greater onus lies on those who are highly numerate and technically inclined, especially those with backgrounds in Math, Engineering and Science.
For this, the organisational leadership needs to think about taking proactive steps to enable themselves and their organisations for an AI-powered future of marketing. NIIT offers one-year blended learning Advanced Program in Data Sciences (APDS) from the Indian Institute of Management Calcutta with 275 hours of live online classes and campus visits spanning 10 days at the beautiful IIMC campus. The course aims to strengthen participants’ knowledge of advanced quantitative and statistical concepts and tools. It covers concepts of Machine Learning, optimisation, visualisation, distributed processing using Hadoop and MapReduce amongst others.
While we must not put technology innovation above the fundamentals of value-creation, purpose-based and customer-driven innovation, it’s important to know that it can be facilitated by new technologies. With Big Data, the bar of impact marketers can have on the consumers is continually being raised. And that’s a good thing; because now, more than ever before, the human element of an organisation’s relationship with its customers will become important.
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