By Atul Raja
Actionable consumer insights are creating ‘never before’ experiences, smart engagements, and increased conversions. The results of two recent surveys caught my attention but certainly did not catch me by surprise.
Deloitte’s 2020 global survey of early AI adopters showed that amongst the top five AI objectives, three were marketing-led, i.e., enhancing existing products and services, creating new products and services, and enhancing relationships with customers.
Also, as per Salesforce’s sixth State of Marketing report (2020), a significant 84% of marketers reported using AI for marketing. This is up from 29% in 2018!
As a career marketer, I feel AI is like a humanities discipline that enables understanding and decoding human intelligence and cognition. There is unanimity in the industry that AI is no longer the ‘future’. It has arrived, and it’s very much here to stay. I have never seen or tracked such a fast-moving technology, and this just seems to be the start!
So, how are the AI-based advanced machine learning algorithms building solutions that will continue to streamline the rigors of crunching huge amounts of data analytics and time-consuming tasks that marketers struggle to deal with on a day-to-day basis? While the AI horizon is extensive, let us examine some of the current and significant AI-led developments in the world of Marketing.
P-E-M: Pre-emptive Marketing
AI is being leveraged to achieve a high level of data analytics that map customer personas based on virtual and on-site interactions, predict purchase patterns and consumer behavior, identify referral sources and create effective customer segmentation.
Once these patterns are identified, marketers can preemptively promote solutions, products, or programs to their respective audience segments.
An excellent example of pre-emptive marketing is Netflix and its ‘you may also like’ prompt. Netflix’s hugely appreciated recommendation engine amalgamates viewing data and runs it through their AI programs to pinpoint similar shows or movies for a viewer to enjoy.
A marketer’s dream is to reach out to individual customers or a specific group with customized communication. AI is fast realizing this dream. The hallmark of hyper-personalization is that it takes consumer experience to the next level with the help of predictive analytics, UX, and content applications. The result is the creation of an empathetic brand that delivers results.
Currently, hyper-personalized marketing predominantly sees its applications fructify in the retail and e-commerce segments. Thanks to its enormous inventory and subscription options, Amazon engages with its customers on a 360-degree basis right from the home page. Not many know that Amazon also delivers a customized homepage for every customer based on their previous purchasing behavior, preferences, browsing history, and entries to the cart.
Starbucks has shown that the more customer data you capture, the more laser-sharp your marketing can get. The company successfully integrates the data from its gamified mobile app and loyalty/rewards program with information such as purchase history and location to provide personalized communication and offers to individual customers.
Optimizing Marketing Spends
AI can throw up data to target advertising to higher-intent audiences and maximize retargeting efforts, thereby reducing the wastage factor, and stretching the value of the advertising dollar; combining AI with tools like campaign budget optimization, dynamic bidding, and dynamic creatives can power marketing budgets towards higher ROI.
AI’s inherent advanced data processing capabilities are being leveraged to identify the proper channels to market, the right target audience, the right markets, the right influencers capped with predictive analytics for smart cost calculation that can save millions of dollars from advertising budgets.
Trends clearly show that hyper-personalization can turbocharge a brand’s ROI by delivering smarter and more targeted campaigns.
Lead Management is defined through ‘Growth Marketing’ and ‘Performance Marketing’, two of the fastest developing areas in the marketing domain. While sales teams are looking at Marketing to get the so-called ‘hot leads’, Marketing teams have traditionally struggled to find the right TG or customers in the ‘considered set’ for better outcomes and optimal cost/lead.
Let’s take an example of how AI can help marketers reach the right customers at the right place. The AI engines can connect to CRM systems and optimize the ads for multiple platforms. They can also shut down non-performing ads. Simultaneously, marketing campaigns are directed to customers who are liable to be in the ‘interested category’. This level of automation across platforms, customers, and markets has the potential to be a game-changer for both inbound and outbound lead generation and conversion efforts.
AI technology can help content marketers appeal to their target audiences more efficiently and easily. Human creativity will remain at the core of the content, but AI tools can help achieve more humanity. Today, a significant portion of sports and finance-related articles are written by machines as both these sectors are traditionally number-heavy, making it easy for AI programs to understand the data and translate it into human-readable articles.
However, as marketing becomes increasingly more focused, the content will begin to be written (or at least outlined) by automated programs for other sectors.
It is estimated that the current AI-led global spending on artificial intelligence hardware, software, and services is more than $340 billion, and this will rise exponentially in the next few years as AI will have many more smart applications than I could list in this article spanning from maintaining trust and transparency through authentic communication (avoiding the menace of Fake News), Virtual and Augmented Reality, efficient response in times of crisis, understanding risks related to corporate reputation and bridging communities and disciplines.
Source: Agency Reporter