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Despite the complexity and the fair share of difficulties, digital marketers are welcoming artificial intelligence as deep learning, machine learning, and natural language processing integrate to routine tasks. With AI-driven strategies, marketing teams are able to drive advanced customisations, cutting-edge personalisation, and simplified analysis. Using the colossal amount of data achieved through digital channels, AI holds the power to inspire target marketing, enhance customer experience, and garner a high ROI.
To help digital marketers understand the true potential of artificial intelligence in digital marketing, Manipal ProLearn organized a webinar to explore the impact of artificial intelligence on digital marketing.
The webinar - How AI is powering digital marketing? – was a live session by Gokuldas K, a digital marketing expert in FMCG, e-commerce, food tech, advertising, training, and e-learning industries, currently senior marketing manager at Swiggy.
Understanding the Role of AI and ML in Digital Marketing
Mr. Gokuldas initiated the session by explaining how artificial intelligence and machine learning can bring about a disruption in traditional marketing. Since modern processes are tasks fuelled by computers and programs, traditional marketing doesn’t serve the purpose well. He then, revealed some reassuring statistics – we can automate 50 percent of work tasks, processes, and activities with the help of technology and 80 percent of these processes can be automated using machine learning alone.
He further deciphered the processes that go into the carrying out of several marketing tasks by marketers. Today, marketers utilise machine learning and artificial intelligence for the following purposes:
Customer acquisition and retention.
Intelligent discounting.
Product personalisation.
Media optimisation.
When we receive a notification, customised discounts, and personalised feeds, what actually goes into this personalisation is a series of intelligent processes. A huge amount of consumer data is cleaned, processed, and analyzed to understand who the customer is, what they want, and what they are looking for.
How Artificial Intelligence is Transforming Digital Marketing?
Role of Artificial Intelligence in the Universal App Campaign
In 2015, Google launched its Universal App Campaign and we saw a new digital wave empowering digital marketing. It is an ad campaign form that allows businesses and developers to easily launch campaigns on Google’s ad networks including YouTube, Google Play Store, AdWord’s search, and display. In 2017, it was recorded that Google was successfully able to provide 6 billion installs to various developers.
The UAC campaign can be set up and executed in less than 10 minutes. However, the processes that form the backend of the campaign stays unapproachable and unknown to the marketer. Now, this is a matter of grave concern to a learned marketer who wants to control and optimise the processes that form the campaign.
Understanding the processes that run behind UAC can palliate many of these concerns.
During manual targeting in digital marketing, a marketer usually develops 10-15 different campaigns just to grasp the essence of the customer requirements. Here, manually optimising the campaign, acknowledging the factors to scale and descale, and moving towards the desired outcome is another herculean task. However, for machines, UAC backend in our case, it is achievable.
UAC is completely built on machine learning, which indicates that the ad campaign, though running at the backend, understands your user. The system recognises the customer, what they want, where to find them, and their differentiating characteristics. Knowing the past behavior of the users allows the system to automatically run the algorithm after optimising the required processes.
When setting up graphics, videos, and images for a campaign, every marketer optimises creatives to suit the requirements of the project. With UAC, you have the autonomy of uploading multiple videos, images, or creatives. The ML and AI processes executing at the backend will automatically optimise and align the requirements of the creatives with the ad campaign.
Thousands of differentiators, aspects, and features run along with these machine learning algorithms at the backend of the UAC. From the type of customer to devices used, every bit of information is gathered to further optimise the campaign for advanced campaign results.
However, one crucial question in front of the marketers is, ‘How does the machine understand your exact requirements?’
To make machines or algorithms understand the requirements, marketers need to acknowledge how machine learning works. For instance, a toy-store retailer is required to pursue parents to buy toys for their children as the child can’t do it himself or herself.
How do you make an algorithm understand this requirement?
It is through the knowledgeable inputs of a skilled marketer.
What are these inputs?
The goal of the campaign. For instance, installs or in-app events.
The KPI of the campaign.
The budget of the campaign.
The creatives and visual communication of the campaign.
The conversion tracking related to the campaign.
The input offered by the marketer forms the foundation of the UAC campaign. Take conversion tracking, for instance. If the conversion tracking is not enabled in the system, you would never be able to draw upon the knowledge of past user behavior. You would not be able to know the users who are signing up for your campaign.
Role of Artificial Intelligence in Programmatic Advertising
Delivering the right message to the right user at the correct time is the basis of programmatic advertising. It is a technology-driven automated method that allows buying and selling of online ad spaces.
Traditionally, this lifecycle involved personally contacting the ad-space providers for an ad campaign. Needless to say, it is an inefficient method as it would become humanly impossible to host an ad on various platforms.
Programmatic advertising is an ad-tool that integrates ads from various vendors at one place. With the help of DSP or Demand-Side Platform and SSP or Supply-Side Platform, digital advertisements are exchanged or purchased.
But, programmatic advertising also raises several questions regarding the execution of the ad purchase.
How does programmatic advertising work?
How to track the ads?
Who is able to observe the ads?
How ads can be purchased?
This is where AI and ML helps.
With the assistance of multiple market DSPs, the buyers can carry out several exchanges and reach out to a relevant audience. The DSPs utilise multiple data management platforms along with data incoming from SSPs, partners, ad-exchanges, and publishers. This data is analysed using an algorithm to answer all the above questions.
Below we have mentioned the tasks achieved by DSPs.
Prediction and planning.
Identification of the target audience.
Campaign optimisation.
AI-driven analytics and insights.
Enhanced targeting.
AI-powered creatives.
Moving Forward: Importance of Artificial Intelligence in Digital Marketing
The computers, machines, and processes utilised by machine learning understand the users and other aspects of the campaign through past data. It extracts data related to customer purchase, demographics, buying patterns, and other customer details to predict target audience, campaign budget, and end-goal.
Just like a human mind that learns when changes are observed in the environmental factors, a machine learning algorithm learns whenever a change is observed in the processes and inputs. These modifications become a source for constant learning and relevant future implementations of marketing campaigns.
However, human expertise is key to a successful campaign as the data lies with us. Deciding the goal, target audience, and budget of the project is rightly achieved with creative human processing. The machines can achieve these tasks, but human intelligence has the ability to consider several other factors and aspects that machines can’t. Hence, machine learning can transform digital marketing with the help of expert human guidance.
