For most users, the first experience of artificial intelligence (AI) was through chatbots that responded to questions with preset responses. From Indian Railways’ saree-clad chatbot Disha, to Amazon and Flipkart’s shopping assistants, to Instagram’s algorithm-backed advertisements, dynamic pricing on Uber and Ola to restaurant recommendations on Zomato and Swiggy — are all examples of AI use-cases in digital marketing.
While that may be the most basic way that AI and natural language processing is being used in India for marketing and sales, these days technology has grown beyond just bots on websites.
According to Sudeshna Datta, cofounder of Absolutdata, marketing is largely about enhancing user experience whether traditional or digital. And these days, artificial intelligence is helping digital marketers provide the customer experience that directly boosts retention and increases brand loyalty measurably. In fact, with data at the centre of the customer experience, businesses can see the impact on various metrics in real-time.
Absolutdata is a data analytics and research company that provides customised AI solutions to businesses. According to a Salesforce report, 51% of marketing leaders across the globe are already using AI and about a quarter more are planning to do so in the next two years. Startups such as Absolutdata are on the bleeding edge of this change.
Even large-scaled enterprises have recognised this. Oracle’s senior sales director, customer experience (CX) solutions, Rakesh Jaitly told Inc42, “Worldwide, marketers are leveraging AI-based solutions in order to optimize the customer journey.”
According to him, it has become easier and faster for marketers to crunch data and formulate insights into their targets. AI is helping them to create and run personalised campaigns for all the customer segments simultaneously, he added.
Effect Of Artificial Intelligence On Digital Marketing
As a result of the use of automated technologies for marketing and customer experience, businesses can extend their capabilities with just a few adjustments. AI tools these days allows brands to enable use-cases such as:
- Data-Backed User Targetting
- Content Automation
- Predictive Analysis Of Customer Behaviour
- Real-time Customer Support
- Automated Ads
- Ad-Content Optimisation (A/B Testing)
- Mixed Reality Integration
Let’s dive deeper into how companies are using AI for each use-case.
1. Data-Backed User Targeting
AI algorithms help companies analyse customer data and make predictions about buying behaviour and thus eliminating intuition and guesswork in making marketing decisions. One example is ecommerce ads that are based on browsing history and wishlisted items. Similarly, Instagram depends on liked accounts and posts to decide which ads to show users.
This is not just limited to product advertisements, according to Aarti Sharma, founder of Thunder Brand Solutions. She told Inc42 that algorithms have helped companies like Netflix and Spotify to drive user engagement and retention. In fact, this also helps these platforms understand what kind of content or genres to pursue in the future for any given geography.
2. Content Discovery And Automation
Digital marketers can use AI algorithms to automate several basic and repetitive tasks in order to save time and work efficiently. For example, AI tools help websites surface the right articles or content to users given their current activity or engagement point. Some of the tools allowing this automation are business marketing intelligence platform Piano.io and content creation tools such as Taboola, Wordsmith, Articoolo, and Quill, which are already being used by some media outlets to create highly-optimised news and content discovery.
Speaking to Inc42 earlier, Ran Buck SVP at Taboola said that the company is different from Google, Facebook or other ad networks. It considers itself a hybrid that combines content aggregation and digital advertising as well as analytics driven by huge sets of user data which it has accumulated over the years. Taboola’s AI and machine learning (ML) algorithms are used to help increase the effectiveness of the content it promotes on partner websites, and the analytics from this helps brands tailor their digital content.
3. Predictive Analysis Of Customer Behaviour
Companies across the world are collecting data all the time about each interaction or action taken by a user. Purchase behaviour drives recommendations and also helps brands predict future purchases. Data management and predictive analysis can collect data from second and third-party websites and services. This means that AI algorithms are collecting data about users across websites and is not just limited to one session. Such a repository of data could help companies to predict the potential buyers of their product even before approaching them.
“Though predictive behavior analysis is still in its nascent stage, AI is constantly collecting, analysing and interpreting data to get smarter at utilizing it. With new algorithms coming in all the time, the AI inches towards perfection every moment,” Datta told us.
4. Real-Time Customer Support
As touched upon earlier, AI-enabled chatbots have made it possible for companies to save hours of waiting time for customers. Today, chatbots give users the impression of interacting with an actual human being and that too in real-time. This aspects also helps companies in providing a positive user experience and thus inspire brand loyalty.
According to Salesforce analysis, “57% of marketers expect AI to impact automated social interactions using chatbots and interfaces.”
For instance, Reliance-acquired Haptik lets customers chat with voice assistants to complete daily tasks such as online shopping, travel bookings, food delivery among others. It counts Samsung, Oyo, KFC, Coca-Cola, Tata Group and Club Mahindra among others as its clients.
Haptik’s Intelligent Virtual Assistant (IVA) solution is claimed to be far more advanced than regular conversational bots. Leveraging the power of advanced machine learning and natural language processing technologies, the IVA engages customers in conversations, pinpoints their intent, and executes the tasks required to resolve their issues end-to-end, cofounder and CEO Aakrit Vaish said.
5. Automated Ads
When it comes to online ads, AI plays a huge role in the current day. Google runs one of the world’s largest online ad networks and its automated bidding feature enables marketers to tailor their ad bids based on the likelihood that an individual impression will lead to a click or conversion. Google’s machine learning capabilities prioritise brand and business agendas while automatically managing the amount spent from the assigned budget.
Similarly Google has specifically helped small businesses with AI-driven local campaigns. This helps companies increase offline store visits by targetting the right users in the vicinity. Businesses have to provide a few simple inputs to enable this feature such as business locations and the creatives. Following which, Google automatically optimises the ads across its family of services to bring more customers into the particular store.
6. Ads Optimisation
Besides targetting the right users through automated ads, Google also offers responsive search ads which makes it possible for businesses to optimise various versions of the same campaign without having to manually run A/B tests for iterations.