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How Digital Marketers Are Leveraging AI Tools And Automation In Advertising

For most users, their first experience with artificial intelligence (AI) was with chatbots that answered questions with pre-populated answers. From Indian Railways’ sari-wearing chatbot Disha, to Amazon and Flipkart’s shopping assistants, to Instagram’s algorithmic advertising, to Uber and Ola’s dynamic pricing, to Zomato and Swiggy’s restaurant recommendations, everything is in digital marketing. An example of using AI. .

This is probably the most basic way to use AI and natural language processing for marketing and sales in India, but today’s technology is more than just using bots on his website.

According to Absolutdata co-founder Sudeshna Datta, marketing is primarily about improving a user’s experience, whether traditional or digital. And today, artificial intelligence is helping digital marketers deliver customer experiences that directly increase customer retention and visibly increase brand loyalty. With data at the heart of the customer experience, organizations can really see the impact on various metrics in real time.

Absolutdata is a data analytics and research company that provides customized AI solutions for enterprises. According to a Salesforce report, 51% of his global marketing leaders are already using AI, and about a quarter more plan to use it in the next two years. Startups like Absolutdata are at the forefront of this change.

Even big companies recognize it. “Marketers around the world are using AI-based solutions to optimize the customer journey,” Rakesh Jaitley, Senior Sales Director of Customer Experience (CX) Solutions at Oracle, told Inc42. rice field.

He said it has become easier and faster for marketers to process data and formulate insights about their goals. AI can help create and run personalized campaigns for all customer segments at once, he added.

The Impact of Artificial Intelligence on Digital Marketing

By using automation technology for marketing and customer experience, companies can expand their capabilities with minor adjustments. AI tools have enabled brands to enable use cases such as:

  1. Data-Backed User Targetting
  2. Content Automation
  3. Predictive Analysis Of Customer Behaviour
  4. Real-time Customer Support
  5. Automated Ads
  6. Ad-Content Optimisation (A/B Testing)
  7. 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.

  1. 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 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.

  1. 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.

  1. 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.

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.

  1. 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.

  1. 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.

Businesses are required to simply feed in multiple headlines and description lines in Google’s responsive search ads tool and then the company’s machine learning tool automatically tests different combinations to find the best combination for any search query and user. This intelligent tool is able to alter the company ads for the same search depending on the change in context.

  1. Mixed Reality Integration

Thunder’s Sharma noted that in the coming years, mixed reality experiences such as augmented reality-based customer experience tools will help marketers drive more and more value from consumers and viewers.

She gave the example of Ikea’s Place app which uses augmented reality to help users virtually place its range of home products in their house. Similarly, VR applications in retail locations will help marketers sell products in a more immersive environment.

Furniture ecommerce company Pepperfry is looking at VR studios to maximise retail footprint, while interior design platforms such as HomeLane have also built similar products to enable 3D visualisation of their design solution.

The Data Challenge In AI & Digital Marketing

Absolutdata’s Datta said the information collected and processed by AI algorithms is of no significance without proper analysis. Most companies lack the understanding to draw insights from this data. Another challenge in the space is the high cost of using AI, which creates a barrier for many companies to start using AI tools.

Further, Datta also noted the existing skill gap in the artificial intelligence space. A Datalabs by Inc42 analysis found that the scarcity of highly skilled tech workers in India was one of the biggest hindrances in the business growth of deeptech startups operating in India.

In the Union Budget 2019, finance minister Nirmala Sitharaman had also proposed to bring a new education policy which would focus on skill development among technology-intensive sectors such as —AI, Robotics and Big Data Education. According to the World Economic Forum, over half of the workers in India will need reskilling by 2022, to meet the future talent demands.

Further, Sharma said that other challenges in using artificial intelligence for digital marketing is its limited number of use-cases and India’s lack of structured customer data is a major hurdle for businesses.

Nevertheless, brand marketers are talking about the future of AI in digital marketing in bullish tones. Datta believes that in the next three years, up to 55% of multichannel marketing messages will be issued by automated marketing systems based on predetermined goals and real-time consumer behavior.

President of Bloggers Alliance, Amit Nagpal also noted that Indian users are very contextual in their conversations and hence, AI chatbots are sometimes not able to grasp the tonality of user requests. He gave the example of a customer support bot that thank customers in response to sarcastic comments about poor service quality.

In the future, Nagpal thinks human collaboration with the AI chatbots will be needed to make customer support more understanding of user requests.

Deloitte’s 2018 analysis also noted, as  more and more companies move towards automation, technologists are recognising that automation and AI are most effective when they complement human insight, not replace them.

Oracle’s Jaitly agreed. “While technologies like AI, automation can help do things faster and better, giving a human face to the  brands and creating profound connections with customers will always be the job of humans.”

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