In the current context, AI has already emerged as the next big thing and has been adopted really well across healthcare, financial services, retail, automobiles, education and entertainments. This is just the beginning and the AI & ML ecosystem is going to evolve big time from here on in India, the latest report on why Indian companies are betting big on AI.
AI has intelligent algorithms which are learning and improving continuously; they’re fully capable of re-writing, modifying or customizing their actions with the ‘interactions, experience and feedback,’ so you get the best of the ROI (return on investment).
The impact of AI (artificial learning) and ML (machine learning) is evident big time in the marketing industry. Across the companies in various segments of B2B or B2C there are an ample number of digital marketing and traditional marketing applications in the current world. As consumers, we do not realize that you have been touched by the AI or ML. Many instances of IoT (Internet of Things) are governed by the principals of AI.
So, let’s talk about the implementation of the AI in the current market scenarios
Chat-bots: This is my all-time favourite, as I have closely worked in developing the user experience of a chatbot which was AI driven. The NLP (Natural Language Processing) has given AI the ability to drive context and content both. NLP also has the capabilities of helping in a new content generation which is dynamic, although, it’s evolving as of now. The chatbot’s can be used as per the business need, on your websites, emails, and apps.
- In the financial industry, digibank by DBS, one of the leading digital banks of our country has the best chatbot or a virtual assistant and it’s called “digibot”. It’s smart, intelligent and proactive. It can share your last transaction detail, to your account balance, spending overviews, mutual funds, mortgages, etc
- In the online food industry, the best experience so far has been with the chat-bots of Swiggy and Zomato, they are just next level. I have noticed various consumer journeys are mapped as per the needs of the consumer and at present are self-sufficient right from payment issues, wrong food items delivered, delivery issues, etc. A human intervention if required is brought in after initial conversations with chatbot.
Voice: Due to the extensive use of AI-powered voice virtual assistants the voice search has become the new phenomenon, there are various devices in the market Siri, Alexa, Amazon Echo, and Google Home.
Digital Marketing:As you know, the search engine algorithms keep evolving and google keeps on updating them so that the results are more genuine.
Over the years, the search engines especially Google has become intent driven than just the keywords, they are now capable of deciphering queries and inferring the exact meaning of search terms. All this is driven by AI enhancements based on the user search behaviors, the long-tail keywords are being replaced with more conversational keywords. This means the search will evolve and move to voice search this incorporates a more intuitive approach. Considering, how easy it is to engage a voice search the adoption will enhance only. As everyone wants a quick answer, the voice search based interactions will be shorter and to the point, thereby saving the precious time.
Programmatic Advertising: It can help the users to build on the artificial intelligence right from finding the best audience, suggestions on the time & place for any ad, all done through its Machine Learning models. Do check Adext,it runs thousands of simulations to discover the best performing audience and automatically update your ads budget with amazing results from 30% to 500% uplift, so you’ll no longer waste money in learnings
- Bids and Budget Management: This area involves infusing AI into the budget management decision process and this directly leads to how well your money is spent. This is such a big space, in terms of all the data decision engines, machine learning (ML) helps to ingest the complete data points into an AI tool to process and share the relevant information. The information right from the sentiment analysis, with relevant contextual analysis of a page, bidding, then the system decisioning the corrective steps
- Better User experience (UX): The AI-powered tailored solutions focus on the context of the customers. Enhanced user experience is a great metric of a successful marketing campaign. Customers want outstanding service and a seamless UX from start to finish, without any journey breaks. AI helps marketers to individually target the tailor-made campaigns for each user, further lead them to take desired actions.
For example, AI automation can be applied to website’s UX design in the form of A/B testing and self-optimizing landing pages of the website. Leading to the increased user experience from beginning to end.
- Target Audience Optimization: There are several targeting options (Audience, Behavioral, Re-targeting, Geo-targeting, Cross-Device, Contextual) which are available in programmatic, each method inherently varies based on the desired goals and type of targeting, still they all have one thing in common: They are focused on the customer and not the context.
Predictive Insights: A remarkable use of Big Data and Artificial Intelligence is predictive analytics, to extract meaningful information out of it. The process of using advanced tools like data mining, statistics and data modelling to predict the upcoming results or customer behaviours. Marketing campaigns can use inputs shared by the predictive for higher business performance, and better return on investment (ROI). The list of predictive analytics applicable for marketers:
- Customer insights: In programmatic, the AI algorithms can segment target audience groups based on multiple variables. Clustering the audience on the basis of behavioural traits, product based interest categories, and brand-affinity based clustering.
- Lead scoring:Scoring the lead based on the pre-defined parameters and directly sending the score to CRM for the customer care teams to action on high ranking leads. This helps, marketing and sales division to collaborate in a more meaningful way.
- Campaign nurturing: Using demographic and behavioral data, to nurture the campaigns, based on the user journeys do specific communications tailored specifically tailored to move the process towards conversions or sales.
- Upselling and cross-selling: Effective up-selling and cross-selling of by using the predictive analytics and big data, based on the buying patterns the companies can try to increase the bottom line.
Personalized product recommendations: Almost every leading retail and e-commerce company deploys AI-powered recommendation engines to effectively provide personalized suggestions.
The recommendation engines are based on their customers’ preferences, cart history, items they have liked, items viewed, and buying patterns. These insights help to give suggestions on products and services that their customers may be interested in. Knowing your customers’ buying habits can help to personalize the journeys and the user experience for your audience, specific communication to engage, leading to increased e-commerce sales.
Artificial intelligence (AI) and Machine Learning (ML) are amazing technologies that can work wonders for any brand if you are clear on the application. It’s a long way to traverse, you need to create an open AI culture to build and cultivate trust, credibility and transparency that maintains both the human and machine relations.
AI can help brands deliver improved consumer experience and do more effective marketing but we have to devote time to improve this technology for our specific use, as it’s based on learning, reasoning and self-correction. Most importantly, as marketers, you would need extended support of your tech team to get this going in a big way across your organisation as there would be a lot of changes.
If you have benefited by the use of AI technology in any of your digital marketing efforts, let us know about your experiences in the comments below for others to understand the value behind the AI tech
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