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Expert’s View: Divya Dixit on How ALTBalaji Uses Customer Data and AI to Predict and Personalize Engagements
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Expert’s View: Divya Dixit on How ALTBalaji Uses Customer Data and AI to Predict and Personalize Engagements

One can’t talk about OTT platforms without mentioning personalization and recommendations. Ecommerce and OTT platforms have been heavily thriving on AI-led personalization for all the right reasons. Time and again consumers have shown an inclination towards personalized content. OTT platforms like Netflix and Amazon Prime consistently talk about how their consumers respond to personalized communications and recommendations positively. AI and ML have made it easy for them to know why their consumers are watching a particular show or why they are “not” watching a particular show and most importantly, will they like an upcoming series or not.

As a part of our ‘expert view’ series on AI-led personalization in association with ResearchNxt, this time we had an extensive conversation with Divya Dixit, SVP Marketing, Analytics, and Direct Revenue at ALTBalaji. In this interview, she talks about how they leverage customer data and AI-enabled tools to predict consumer behavior and personalize consumer engagement for their OTT platform.  

Your key takeaways from this interview

  • The role reversal of marketing budgets between Ambivalent Media (TV) to digital media. AI and ML for personalization and better engagement.
  • What’s ALTBalaji’s mindset marketing strategy and how it helps leveraging customer data analytics to personalize user experience.
  • AI use cases to predict user engagement or behavior even before the show is launched.

Here are a few extracts from the interesting conversation we have had with Divya.

“Across the media and entertainment industry, I would say the latest trend is going digital all the way.”

Netcore : You were part of many organizations across multiple industries over the past two decades, and now you are a marketing leader in the Media and Entertainment space. What are the key trends you have observed over the past decade across various industries? 

Divya: I started my journey as a marketing executive in retail, and from retail, I moved to broadcast media, then to music, to telecom, and finally now in the digital space.

The trends that I observed in retail were quite a few; however, the most interesting was being called “The Barista Generation” because the key trend then was the start of the coffee culture and socializing over a cup of coffee in a chic ambiance. Another trend that I started at Barista was creating merchandising and space selling categories that got later adapted by many coffee chains. Moving on, when I shifted to broadcast, I observed the fact that the broadcasters then, could create mindset changes via content and there are multiple examples like Balika Vadhu with a social message, Indian Idol, Big Boss, Jhalak Dikhla Jaa, etc. which gave rise to reality shows viewing culture. At Tata Docomo, we created the trend of “pay per second,” while the industry trend was “pay per minute” therefore exceeding the subscriber count by 3X of what was expected. Six months later, TRAI made it mandatory for every telecom player to introduce the plan of pay per second. The music industry introduced the trend of EDM – Electronic Dance Music, and LeEcO started the trend of creating a 360 degrees ecosystem comprising of content, apps, and peripherals.

Across the media and entertainment industry, I would say the latest trend is going digital all the way. From a time when only 7% of marketing budgets were allocated to digital, it has come a long way now that digital gets at least 70% of the same budgets. It is a considerable change in how marketers across industries depend on digital, AI, and personalization for consumer engagements rather than using the ambivalent media or TV.

“We are using personalization, predictive analytics, and measurement using AI to interact, engage and serve our viewers with their content and communication preferences in mind.”

Netcore: I am sure that this shift comes with its own set of inherent challenges because you also need to have content concerning consumer trends. How are you leveraging technology to meet consumer demand in terms of personalization of content? Is ALTBalaji using AI in any form to manage content personalization at scale?

Divya: Yes, there are challenges, and that is where the analytics behaviour comes into play. We at ALTBalaji not just look at segmentation across basic demographics, i.e., age, location, and social attributes, but also emphasis on something called mindset marketing. Here is an example of mindset marketing.

Last year we launched season two of a show called “Broken but Beautiful” meant specifically for the urban women and men. However, after a certain point in time as our regular exercise, we tried to identify the behaviour of the viewers who were churning out to find out what had they been doing on the app, time spent, other shows watched, and which top five shows were there on their priority list. The results were quite an eye-opener for us. The first show that they onboarded with was “Broken but Beautiful,” but the next show a certain segment of that audience saw was “XXX,” which is from a completely different genre. This shows that there is a tendency among the viewers to change genres at the flick of a button and busts the myth that women do not see sensual shows. We also identified that not just the young women, even the ones above 45 or even from the small towns, watch sensual shows. So, there is multiple interesting behaviour analytics that can be found through data science. Using AI, we reached out to these women viewers and sent them personalized messages that they anticipate. This means that a certain segment of the viewer community is more open to various content genres, and there is a possibility of engaging more with these sets with multiple pieces of content at once. These are the kinds of discoveries and actions we are leveraging out of analytics and trying to personalize the communication and improve engagement and subsequent action.

Netcore: Are there any other AI use cases that you would specifically like to mention helping ALTBalaji achieve business growth?

Divya: We use personalization in our messaging across business WhatsApp, emails, SMS, and push notifications to reach out to various consumer segments daily to control the churn. We also use AB testing across our viewer base with offers while onboarded by serving segment-specific content using AI-led personalization and hyper-personalization. We subsequently track the response that lets us understand how each consumer is reacting to what type of personalization. However, we must realize that AI, for us at this point, is still at a very nascent stage and can only improve with the data wisdom we acquire. 

Another case is that we are now going to use AI to measure and predict user engagement based on their behaviour for specific shows daily. This will help us create a predictive user journey and a model that allows us to map a show performance well ahead of it being launched. So, to sum it up, we are using personalization, predictive analytics, and measurement using AI to interact, engage, and serve our viewers with their content and communication preferences in mind.

Our goal of content discovery during this phase has not changed, and it is the mediums through which we reach out to the consumer that has changed.

Netcore: Very recently, ALTBalaji and Vijay Sales formed a first of its kind strategic alliance for in-store branding for a web-series, creating visibility to a captive high net worth audience, maximizing brand recall, and business ROI. What other vital initiatives have you been executing as a marketer in the OTT space?

Divya: OTT is typically divided into a few kinds of business models for apps, and one of them is SVOD (subscription video on demand) business model. Examples of some SVOD apps are ALTBalaji, Netflix, Amazon Prime Video, which are strictly subscription-driven platforms. We have no AVOD (Ad-based Video-on-demand) content available. With us, at ALTBalaji, most of the first episodes of a series are free, and the rest is entirely behind a paywall for which viewers must subscribe. Network backed apps like Hotstar, ZEE5, Voot, etc. are a combination of AVOD and SVOD. They have their broadcast channels catchup content on an AVOD platform; however, original content or movies are always a part of their SVOD offerings. Typically, AVOD platforms are supported by advertiser revenue, whereas the SVOD platforms will have opportunities available so as not to disturb the consumer ad-free viewing experience.

We allow brands to participate in advertising only on the first free episodes, we do co-marketing on already shot content, and then we have content integration opportunities for advertisers. However, we are very particular about how the integration happens so that the consumer has a seamless viewing experience.

We have executed Virtual Reality of 10 mins around Ragini MMS 2 that no other OTT platform in India has done; we have done the Breast Buffer campaign that got us nominated in Cannes as well, and many such initiatives.

Netcore: Content production almost at a standstill for all production houses due to the Covid19 pandemic. However, there has been a spike in subscribers for ALTBalaji in Q4:2019–20 plus most of April. How do you manage the creation of new content and the distribution of existing content to keep the user stickiness intact? 

Divya: As India grows more digitally savvy and adds almost 10 million active internet users per month, as per a Google report, we can still target new viewers as for them, our library is new. We have the most extensive Hindi originals library compared to all digital platforms with 60+ original series. So for us, the tracks are parallel, library push, and the launch of new shows. We have already launched three shows during Covid-19 and planning to launch our fourth show, as well as we have several shows in the pipeline to be edited and launched over time.

Netcore: As a marketer, in the post-COVID-19 situation, what kind of trends do you foresee across industries? It can be specific to the OTT if you want to share that, or it could be just across in general for a marketer?

Divya: During Covid-19, as I said, our work hasn’t gone down as an OTT platform. We’re continually working and delivering to the consumer to keep them entertained during this tough phase. Our goal of content discovery during this phase has not changed, and it is the mediums through which we reach out to the consumer that has changed. In the current phase, we are not using OOH, print, or radio as an advertising channel. Instead, we are focussing on digital mediums, other OTT platforms, Television news channels, etc. 

The second trend we will see is the small-town focus. We are focusing more on acquiring smaller town, web viewers using a web light version, PWA app, for our library of content. So, from an AVOD perspective, things may not look good at the moment; however, things have moved up from a subscription perspective. Also, the advertising revenue for the broadcast industry will change in the equation as the post-COVID situation will see a lifestyle remodelling, and ultimately new normals will emerge for marketers to connect with the consumers. 

The third trend that I see emerging is virtual reality, digital engagement like gamification, digital payments and delivery, and digital healthcare and digital education that will be on the surge.

And on this note, our conversation with Divya ends. However, the insights she gave into OTT consumer behaviour were quite practical and useful. AI-powered personalization tools allow you to know where and why consumers churn, and what actions can be taken to win them back. And not forget about personalized content recommendations and keeping them seamless across all platforms. AI also helps predict behaviour of new users based on the behaviour of old users which ultimately leads to consumer retention and brand loyalty.

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