Managing the strategy and delivery for the Research and Analytics Center of Excellence (CoE) for Time Inc. India*, Aldrin Luiz is passionate about data and how it can play a pivotal role in corporate decision making and deriving hidden insights and consumer behaviour patterns that traditional research methodologies by themselves would probably fail to discover. Serving as the Vice President, Research and Analytics CoE, his core experience as analytics professional spans multiple roles with organisations such as Ipsos and Nielsen, and has dealt with diverse set of clients in media, telecom, technology, banking and government domains.

The Research and Analytics CoE at Time Inc., India, which he has helped set up is responsible for working across business units to empower data and analytics to help drive revenue and business strategy across ad sales, editorial, subscriptions, newsstand and digital. In an email interview with Analytics India Magazine, he shares his insights on how the organisation has been benefited from the adoption of analytics so far,  future plans for analytics and much more.

Disclaimer:

*Time Analytic & Shared Services Private Limited, a subsidiary of Time Inc., is herein referred to as “Time Inc. India.” TIME INC. is a trademark of Time Inc. and is used under license by Time Analytic & Shared Services Private Limited.

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Analytics India Magazine: How analytics is central to the overall working of Time Inc.? In what ways do you leverage data analytics?

Aldrin Luiz: Analytics is helping empower Time Inc. to maximize the value of its extensive data assets to ensure that we continue to remain a leader in offering consumer-centric data driven content and ad solutions.

Some of the ways we leverage data analytics include:

• Providing the sales and marketing organization with actionable representations of audience behaviour (read “storytelling”) to help pitch for and drive ad sales.
• Robust ROI measurement on ads featured in our magazines/ dot-com properties, thereby enabling our brands to showcase their value and effectiveness in contributing to the advertiser’s marketing strategy.
• Content analytics to provide a feedback mechanism for editors to augment the value of their editorial initiatives.
• Site analytics to help development teams across editorial, design, marketing and advertising make informed decisions on improving digital viewership, user experience and efficacy of ad placements across platforms.
• Advanced modelling to support not only the execution of targeted advertising programs, but also to identify potential customer segments for acquiring and retaining profitable customers for our magazine subscriptions.
• Analysis of retail trends, promotions and covers to optimise newsstand distribution and enhance sales of our magazines at retail outlets.

Analytics India Magazine: Would you like to highlight a few use cases where the adoption of analytics has benefitted Time Inc.?

Aldrin Luiz: Being in the media industry, the two critical focus areas for us within digital analytics are – Content and Ad Inventory.

A key challenge facing digital publishers today is evidencing the value of their Ad Inventory. Advertisers want to ensure that their ads were not just served, but also had the opportunity to be seen and/ or interacted with by a real human being. This is where Ad Viewability and Ad Engagement metrics come in. Analytics continually helps us conduct diagnostics on ad slots on our digital properties and propose appropriate strategies to improve Ad Viewability and Engagement. Our network display viewability which used to hover around the 50% mark two years ago now stands at 70% (significantly higher than the industry benchmark) thanks to the work that has been done on Viewability modelling and diagnostics.

Content analytics frequently evaluates the interplay between two critical factors for an industry such as ours – content and audience. It tries to answer, “what content is likely to engage well with consumers and why?”  We explore the interaction between variables such as time spent/ page exit rates and causal variables such as page design, pictures, videos, article length, readability, story type, story sentiment, links, etc., in order to help inform editors and page designers how to get visitors to stay longer and minimize bounces.

Analytics India Magazine: Targeted ads is a big business for digital media houses. How does Time stay competitive in this space vis. a vis. other rivals?

Aldrin Luiz: Time Inc. has substantial data assets- 155 million subscribers and 135 million unique site visitors (of which 110 million are on mobile). We already know quite a bit about the directly addressable 155 million profiles by virtue of their present/ past subscriptions with us. We partner with various Data Management Platforms (DMPs) to better understand and activate the sizeable digital audience that our brands have. On the basis of how visitors to our sites search for and consume content, we are able to determine their interests, preferences and social affinities. DMPs help connect this behavioural and affinity data with additional audience insights and other disparate data points, allowing us to serve targeted ads that drive specific KPIs for advertisers.

Last year, Time Inc. entered the Ad Tech ecosystem through its acquisition of Viant, the parent company of Myspace and a data driven marketing company that has a database of over 1 billion registered users. This allows Time Inc. to blend its content and subscriber database with Viant. The acquisition has helped us unlock a number of opportunities such as creating powerful audience segments based on customers and their shopping behaviour data, understanding the true reach and frequency across devices, and gaining real time understanding of ROI from ad campaigns.

With media buyers calling for more transparency and Ad Tech moving towards a self-service model, Viant acquired the demand side platform Adelphic, offering marketers the ability to directly buy advertising that targets specific consumers. Outside of Google and Facebook networks, advertisers have to rely on cookies to target consumers but the Viant acquisition has helped us create the first “people-based Demand Side Platform” to allow advertisers to target specific people-based on the data they input. All these initiatives help us stay competitive in the targeted ad space.

Analytics India Magazine: What is your roadmap/plans for analytics at your company in the future?

Aldrin Luiz: Given the scale at which Time Inc. operates and the volume of data that is ingested on a daily basis, a data warehouse becomes an integral part of the analytic infrastructure in order to make meaningful sense of all the data.

We have a dedicated product engineering team that is responsible for data architecture. They are focused on continuously strengthening capabilities in: providing a 360-degree view of our customers, self-serve data solutions for business users (for simple analysis), productionizing modelling solutions, and ensuring continued compliance with accepted best practices for data governance.

Analytics India Magazine: What are the most significant challenges you face being at the forefront in analytics space?

Aldrin Luiz: From my perspective, there are three key challenges facing the analytics space:

1. The Right Talent: Given the exposure the field of analytics has received over the last few years, there is no dearth of operationally sound data science folks who are well qualified to execute complex analytics projects. However, the real challenge is finding individuals who bring with them the right balance of analytics skills coupled with core business domain knowledge i.e., the ability to look at and apply data from a business perspective. This is key to ensuring that the analytics solutions and recommendations we generate are actionable at the end of the day.
2. Agility: Today, analytics functions are structured in such a way that they operate as siloed delivery centres with little deep interaction with the end business user. If analytics is to meaningfully support the business in providing a strategic advantage, it needs to be more agile and in sync with the business during the decision making process, rather than being a function that serves to validate decisions or provide post hoc diagnostics.
3. Data Right Sizing: Too much data can take the focus away from actionability and into data paralysis! If employed effectively, data lakes and warehouses have the ability to store massive amounts of structured and unstructured data, and has even transformed the way we look at data holistically. Organisations need to ask themselves if they are really equipped to make sense of such large volumes of data and more importantly, are all these data points going to be utilised. Understanding what is critical and what needs to be measured in order to help with organisational decision making is crucial. A lot of time, effort and money is spent on collecting, storing and integrating data sources without first determining how the data will eventually be consumed and by whom.