The COVID-19 pandemic of the past two years has brought many changes to news publishers. These have included both positives as well as challenges, Jagran New Media (JNM) Chief Revenue Officer Gaurav Arora told INMA members during a Webinar on Thursday.

“Most content publishers have built a very healthy user base — but monetisation has been a challenge,” he said. “It has grown, but it has obviously not grown at the pace we wanted it to.”

Marketers have been cautious in their media-buying approach throughout the pandemic, and new ways of doing business have evolved in the news media industry. Some of the major shifts have been:

• Digital consumption has seen a huge increase in user base.

• The virtual world has expanded, with more online shopping, events, entertainment, and payments.

• The work-from-home culture has grown and work hours extended for many.

Sales and monetisation has not kept up with the increased digital consumption in many cases, Arora said. This has put publishers in the position of making one of two choices:

• Wait and watch: Stay in the market and allow the market to drive organic revenues.

• Progressive approach: Strategise new ways to do business, evolve strategies, and start new conversations, both internal and external.

Jagran chose the progressive path and began doing new things the team had never done before. Arora explained in-depth to INMA members what that entailed and how JNM has used data to to maximise page yield, new clients, optimising available inventory, eCPMs, and viewability.

“We were always data savvy, but we started to deep dive much more once we were in that situation,” he said.

Why data is important

JNM aspires to be the No. 1 vernacular publisher in the Hindi Heartland of India, driven by data-based journalism and built on a strong tech foundation. 

The revenue stream is driven largely by display advertising, which makes up 64%. Another 14% of revenue comes from branded content, and 21% from content syndication — only 1% of which is from subscriptions. The bottom line is that 78% of JNM’s revenue comes from some form of advertising.

“Hence, the role of data is extremely critical in sustaining and growing this,” Arora said.

Understanding the buyer’s mindset

This is an important part of the ad sales process for brand campaigns such as what JNM does, Arora said. He outlined the top five parameters in a buying decision:

• Brand safety.

• Campaign viewability.

• Reach.

• ROI.

• Spends.

“The first four of these are directly relatable to spends,” he said. “The brands also engage with you when you get them new users, new markets, when you have credibility.”

Other considerations include scalability, recognition, multi-platform capability, and audience. Factors that impact direct and indirect monetisation include:

• Reach and site engagement.

• Considerable impression volume.

• Viewability of impressions.

• Audience buckets.

• Performing placements.

• Reducing unfilled inventory.

• Platform eCPM.

• Optimising discrepancy (inventory vs. page views).

• Competition between network partners.

In the JNM sales process, data is core, Arora said: “Think of it like this: While you are prospecting, you are looking at some data. While you are planning, you are looking at data. Where you are strategising, there is data at the core. Data analytics is very important.”

The data at the core of the JNM strategy includes audience and advertiser intelligence.

Data intelligence

Arora shared a list of things that are important to track:

• Impressions.

• Viewability.

• Platform eCPM.

• Audience affinity.

• Ad unit performance.

• Market MIS.

• Keywords.

• New business development.

Some of the sources to collect and track this data include ComScore, Google Ad Manager, Google Analytics, Similar Web, Data Studio Dashboard, CrowdTangle, and Piano.

 JNM uses these tools to track and analyse ad inventory data in real-time. This is broken down into direct, ADx, and network revenue. “I can see the actual CPM on each of these line items,” Arora said.

“Another report we look at is the real-time advertiser report,” he said. “I see what is the revenue with my top 10 or top 15 advertisers. I can see the change compared to last month, I can see the CPMs in which they’re operating, and I also get the same report compared to same time last year.”

His team also analyses data for inventory segmentation, which segments premium versus non-premium inventory across categories, using the Big Data Custom Dashboard. “When I have these numbers with me, I can base my direct sales pitches on the rate which can be the benchmark taken out from this report.”

This dashboard also allows JNM to collect leads in an ADx report, giving them the ability to build sales funnels using the data. “This works like a working client list for me,” Arora said. “This is where my direct sales team will go out and talk with these advertisers that are already buying on open exchange, and there are many more benefits to buying directly.”

He also keeps an eye on impression discrepancies, monitoring the pageviews on the global ad manager, and comparing them with ad requests. A discrepancy between +10% to -20% is considered normal, and anything beyond that considered an anomaly. This is investigated immediately and resolved by the adtech team.

“We want to look at why the page view is there but the impression is not being counted. This helps me to investigate any leak that could have happened and loss of revenue.”

ComScore allows the team to analyse data for audience affinity and is used as an evaluation of the demographics as well. Similar Web allows them to analyse and understand user patterns, demographics, and audience interest overlaps. They also use Similar Web to collect leads for building the sales funnel.

“It is endless what you can get from these,” Arora said. “But it has to be played with to see what is the data you can use to your advantage.”

When it comes to content marketing, there are other data analysis tools that provide a roadmap for new clients and new ad formats, measuring success, and influencer management. There are a number of different tools they use for this.

“All of this, when you share it with your clients, gives your pitches and sales mode credibility,” Arora said.

Pricing strategy is also determined through data analytics. He explained that the JNM pricing strategy is primarily categorised on the following aspects:

• Property/genre: Jagran.com, Jagranjosh.com, Onlymyhealth.com, and Herzindagi.com.

• Platform: desktop, mWeb, AMP, apps, and PWA.

• Geography: India and outside India.

• Ad positioning and size: ATF/BTF, premium or standard placements, ad sizes.

This is all analysed to create a win-win situation for both the publisher and the advertiser.

Tools to create competition

“Automatic buying works best if there is competition,” Arora explained. “Header bidding is one easy solution. It works great. We’ve seen a swing of 20% to 25% using heading bidder implementation across our sites.”

This allows for multiple target audiences and increased page yields. JNM has experienced a higher fill rate, above 90%. Arora said this method works on audience segments as well.

Communication should also be data-based, he added: “When we talk to a client, we obviously ask them a lot of data-based questions. We talk to them about audience affinity that we can provide them.”

They also discuss why the client should buy directly and what makes Jagran sites safe for their brand. They explain why high viewability with Jagran leads to better OTS and performance.

“Brand safety is very important,” Arora said. “That is a question that is best answered with data.”

Today, Jagran New Media has close to 105,000,000 users and is growing — however, Arora believes the journey should continue.

“We are very proud of this, and still having massive growth in terms of users,” he said. “Now we are hoping to catch up on the monetisation part.”

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .