AI disruption won’t eliminate the human need for ads. The key question is whether digital media products can monetize with ads profitably?
A House of Brands refers to a business structure where a parent company owns multiple subsidiary brands, each operating independently and marketed under its own brand name. For example, Procter & Gamble owns Pampers, Duracell, Pringles, Tide, etc. More strikingly, Unilever owns four ice cream brands: Ben & Jerry’s, Magnum, Walls, Paddle Pop, etc.
When does this work: Each sub-brand can operate as an autonomous division with little to no coordination required with other sub-brands.
Why it matters: Operating a house of brand provides multiple advantages:
Digital media homepages are cluttered with widgets for various sections, leading to higher bounce rates and accidental clicks.
This difference places the cognitive load and choice fatigue on users.
In contrast, algorithmic platforms—social media, search engines, and OTT services—present users with a simple, sorted list of content to choose from.
Meanwhile, on algorithmic platforms, this burden is shifted to the recommender algorithms, making it easier for users to find what they want.
GIF Credits: Ralph Ammer
Format is the pre-defined technical structure in which bits are stored in software. For example, typically, we use human-readable formats like Google Sheets, MS Excel, PDFs, Google Docs, Websites, etc.
However, these file formats are human-readable formats and aren’t always ideal for use by machines.
In Google Sheets, you can do formatting here:
When doing data analysis, you want to strip away the formatting and use machine-readable formats like CSV, XML, JSON, etc.
Machine readable formats follow some form of pattern that algorithms can read quickly. For example, pipe-separated value (PSV) files split columns by | and each row is identified by new line character \n. CSVs separate columns by comma, SSVs separate columns by semicolon, etc.
Google Sheets stores formatting separately from information. Similarly, the advent of Generative AI will force information products (Search Products, Social Media, etc.) to separate the core information value and the form, format, style, and tone it is presented in. Without this, we are in for a flood of similar content that is written just slightly different.
Historically, modern CMSes like Washington Post’s Arc CMS went headless and started storing the story and its presentation (HTML tags) separately. We’ll now have to extend this further.
To create value, make something people want but cannot get easily elsewhere.
You can escape being commoditized if you’ve competitive differentiation.
Why it matters: Differentiation allows you capture value for yourself without worrying about others copying you.
Types: Defensible differentiations are also called moats. There are different types of moats.
Complexity is the amount of things you’ve to keep in mind before/when doing something. There are two types of complexity: accidental complexity and essential complexity. It is the job of the product organization to drop complexity.
Why it matters: As a system grows, it becomes complex. You should care about it because Complexity slows down execution. Hence, ruthlessly identify and shed as much accidental complexity as possible.
How to handle it
Users are able to use products for free because they give their time and attention which is then monetized through advertisements.
Companies invest in advertising for:
Companies will pay a premium for:
Indirect programmatic advertisement is bad for business and users. Yet, most companies adopt it because it is a relatively easy plug and play revenue channel.
Print and TV Advertisements Earn More revenue Than Digital.
The pivot to privacy brings in new opportunities!
Each page template can hold multiple ads at different positions. Thus, each page template’s monetization value from programmatic ads is different.
Those of you familiar with survey design will find these familiar! That’s because the same rules of good survey design apply to customer interviews as well. There is a great detailed breakdown of survey design available from the Pew Research Center.
Even after doing these things it might seem difficult to turn qualitative feedback into data driven decisions, so tomorrow we’ll cover more sophisticated models of processing feedback (known as Customer Satisfaction models). They will help you turn your customer interviews into a highly data driven exercise!
Questionnaire design – Pew Research Center Methods | Pew Research Center (archive.org)
“Does it work? Let’s try it, and if it does work, fine, let’s continue it. If it doesn’t work, toss it out, try another one.”
Lee Kwan Yew
Experiment-driven development entails running tiny tests to evaluate options/ideas that you’ve in an iterative and structured fashion to incrementally achieve results.
Phrase all ideas as hypothesis. “What if we…”
Short Shelf-Life content is content that experiences an immediate surge in interest, which then quickly declines. Most news content falls in this category because it often reports on events—breaking news, summits, natural disasters, ‘He said She said’, deaths, etc.
Below is Google Trend on the keyword Bipin Rawat.
Long tail stories maintain consistent levels of traffic over extended periods because of their enduring relevance.
For every query, Google Trends returns data that is normalized in relation to a peak (100). Here’s the response when you search for the topic Yogi Adityanath.
Lets run a similar query for General Bipin Rawat
This makes it impossible to compare these two terms. Hence, we introduce a neutral term – say “Google News”. And now we get these results.
https://trends.google.com/trends/explore?date=2021-12-01%202021-12-31&geo=IN&q=google%20news,%2Fm%2F0h4cxd
How to normalize? We need to make the traffic data from Google Trends comparable between Google News, Yogi Adityanath, and General Bipin Rawat.
Response from the query for General Bipin Rawat on December 8, 2021.
https://trends.google.com/trends/explore?date=2021-12-01%202021-12-31&geo=IN&q=google%20news,%2Fm%2F09k76ff
Response from the query for Yogi Adityanath on December 8, 2021.
Normalized result using min-max scalar.
The business case for launching Apps
Do competitor research with AppAnnie
Paid or Acquired Traffic: As of 2020 in India, it typically costs Rs. 50 to acquire mobile app downloads. For these users, you’ve to be confident that the product is strong enough to grow Sessions Per User so they stick around and give you enough revenue in the long run. Another way to track this is to look out for Uninstall to Install ratio.
It seems most media businesses, at least in India, have not built Profitable mobile apps.
Habit-forming products have a clear trigger-action-reward.
Why it matters:
Will customers miss you if you are gone tomorrow?
You’ll not find Supreme’s goods on Amazon or in another store.
Trigger: Like clockwork, every Thursday at 11:00 am during the spring and fall season, Supreme drops a limited collection of merchandise on its website. This fixed time and location reinforce the habit. Customers know when to expect new merchandise.
Action: Hence, they keep coming back to the Supreme website every week. It also creates excitement, rumors, and conversations within the community.
Reward: Find out what’s new.
Print newspapers have always had the back-of-the-page infotainment section page. This page typically includes comic strips, brainteasers, crosswords, horoscope, events listing. Traditionally, it has been one of the pages which has had high engagement and time-spent with newspaper readers.
Trigger: Before cell phones went mainstream, it was common to see people interacting with this page during their time off. While Page One was the morning trigger, the funny pages with cartoons, games and comic strips was the reason you picked up the paper later in the day or carried it around with you. It was also one of the early use-cases for young readers — many began their newspaper reading with the comic pages.
Action: Read or play for entertainment.
Reward: On reading this page, the reader got clear well-established rewards:
Everything about Axios was habit-forming:
What do journalistic investigation, dating, sales, and hiring have in common? Each of them are funnels towards insight, partner, customer, and employee respectively. This same concept can be expanded to value generating outcomes like Conversion, Retention, Ad Click, etc.
A funnel is a series of events or actions that customers need to take leading up to a value generating outcome. You start broadly (Top of the Funnel) and then increasingly narrow down into what you want.
Why it matters: A funnel models reality and exposes steps in the funnel that need to be optimized.
Actively use A/B Testing or Multi-armed Bandit to optimize your funnels:
Build and maintain an Audience Funnel
Onboarding helps orchestrate evolving users from one segment to another.
Why it matters: Like all people, customers change over time and go through a Customer Lifecycle. The more a customer learns about your product or service the better they will make use of it and the more advanced their usage will become. Onboarding helps them evolve.
Setup: On sign up or purchase, thank them immediately and offer help to engage further with your product.
Auto-responder campaign: You also want to run a Newsletters campaign that introduces the user to your mission, introduces your staff, serve them your most popular content, and ask them questions about their motives and interests. This could be as simple as asking them about their favorite local restaurant. The goal is to kickstart a two-way communication.
On-platform nudge users to towards specific actions. For example, ask them to leave their first comment, poll their opinion about topics, after a story ask them what else they they would like us to cover or share tips on what they could have done better. Some platforms like Stack Overflow offer points to encourage usage.
Risk: Beyond this point, you cannot keep bombard or overload the user with everything in one go. Instead, your must progressively narrow down to specific personalized actions, features and topics.
How long: You could start off with a fixed period onboarding but ideally you should go on until user graduates to desired engagement level on the Customer Lifecycle.