Chapter 425: Absolute Overpowering

The three of them shared a joke, then got down to business—mainly discussing how to promote and release "Love Like a Bundle of Joy."

The reason Zheng Zhihao was called in was for ticket subsidies and big-data audience matters; he is the CEO of Rabbit Ticket, and this film is also being released through Rabbit Ticket.

It's essentially a joint release between Jade Rabbit and Rabbit Ticket.

Playing the ticket-subsidy game is now a very common tactic to draw in audiences; plenty of ticketing platforms on the market are pulling this same move.

And after a year of settling in and promotion, Rabbit Ticket has not only matured its team through the grind, but has also gone through several revisions, with transaction volume breaking through 3 billion.

Behind that transaction volume, Rabbit Ticket has collected a great deal of data on moviegoers—the age and gender of this group, what kind of demographic they belong to—and that's extremely useful.

This transaction volume isn't how many films were released, but the ticket-purchase transaction data of users on the platform; however, it doesn't make money—no service fee is charged.

Now is not yet the time to start charging a service fee.

Tickets for any film can be bought on it—recent ones like "The Monkey King," "From Vegas to Macau" can also be bought there, with no restrictions.

It's just a transaction platform; it has to be fair to a degree, and every film gets ticket subsidies—five or ten yuan, not much, but everyone gives them to draw traffic.

But whether to give large amounts depends on the platform, and whether to give splash-screen promotion is another matter.

Of course, a favored child definitely gets preferential treatment.

Now getting down to business, Fang Hong asked: "How much money did you burn last year in total?"

"600 million. It covered 85% of the country's cinemas, and the number of users covered reached 150 million." Zheng Zhihao rattled it off like a well-rehearsed list.

"Then you must have collected a lot of data—which groups like watching what, which age bracket has the largest moviegoing audience." Fang Hong said.

This was something he had proposed earliest on: build a database, gather all the box-office situations, audience numbers, viewing habits, and viewer demographics.

"We've been doing this all along. From our observations, 52% of moviegoers are post-90s, with post-80s and post-70s making up 40% and 8% respectively. Among them, underdog-rising inspirational films and fresh-and-tender, fresh-faced idol films are the most popular with the post-90s. Post-80s prefer nostalgia films, post-70s prefer family films."

Zheng Zhihao rattled it off like a well-rehearsed list, leaving Chen Zhixi listening in a daze.

The feeling was that others were still playing the most traditional promotion model—internet carpet-bombing, roadshows, running events—and had only just come into contact with new media, while General Manager Fang had already started playing big data.

He was already analyzing which users liked watching what, which demographic had the largest user count—clearly the post-90s demographic was the largest segment.

He was always walking ahead of everyone else.

"Here's what we'll do: share this data with Chang'e Technology and let them analyze user portraits again." Fang Hong said.

"Isn't that a bit off?" Zheng Zhihao said.

The data they had worked so hard to collect, sharing it so lightly with others—that didn't sit quite right.

"What's wrong with it? You share the data with them, and they do further analysis and processing for you, screen out high-quality users, and during promotion push precisely to fixed demographics—that saves on promotion costs and resources too." Fang Hong said.

Chang'e Technology's technical strength is definitely stronger than Rabbit Ticket's, and the number of users it reaches is also greater.

A few apps have daily active users in the tens of millions; one push from the backend, and tens of millions of people can see it at once, and it can be precisely pushed to fixed user groups.

Hitting a specific user group with focused reach.

The benefit of doing this is it avoids wasting resources and goes straight at the target demographic.

Zheng Zhihao fell silent, as if thinking.

"Let me give a very simple analogy. Say a user clicked on the 'Love Like a Bundle of Joy' promo on Bilibili, and also bought a movie ticket on Rabbit Ticket—then the system decides this user has some intention of seeing this film, and will push heavily to this user, one ad a day.

Another example: a user hasn't bought a movie ticket, but this user often watches Liu Tianxian news or film and TV on Bilibili and Chang'e Video—then we conclude she's a fan.

Isn't she a potential moviegoing audience? Then give this user a 19.9 deal to try the moviegoing experience. That pulls new users for Rabbit Ticket and also contributes a ticket sale—see the logic?

One more example: you just curiously watched the 'Love Like a Bundle of Joy' ad promo—that proves your intent to see this film isn't strong, basically a passerby; give you a 9.9 to try it out, how about that?

Doing it this way is basically promoting Rabbit Ticket, pulling new users for Rabbit Ticket, and letting you collect even more demographic data—do you think you lost out?"

Fang Hong's rapid-fire words left Zheng Zhihao unable to help falling into thought. It did seem to make sense—although the data was given away, Rabbit Ticket hadn't lost out either, and had quickly pulled in many new users.

Chen Zhixi was already starting to find it hard to accept—the concept was too far ahead, at least a full version ahead of the current era.

They're already playing big data—what do their competitors play with?

In his previous life, Maoyan had information barriers with the ByteDance system, and platforms like Bilibili and Tencent Video weren't willing to cooperate with Maoyan on any big-data stuff.

Only Alibaba was doing this, so although Alibaba's films were bad, they rarely lost money—it really knows what you like to watch, and it's analyzing what you like to watch.

Even super-bad films like "The Captain of China" and "The Bravest" could be pushed to one or two billion, even tens of billions at the box office—can you call that a coincidence?

Probably cooperating with Alibaba was Brother Xiaoming's finest hour; the films he starred in solo as lead actor had never in his life reached such high box office.

And Tencent was far behind in this area—not willing to analyze what content users like to watch; they only analyze whether you've topped up in their games, and why you haven't.

In this life, Fang Hong could integrate this whole area—Bilibili, Xiaohongshu, Chang'e Video, Today's Headlines, Rabbit Ticket—whether text-based or video-based, whatever you've clicked, whatever you've watched, all turned into big data.

Then push you to watch movies, watch TV dramas.

This can also assist the Recommendation Algorithm work at Chang'e Technology.

Anyway, Zheng Zhihao listened with quite some amazement, and asked: "It's still very hard to realize right now, isn't it?"

Analyzing hundreds of millions or even billions of people—the data volume is massive; whether in terms of technology or hardware, it can't be achieved in one step.

And right now many people have several accounts; the era of one phone number covering all accounts hasn't arrived. And collecting data is long-term work.

"At least having the concept is something—you can start with rough promotional pushes, having it is better than not." Fang Hong said.

A casual effort would already be more advanced than competitors.

This industry doesn't have this concept yet—probably only Alibaba has it.

"I'll go back and arrange the data sharing." Zheng Zhihao agreed to give his data to Chang'e Technology—it would be hugely beneficial for their promotion.

The previous promotion methods were too crude; this way you could directly target specific demographics.

"But ticket subsidies still have to be done—19.9 or 9.9, we need a plan, the subsidy has to be big. Last year you only burned 600 million, this year burn more, burn it all." Fang Hong said.

Previously they had raised 3 billion, so there should still be around 2 billion left; plus there are operating costs, administrative costs, etc.

Of course, releasing through Rabbit Ticket also earned some money—basically every Jade Rabbit film brought in tens of millions in fees.

In the future, exclusive releases would bring in even more.

"Fine!" Zheng Zhihao had no objection to this.

This year and next were originally the decisive years; there are too many ticketing platforms on the market now, and they need to be cleared out.

Fang Hong looked at Chen Zhixi and said: "The publicity plan is still on your side to handle. How to publicize, get the data from Tu Piaopiao."

There's nothing much to say about publicity — it's just about resonating with the audience and bombarding them with promotion.

"Understood." Chen Zhixi then asked: "Then how do we deal with the opponents?"

"There's no point in smearing those people. Who doesn't have a pile of dirt on them? They've all walked this path, yet they still stand firm and unshaken," Fang Hong said.

That's true enough — Fa Ge, Wang Jin, Yuzhou Dan, these Hong Kong film stars all have heaps of dirt on them, but they're still doing just fine, still have plenty of fans willing to pay up.

Splashing dirty water won't solve the problem.

That's just how this thing works. Liu Tianwang has such a great reputation, but the movies he makes just don't do well at the box office; meanwhile those with terrible reputations have great box office — what can you say about that?

Da Xiao Wang, Yu Fatty, the Principal — they've been smeared beyond recognition, yet their movies still make money.

It still comes down to the movie itself, still comes down to distribution and marketing, still comes down to capital and real strength.

"Do the publicity well. Where you need to buy out screenings, buy them out. Where you need to give rebates, give them. For this movie, you need to be prepared not to make money. The key is to crush the opponent's morale, crush their market value — that's the real point.

Once there are fewer investors, naturally there won't be capital chasing after them, and this market will be ours to call the shots. If you absolutely must splash dirty water, splash it on their movies," Fang Hong said.

This time he didn't plan to go after the Hong Kong film stars directly, but to destroy their value, to make them worthless on the market, to let people know they don't make money.

Of course, this can't be resolved in one or two rounds — it will take many confrontations.

Additionally, Liu Tianxian's value can be pushed up!

"I understand." Chen Zhixi knew what to do.

Now Yu Tu has money — throwing out a hundred million to splurge is no problem at all. Just consider Dad Where Are We Going as not having made money.

Big Data push promotion, plus Tu Piaopiao seat selection ticket subsidies, plus buying out screenings and giving rebates — eight-pronged attack like this, how would the opponent respond? Absolute strength and Big Data crushing.

Buying out screenings and giving rebates — Huayi has played this game before, going back and forth with Yu Tu.

But this time Yu Tu isn't holding back — it plans to crush straight through, to crush through even at a loss.

Buying out a screening is equivalent to renting a cinema — for example, renting out a certain cinema, and that cinema no longer sells tickets for other movies to the public; only specific groups of people or only a specific movie can be shown.

For example, if Yu Tu rents it out, that cinema can only show "Bundle of Love" — no other movies can be shown.

Of course, this might mean no audience — but it doesn't matter. If we don't watch, we don't let the opponent watch either.

And the price of buying out a screening is relatively fixed — renting out one auditorium costs about five thousand, two hours per show, so about thirty thousand a day. A thousand auditoriums would be thirty million.

And a thousand auditoriums is equivalent to one-eighteenth of the total.

China currently has just over ten thousand screens in total, and many of them are junk screens in places where nobody goes.

And five thousand is a very high price — some can be done for two or three thousand, and there's bulk discounts too.

So renting out a thousand auditoriums won't cost thirty million — that's just an overestimate.

And that's only one day's cost. So not many people can afford to play this game. Think about it — if you buy out all seven days of the Spring Festival? Several hundred million gone. Who can afford to play?

And you can't even buy out everything — no matter what, they still have room.

This method is also welcomed by the cinemas — they don't have to bear the risk of loss. Whether you lose or make money, it's on you. They earn pure profit — why wouldn't they be happy?

After the basic strategy was discussed, Chang'e Technology also received Tu Piaopiao's data information.

This is also beneficial for them — they can find ways to draw over these people who have bought movie tickets, and these people all have spending power.

They can analyze which demographics are the main consumer force for movies, and specifically push heavy traffic to these people. Additionally, they can analyze who loves watching this kind of romance film.

Pushing content to this demographic is beneficial.

Of course, the analysis is still quite crude, but that doesn't prevent this from being doable. Zhang Yiming has been working on the Recommendation Algorithm all along.

(End of this chapter)