Disrupting Advertising: 3 ways to take on Google & Facebook while they eat at TV’s slice of the pie

In 1995, newspapers accounted for a third of total advertising spending. That’s down to 12% today. The money went online.

During the same period, TV’s share of ad spending had been quite stable at around 40%. That’s about to change.

TV’s market share of ad spending is forecasted to shrink to the low 30’s by 2021. On one front, Netflix and Amazon allow us to watch shows and movies ads-free, whenever we want. On the other, Youtube and Facebook keep us entertained with novel content, especially when we’re on the move. Should this trend continue, it spells major revenue loss for the big six media companies. Their studios will continue to profit from original content, but lose control over how it is distributed.

In parallel, Google Search has become king of online advertising. It attracts a whopping 40% of all online ad revenue. Facebook follows behind with half of Google’s market share. The two tech giants have in effect created a duopoly, but their continued growth is anything but guaranteed.

On the search side, Google faces stiff competition from Amazon and Apple on voice search. Amazon’s success with Echo is forcing Google to play catch up. And the question of whether search advertising (Google’s bread and butter) has a role in the voice world remains unanswered.

Google’s dominance in search is also being challenged on the mobile front. As users jump right into Facebook App to connect with friends, Uber for a ride, Yelp to find a local business, or Amazon to find a product, they skip Google as the starting point. Already, it has been reported that a third of online users started their product searches on Amazon, compared to 13% who started from a search site.

Google’s strategic answer to these threats is a large investment in AI. As CEO Pichai writes in a letter to shareholders:

“A key driver behind all of this work has been our long-term investment in machine learning and AI. It’s what allows you to use your voice to search for information, to translate the web from one language to another, to filter the spam from your inbox, to search for “hugs” in your photos and actually pull up pictures of people hugging … to solve many of the problems we encounter in daily life.”

From an ad platform’s perspective, we do have to ask how finding answers more effectively with AI is going to help advertise. The less time we spend searching for things, the less time we are exposed to ads. In turn, Google’s AI efforts may actually reduce its amount of advertising real estate.

That’s a problem Facebook doesn’t have. Users flock to it to be entertained, to pass time. We already spend 50 minutes every day on Facebook’s platforms. That’s likely going to increase once virtual reality becomes mainstream and Oculus Rift finds its way to our living room.

Facebook’s position is challenged by a series of more focused social networks: Snapchat that’s winning the hearts of Generation Z; LinkedIn which is a leader in professional networking; and the dozens of chat apps including Kik, WeChat and Slack — each with a specific purpose and geographic reach.

While everyone competes for a piece of the advertising pie, it’s important to note that the pie hasn’t actually increased in size relative to GDP. Bloomberg reports that throughout the past century, ad spending has largely stayed between 1% and 2% of GDP. This means that once Google and Facebook finish stealing ad revenue from TV, the last stronghold of traditional media, their growth will largely follow GDP growth: 0–2% annually. Not the explosive growth investors are used to. That may raise tensions further among the two giants and lead to price wars.

This is all if the tech giants are able to stop the fast adoption of ad blockers. More than 25% of online users are already blocking ads. And if they do manage to stop this trend, they’ll also have to figure out how to respond to millennials’ ability to neglect ads altogether.

How to take on tech giants

The shift to online advertising and video streaming has not made the world perfect. There exist many problems that can be sources of new opportunities to disrupt the industry once again.

So what problems have been created by the shift to online advertising? And what problems remain unresolved? How could one disrupt Google, Facebook, Netflix and Amazon?

Here are three thoughts:

#1 | What am I searching for?

Google Search helps us find two things: Known knowns (e.g. the address of my favorite restaurant) and known unknowns (e.g. where I should go eat on my trip to Thailand). In both cases, we must know what question to ask.

What Google has yet to help people discover is unknown unknowns. Stuff we’re not actively looking for, that we are not even aware they exist, but that we absolutely need. Solutions to problems we don’t yet realize. For example, nobody knew they needed email for work in 1995.

Facebook is a little better equipped to deal with this issue than Google, as their ad platform allows businesses to target specific populations. However, what if a business’s target audience is wrong or incomplete? What if the business is unaware of which segment of population need their solution?

This is a major problem with innovations. Companies are often unsure of who exactly needs their product when they launch new products. One can resort to mass advertising, but that’s seriously expensive.

We need a better way to connect consumers with a problem they don’t realize to businesses with solutions that don’t have a clear target market.

#2 | What to watch next? What else should I buy?

We have an incredible amount of choice with Netflix and Amazon Video, yet we don’t know what to watch next after we finish a show. As result, we waste 18 minutes every day browsing and clicking our remote in an attempt to find something worthy. That’s more than the 10 minutes we used to waste changing TV channels.

Online retailers face a similar problem, in that they don’t know what else to offer shoppers besides what they came looking for. If someone’s shopping for a camera, what besides camera related items may entice them? Up to now, customers still make more Impulse buys in store than online.

Both problems can be partially attributed to the inefficacy of existing recommendation systems. These systems typically suggest recommendations based on collaborative filtering and/or content-based filtering. In other words, they recommend options that people like us have chosen before and/or options that share similar characteristics as our previous choices. Amazon’s “Customers have also bought” uses collaborative filtering, whereas Netflix’s “You may also like because you watched xyz” uses content-based filtering.

Yet recommendation systems have several shortfalls:

• They don’t inspire me to make impulse buys. When shopping in a physical store, my impulse buys are typically stuff totally unrelated to what I came to the store for. I once bought a T-Shirt while shopping for Diapers at Target. Online, recommendation engines only show me stuff related to what I searched for. If I’m shopping for diapers, it shows me more diapers or baby stuff. It’s unlikely to show me an electric drill on sale that I may want. Overall, I’m a much more calculated buyer online as it’s easy to compare prices, research alternative products, drop stuff from my cart (I don’t have to walk back to aisle 1), and make sure my order total didn’t surpass my budget.
• They don’t adapt to my present need. If you had access to my Netflix viewing history, you’ll notice I like dramas, comedies, action flicks, international titles from Korea, India, China… In turn, my recommendations are all over the place and unhelpful. What the system fails to acknowledge is my present mood and emotional need. How do I want to be entertained NOW. It tries to forecast a future decision by accounting for my past behavior, but fails to acknowledge my present state. Add this to the fact there’s two of us use the same Netflix account at home and suggesting the “right” choices becomes futile .
• They don’t help me explore new interests. Again, because recommendation engines use historical data, they trap us in our past preferences. It makes it difficult to evolve our interests and take our identity in new directions. For example, if I and people behaving like me have never watched any Korean TV dramas, a recommendation system will never suggest it, regardless of whether it may become a new passion.
• They don’t choose for me. The most frustrating shortcoming of recommendation systems is the fact they offer options rather than choose for us. Once we’ve finished a movie or added something to the cart, they force us to browse for something else. I hate browsing. It’s a waste of time. I expect any intelligent system to choose for me and save me from the hassle of browsing. If I wanted to browse, I would not need a recommendation engine. This is an area TV does better as there’s always something playing. It may not be the show that matches my exact desires, but the fact I’m really tired after a workday and don’t want to think, I’m thankful TV chose for me. It’s therefore not a surprise we spend less time changing channels on TV than browsing on Netflix.

There’s a tremendous opportunity to create a more effective recommendation system. Or dare I say choice system that entices us to make impulse buys, acknowledges our current needs, and most importantly, chooses for us. The fact we’re stuck on recommendation systems says a lot about the low confidence engineers and data scientists have in the options these systems suggest. They still need us to make a final call.

#3 | Why should I care about the ad?

People don’t trust ads, especially millennials. Advertisements fall under the category of annoying, deceitful and unwanted content, regardless of whether it is targeted or not.

For advertisers to attract eyeballs and convert impressions into sales, it’s time to give a reason for people to acknowledge them. It’s time for ads to provide value.

So far, ads have been extremely selfish: A one-way relationship where it’s all about advertisers. If someone clicks on an ad, Google definitely makes money, the advertiser or company behind the ad has a small chance of landing a sale, and the user very likely will waste a minute of their life.

The most trusted source of information remains recommendation from someone we know. Word of mouth. That’s not only because our friends and family know us best, but because we know they have our best intention at heart.

Ads don’t have our best intention at heart.

It doesn’t have to be this way. Advertising can create win-win scenarios where the user gains something of value too. For example, they can entertain us like the ad parodies from SNL, or educate us like Snapple caps attempt to do.

It’s time to design and deliver ads in a way that provides real value to the audience.

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