Yale Marketing Master: Tell You The Future Ten Big Data Will Crack The Ultimate Secret Of Consumers.

Yale Marketing Master: tell you the future ten big data will crack the ultimate secret of consumers.

Dole, Professor of management at Yale University, shared his 10 anticipation of consumer behavior in the digital age.

He thinks big data will conquer a big problem of brand marketing: why do consumers buy?

Levi Doll (RaviDhar), a professor of management at Yale University and director of Yale consumer insight center, is an authoritative expert in the field of brand marketing strategy, and also a leader in introducing psychology and behavioral economics into consumer decision research.

He currently teaches behavioral economics courses at Yale Beijing center two times a year.

During his last lecture in China, FT's Chinese net interviewed him exclusively, and asked him to share 10 predictions on brand and consumer behavior in the era of digital marketing.

The following is an interview with the editor.

1) the social media age will witness the rise of small brands

The emergence of social media has greatly increased the importance of word of mouth to the brand.

When people shop on Amazon, they will see other users' comments on the product, because they believe that the product information provided by the company is not necessarily true.

This is a growing challenge for brands, but it brings opportunities to small brands.

In the past, brands usually rely on scale. But now, if a small brand has a good reputation, even if its customers are very small, it can stand out on the Internet as long as it is loyal to it.

Our survey also found that overall brand growth has leveled off, but small brand growth is accelerating.

This is true in many industries such as clothing, food, beer and so on.

2) the traditional big brand strategy will be more vulnerable.

A few months ago, a new advertisement, which was produced by Pepsi and spent a lot of money, invited the famous model KendallJenner to stir up criticism on social networks.

It is thought that it consumed the "Black LivesMatter" civil rights movement. Pepsi Cola had to rush off the shelves and make public apologies in less than a day.

Such a heavily advertised advertisement must have been examined and approved in a number of ways, and it must have been tested in a small range. But why hasn't it been found? This is a recent case showing how turbulent the negative emotions of a brand can be in social media.

It may even be possible that at the very beginning, online feedback on an advertisement is positive, but with some people pointing out problems, the mood can suddenly turn into a massive reversal.

Therefore, social media has brought great challenges to the traditional advertising mode.

When your scale is so large, how can you turn around in a day? How much loss will it take? Many big brands and advertising industry have played this way very well, and now it's time to think again.

3) losers in the online shopping era: chewing gum, soda and clothing on impulse consumption.

Online shopping will greatly reduce the traditional impulse consumption under the line.

In the past, many of the sales of soda, chewing gum and even clothing were driven by impulse spending.

No one will go to the supermarket to buy gum, so most of the chewing gum shelves are placed beside the supermarket cashier. When people check out, they can buy them readily.

If the sale of a product 70% is based on such impulsive consumption, and people now move the shopping to the Internet, what about this product? This is not a zero sum game.

Although sales channels have increased, the reduction in impulse consumption may add up to all channel sales, which is still only 90% of the original sales.

I've talked to many of these companies. Many of them haven't realized this yet, but I think they will feel the impact in two or three years.

4) the winner of the online shopping era: "instant gratification" service such as taxi and ordering.

The emergence of various mobile terminals app makes it easy to call cars, ordering meals and other services.

I used to order a meal in the evening, maybe I had to make a plan in the early morning, call the restaurant several hours earlier, and now order the order with the order software, and it will be delivered in half an hour.

My house is only half a mile away from the University. I used to walk to and from work, but since I had Uber, I often walked a few steps, and then called for a taxi.

Now sharing bicycles all over Beijing, the original pedestrian jumped off in a car and rode away.

The result of shopping at anytime and anywhere is that not only the user base has increased, but also the frequency of each user has increased, thus increasing the overall demand.

5) no cash payment may make you overspend.

Many surveys have shown that paying cash is more painful than credit card spending.

When you travel abroad and use foreign bills, you can easily spend more because you feel that they are not like real banknotes.

Now, mobile payment doesn't need to be brushed. You can't feel the change of money, which will make people spend more.

No cash payment will also change people's consumption experience, and to some extent, make the two sides feel more equal.

For example, I used to take a taxi in the past. If the driver is friendly to me, I don't know whether he is really friendly or else he has other plans. For example, I hope I can tip more at last.

Now I use Uber to call a car. Both the driver and I know that there will be no cash changing hands later. I can not change the fare, which will weaken the relationship between employment and employment.

The opposite of cashless is that it will make consumers lose control of the trading process and are more likely to overspend.

6) virtual reality and machine learning will make online shopping omnipotent.

With the help of Amazon's Alexa and Google's Siri technology, voice shopping (voice activatedcommerce) is booming, and consumers can place orders when speaking to mobile phones.

And the process is becoming intelligent.

For example, if you want to buy a milkshake, you don't need to say "I want a big strawberry milkshake", but just say "buy me a milkshake".

The machine will analyze your brand, taste and food intake according to your purchase records, and help you place your order.

The popularity of the Internet of things enables you to have a comprehensive understanding of a product.

For example, when you buy apples on the Internet, you can see what areas they grow in China, what kind of trees they grow and what kind of farmers they grow.

More and more virtual reality technologies are springing up. You can smell or even touch online shopping in the future, let alone those fitting software.

This will bring more impact to offline stores. If you can try on your clothes at home and try how long you want to try, who else would like to try it in a physical store?

7) several beasts will monopolize the background of e-commerce in the world.

All retailers are moving online, but building backstage, doing big data and developing those technologies just now require billions of dollars of technology investment.

In addition to several giants, how many small and medium-sized retailers can do this? Therefore, my prediction is that there will soon be two giant enterprises, such as Amazon and Alibaba, and perhaps WAL-MART, which will provide backends for all retailers, mainly referring to supply chain, logistics and data services.

New types of monopolies are emerging.

That's why when Amazon announced that it wanted to buy WholeFoods, an American organic retail supermarket, almost all retailers' shares fell, because another big piece of data was acquired by Amazon.

This is a problem that regulators need to think about.

8) the next step in big data: no longer care what you buy, but care about why you buy it.

Consumer data have been in existence for many years, and we haven't, and now we have "footprints" of the so-called customers: what products have you considered before placing the order? How long have you decided? Do you want to wait for the discount? What else do you have in the shopping cart? At present, the data research on customers basically stays at four W: who (who), when (when), where (where), and what to buy (what), but this is too basic.

The most valuable information is in the fifth W: why (why).

Big data in the future will be based on your purchase records, your schedule, your habits and customs, and connect dots to figure out why.

For example, Mary recently bought an expensive skirt. Data analysis showed that she had attended a very important meeting.

The next time she has meetings and parties on the agenda, businesses will be able to push the top dress information to her.

This can help brands push accurate advertising information to individuals and greatly improve the efficiency of marketing expenditures.

There is an old saying in advertising industry that half of marketing expenses are wasted and do not know half of them.

The current global advertising market, including online and offline, is 300 billion to 400 billion US dollars. As long as we increase efficiency by 10%, we can save huge sums of money for brands.

9) too much data can not replace human beings.

To get the "why" above, you need both computing tools and people who have insight into brands and markets.

Big data is bottom-up, but you need someone to look at these data from top to bottom. AI does not have such a perspective.

Some companies will say that we have 200 computing engineers, but they do not necessarily know how to view data.

I like to use the following analogy: someone found the key under the street lamp and asked where he lost his keys. He said, he was lying across the street.

Why do we look for it on this side? He said, because there's plenty of light here.

If engineers do not know the brand and the market, it is like the person who finds the key under the street lamp.

10) privacy regulation is a difficult problem.

Privacy is the most concerned problem in the digital age, but regulation will be a difficult problem, because you ask ten people what is privacy and get ten different answers.

For example, Google engineers discovered that when a person drives to the airport to catch a plane, and if the road is blocked, he will welcome this reminder if his map software reminds him to take another more accessible route.

But if this person goes to a place he does not want his wife or girlfriend to know, then if the map reminds him of the same situation, he may be scared to death.

For example, I asked students, if there is a travel agency to push holiday information to you, accept it? They say yes.

But if a pharmaceutical factory finds that you have AIDS, will you push AIDS drugs? They say they can't accept it.

Some people are willing to tell others that they have depression, and some people do not want to.

So privacy is contextual.

How can a manufacturer know what kind of situation you are? Even consumers sometimes do not know.

Because it is too difficult to define, regulation will test the wisdom of regulators and the industry.