Retail Is A Sign That The Slowdown In The US Economy Is "Normal".

The US retail sales figures released in September on Wednesday (October 15th) once again show that the US is in an economic slowdown.

The US core retail sales monthly rate in September was -0.2%, far below the generally expected +0.4%.

In September, the retail sales rate fell by 0.3% (-0.1%).

The data is now milder after a long period of strong retail sales data.

This is a normal pattern in American style.

However, the data sparked worries about the US economy, worried that the US economy slowed down more than expected, and the US economic growth was lagging behind other economies in the world, rather than the rest of the world catching up with the US.

Because the United States has been seen as the last pillar of the global economy, this data has also increased the market's worries about the global economy.

Weak retail sales data in the United States could also plate into further decline in ISM data in the coming months.

ISM data in the US reached a very high level in the summer, but it declined for the first time in September.

The ISM index is likely to fall further, supported by the New York fed manufacturing index, which dropped sharply to 6.17 in October, with a previous value of 27.54 and a forecast value of 20.5.

(Danske bank) the bank said: "we have stressed for some time that the high level of surprise index in the US should be reduced, considering the very high level of the US economy in the summer.

The slowdown in the US economy is no longer natural.

But, as we have always mentioned, when the US economy hits "weakness", especially when other economies in the world seem to be weakening, this raises market concerns about the global economy.

Looking ahead, projected us

It will further slow down and the surprise index will continue to slide.

However, the sharp decline in oil prices and the overall good fundamentals of the US have made the outlook for the medium term economic development of the US remain promising.

Even now, retail sales data in the US have increased the willingness of the market to avoid risks and the downward pressure on bond yields.

This is likely to continue for the rest of the year.

Retail sales data show that the FED should now put aside the discussion of interest rate hike, focusing on whether to increase bond purchases.

"We do not expect the US economy to be weak enough to make the Fed go this way," the bank said.

But this may become a topic of discussion in the market for some time.

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From the development and practice of Japanese retail enterprises, we can get this inspiration:

(1) the decision maker of the business district is no longer a retailer, but a customer.

In the past, business circle was set up by retailers themselves, looking at customers from the perspective of retailers; but now, business circle is determined by consumers according to their location, and is a moving business circle.

Therefore, retail stores can be seen by customers.

If there is no retail outlet in the consumer's "business circle", then the retail store will be eliminated.

That's why 60% of Japanese retailers want to do O2O.

(2) marketing with data.

We should use big data analysis to find new demand and then carry out precision marketing.

In this respect, Japan has an interesting case.

Before making any data analysis, Japanese retailers only know that there are men who buy bras, but they do not know that men are buying bras for themselves, thinking they are buying for their girlfriends or wives.

But data analysis revealed that 30% of the male customers who bought bras bought them for themselves, the youngest more than 20 years old and the oldest 70 years old.

They feel embarrassed to go to the physical store to buy, but prefer to buy it online.

Through data analysis, the big market has been discovered, and retailers can make targeted development accordingly.

Obviously, if there is no data analysis, this is impossible.

Looking ahead, big data analysis is the key.

In the past, many enterprises with data were not successful. The main reason is that retail enterprises do not understand their KPI well enough, so the utilization of big data is not enough.

Therefore, we must understand what data we need, otherwise, even if we have big data, we will still fail.