Directory of Major Malls
Directory of Major Malls

Retail Forecasting: Consumer Confidence is Rising, But Should Retailers Expect Higher Sales?

Retail Forecasting: Consumer Confidence is Rising, But Should Retailers Expect Higher SalesIn February 2019, U.S. consumers were feeling more confident about the economy than in recent months. The Conference Board’s consumer confidence index rose to 131.4 in February, up from 121.7 in January. February marked the first increase in confidence in 3 months as stock market volatility decreased and the partial government shutdown ended.

By all other measures, consumers seem optimistic about the direction of the economy. The present situation index is up, the expectations index is up, and the percentage of consumers expecting business conditions will improve is up.

Typically, consumer confidence is directly correlated with higher levels of consumer spending, or at least that’s the theory behind the measurement and why it’s revered. In the retail industry, consumer confidence levels are closely watched, as any rise in spending is a boon for the industry. But just because consumer confidence is rising, should retailers expect higher sales?

How Retailers Should Understand Rising Consumer Confidence Levels in Terms of Sales Forecasting

The consumer confidence index is a relatively reliable measure for predicting consumer spending levels, but it’s far from perfect and many assumptions have to be made for retailers to think higher confidence will translate directly into higher sales.

One reason that consumer confidence levels don’t tell the whole story is because, in reality, the “average consumer” doesn’t really exist. The wide-ranging demographics of American consumers, as well as the incredible diversity of retail products sold, makes the consumer confidence metric a very broad determination to begin with. When confidence is high, this indication may not apply equally to all portions of the retail sector.

Further, consumer confidence measurements don’t derive their data from economic performance. The most recent example may be the Brexit referendum. After Britain voted to leave the EU, consumer confidence levels plummeted. In retrospect, however, economic performance and spending remained consistent. Shocking events such as this tend to impact confidence indices, but don’t necessarily reflect expected economic outcomes.

Most importantly, consumer confidence levels don’t give any indication to actual spending potential of consumers, it’s merely a measurement of their confidence in the economy. While February saw this confidence increase, actual consumer spending is still slowly recovering from the Great Recession.

School loans have risen to their highest levels in history, and along with auto loans, consumers have been saddled with debt. Rising income inequality, outsourcing of jobs, and stagnant wages have left many consumers with less budget for discretionary spending. Consumer confidence may rise in the short-term because of a perceived improvement in the economy but it doesn’t necessarily account for the kinds of long-term trends that present obstacles to higher spending.

Consumer confidence measurements have their value, but it’s a very broad measurement that cannot quite be applied to the prospects of individual retailers. For retailers to predict their sales volumes, far more context is needed.

Retail Forecasting: Consumer Confidence is Rising, But Should Retailers Expect Higher SalesHistorical Retail Data Offers Critical Context for Sales Forecasting

Historical retail data offers more concrete insight than the short-term measurement of consumer confidence, which are based off surveys and opinions. Using historical retail data, retailers can create more accurate sales forecasts and predictive modeling, even on a granular scale.

Historical retail data can be used to analyze metro areas and determine the fluctuating levels of retail saturation through the years, as well as the mix of tenants and how they change over time. This information could then be used to make accurate predictions of retail activity in a given area for nearly any retail vertical.

When considering the potential use of historical retail data on a small and more relevant scale, even for trend tracking a single location, some options include:

  • Understanding how many major anchor stores a particular market has lost over the years
  • Tracking redevelopments of a retail location and how this affected the success of a retail center
  • Analyzing retail company activity over a span of many years
  • Identifying historical retail development trends in a geographic area
  • Tracking economic activity in a geographic area
  • Amassing data for employment changes, transportation changes, and more

A wealth of data can be collected with historical information on a much more granular level, even for individual retail locations or geographic areas. Consumer confidence measurements, for example, would never be able to describe what happens to an area when a new Amazon distribution facility opens up – if housing demand increases, if population increases, or if demand for certain products increases with more consumers in the area.

The retail data examples above can empower retailers to navigate a changing market with greater agility. Highly specific data affords retailers a more detailed yet holistic view of the retail landscape.

Historical retail data reveals an entirely different view of what’s happening in key markets when compared to broad and generalized confidence measures. With more reliable data, retailers can more reliably forecast sales and predict industry trends. 

Retailers should still be mindful of consumer confidence levels – they have their place as a general indicator of consumer spending. Retailers should also be excited by the prospect of rising consumer confidence, because at the most general level, higher confidence typically translates into higher retail spending.

However, it’s wise to not put too much stock in consumer confidence levels. There are problems that may arise in the calculation of these indices and they lack detail.

For accurate sales forecasts, more context is needed. Historical retail data, from the right retail data provider, gives retailers exactly the context they need.

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