Economic data paints the picture of the current state of the economy, which of course, informs business strategy decisions every day. At the most basic level, if the economy is good, brands generally lean into quality messaging. If the economy is down — or perhaps even experiencing high inflation — brands tend to push value and savings messages. Retailers may even prioritize store or discount brands and reduce inventory for luxury brands they keep on shelves.
Applying knowledge of the economic environment to decision-making is nothing new.
Unfortunately, most brands employ only the highest level of information. For example: “At the national level, is the economy good or bad?” That broad and limited view of the economy can only impact decision-making in an anecdotal way, rather than an actionable one.
70% of consumers in our recent survey stated that they were buying lower-priced brands as a result of recent inflation. 68% stated that they were dining out less often.
Localized economic data is an under-utilized secret weapon.
Even when the national economy isn’t dominating the headlines, local economies still experience fluctuations.
Example: When a military base closes, that local economy goes through an adjustment period as home prices and employment rates settle. That change has a major impact on how those local consumers and business owners feel about the economy, even if the national economy is unchanged.
National brands could adjust not only messaging but also inventory and trade spend based on this local economic data, and at scale, by accessing the right dataset. This includes population growth, income levels, employment rates, and industry-specific data.
By analyzing this data, businesses can also assess marketing potential, identify target customer segments, and decide about market entry, product releases, expansion, or diversification.
Localized economic research data directly helps determine where to invest in marketing, sales efforts, distribution channels, and infrastructure.
“Our team makes ‘real-time’ adjustments to our PeopleCore variables based on current, real economic trends. It seems obvious, and that it’s likely a common tactic in data creation, but it’s not. This is just one of the many tools we use to bring common sense into creating data products.”
– Gregg Weldon, Chief Data Scientist AnalyticsIQ
Applying Economic Data is Standard Practice
Unfortunately, many brands are not even applying high-level economic data to models, let alone localized economic data.
This may be due, in part, to a perception that data of this level is only available or actionable for large data science-heavy organizations. Mid-sized brands with limited data resources in-house may feel that economic data is a luxury (ironic), so do not even explore the possibility. But similar to other marketing tactics, smaller organizations can look to super-size brands for inspiration on how to adapt and grow into more sophisticated techniques.
In one example of how the economy impacts performance, Walmart beat Wall Street’s estimate of $141.7 billion by over $10 billion. As the effects of inflation due to Covid-19 related economic inflation and supply chain issues lingered, higher-income households and younger shoppers are bargain shopping at the big box retail. This has also resulted in gaining market share in their grocery category.
“The persistently high rates of inflation in these categories, lasting for such a long period, are weighing on some of the families we serve.”
– Dan McMillon, Walmart CEO
The acquisition of higher-income shoppers at Walmart shows a clear opportunity for brands willing to examine their economic strategy. By understanding economic data, businesses can capitalize on economic shifts that could drive increased market share and consumer confidence.
Discretionary Spending Choices Impacted by Economic Trends
Industries that sell products or services that may be considered discretionary — both for individuals or businesses — have historically been more significantly impacted during economic downturns.
- Retail and Consumer Goods
- Travel and Tourism
- Entertainment (EX: Movies or casinos)
- Personal Service Providers (EX: Nail Salons)
- Real Estate
During times of higher inflation rates, men look to change the ways they invest. Women tend to cut costs across categories like personal products and cancel subscriptions previously held.
The Do’s and Don’ts When Applying Economic Data
DO Ensure the data points feeding your models take localized economic data into consideration. For example, to increase accuracy, household and personal income and overall wealth data must include economic data sources.
DON’T use raw economic data directly in your models due to the volatile nature of the data. It is based on the economy, after all!
DO use economic data to better train your models, applying greater weight to specific variables to increase performance.
DON’T get in over your head. If you do not have a large-scale data science organization, don’t attempt to directly apply economic data to your segmentation. Instead, work with your data provider to ensure economic data is effectively applied at the source.
Practical Use Cases for Localized Economic Data in Models
Now that you know how to surgically apply economic data to your strategy for a competitive edge, here are some use cases that will be impacted by it.
Audiences or segments based on standard data offerings are valuable. However, as the industry becomes more data savvy, the stakes are rising. Simply creating a best-in-class model based on simple demographic and first-party data alone is no longer a competitive advantage. Just a way to stay on par.
Understanding the purchasing power of consumers on more granular levels allows for a strategy in line with pricing sensitivities. Without this information, brands may price themselves out of consideration or fail to maximize their yield.
Trade Spend Optimization
Manufacturers and retailers should be high-volume consumers of localized economic data. This would help them both have the right products on the shelf to maximize sell-through and ensure trade dollars are spent effectively in the markets where they will have the most impact.
For rapidly expanding brands with a physical presence using localized economic data is a must. It will help them effectively select new locations, determine locations that will be closed, or select where to allocate renovation and store modernization budgets.
More Accurate Forecasting
A greater understanding of the possible volume sales for certain SKUs will help finance leaders better predict revenue and goals for the business lines they support.
How is localized economic data different from national data?
While local and national economies can often appear similar, they co-exist independently for several reasons.
Different regions often have distinct industrial production specializations and concentrations.
Common examples in the United States are the auto industry in Detroit, tourism in Florida, and agriculture in the Midwest.
While the national economy might have a different industry mix, variations in composition at the local level can impact employment levels and overall economic performance.
Local economies are also driven by access to natural resources. A region rich in natural resources like oil and minerals will experience vastly different economic dynamics compared to regions without those resources.
The presence of major universities typically creates an economic “bubble” around research institutions or technology clusters, resulting in dependent local economies. It has been estimated that the Covid-19 pandemic cost colleges and universities over $183 billion.
Proximity to international borders, trade routes, and neighboring economies can also create opportunities and challenges that differentiate the local from the national economy.
In all local economies, labor market conditions can be affected by local government policies and regulations. Local tax incentives may drive businesses to establish or expand themselves in an area.
AnalyticsIQ Approach to Economic Data
EconomyIQ, our granular economic data product, is created by measuring current and forecasted economic conditions by CBSA (Core Based Statistical Area), or geographic clusters of at least 10,000 and fewer than 50,000 people.
EconomyIQ data points include:
- Overall Economic Condition
- Bank deposits
- Consumer bankruptcy
- Household Income
- Home Sales Prices
- House Starts
- Retail Sales
- Unemployment Filing Claims
- and more
This is a powerful tool we apply to creating many of our own data products. For example, we leverage EconomyIQ to adjust and refine our financial-focused data variables, such as household income or net worth. Essentially, if you are using data products directly from AnalyticsIQ that could be impacted by Economic Data, you are already benefiting from the inclusion of this data.
However, if you are taking variables unaffected by the economy, (EX: age or gender) and combining them with other datasets (EX: a first-party audience) for modeling, you may be leaving performance on the table.
Curious if your current data strategies could see better performance by understanding the economy better on a granular level? Reach out, and let’s talk. You can email email@example.com or schedule a meeting with our chatbot. We are a team of experts who love geeking out on all-things data and how small adjustments can yield better results.