Understanding Extreme Growth Values in Spend Data

Overview

You may occasionally notice unusually large increases in Spend Index values in your Geo Insights data. These spikes can be surprising, but they often have a clear explanation tied to specific real-world changes in the retail environment.

What can cause extreme growth values?

Here are the most common reasons why Spend Index metrics may show significant growth in a given geographic area:

Store Opening: A newly opened store can generate a substantial increase in spend where previously there was little or no activity.
Store Closing: If a store closes within a quad, a sharp decrease in sales or transactions will be seen.
Refurbishment or Temporary Closure: When a store is temporarily closed for remodeling or refurbishment and then reopens, the period following reopening may show an abrupt increase in spend compared to the zero baseline during closure.

How Geo Insights metrics amplify these effects

Geo Insights data is presented as indexed metrics, not raw transaction values. This means:

Spend is calculated as an index relative to a baseline (typically the daily average for 2018).
In areas where spend was previously low or absent (due to closure or no store presence), the first signs of activity can appear as extremely high growth percentages.
These effects are especially pronounced at the most granular levels of the data (e.g., 150m x 150m "Quad" blocks).

Note: Index-based metrics help identify trends, but they may exaggerate fluctuations in cases where the denominator (past activity) is near zero.

How to interpret these spikes

While sudden increases may seem like data anomalies, they can be valuable indicators of:

Commercial activity resuming after a gap
New developments or retail investments
Recovery after temporary disruptions

Always cross-check high growth areas with store operations data or local business activity to confirm the underlying cause.

Tip: If you're using these metrics to inform business decisions (e.g., network planning or site analysis), be sure to review contextual factors — like store timelines — to understand whether extreme growth is a signal of genuine expansion or simply a return to baseline.