Buzz-to-Sales Lag Analyzer
Pricing
from $1.00 / 1,000 results
Buzz-to-Sales Lag Analyzer
Compare your own daily product-mention counts with sales to measure historical peak timing and lagged correlations. Uses data you provide; it does not scrape social media or forecast future sales.
Pricing
from $1.00 / 1,000 results
Rating
0.0
(0)
Developer
Chris Johnson
Maintained by CommunityActor stats
0
Bookmarked
2
Total users
1
Monthly active users
18 minutes ago
Last modified
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Find out whether increases in online mentions tend to come before changes in your own product sales. This Actor compares daily mention counts with daily units sold and reports the observed peak dates, their day offset, and the strongest historical relationship within a lag window.
Use it when
- You already export daily mention counts from a social-listening or analytics tool.
- You have daily sales totals for the same product and dates.
- You want a repeatable, machine-readable analysis across several products.
This Actor analyzes data you provide. It does not collect posts, connect to social accounts, or predict future sales.
Input
Provide 3–366 consecutive daily observations per product. Each observation needs a date, mention count, and units sold. Choose a lag window from 0 to 30 days.
In a full run, include at least three consecutive days for each product. Use consistent dates and definitions across both data sources. Do not include post text, usernames, customer details, or other personal information.
Results
The Actor emits one dataset item per product with the largest observed mention and sales peaks, the number of days between those peaks, the strongest lagged correlation between daily changes, the number of paired days, and an evidence status.
How to interpret the result
This is a historical comparison, not a forecast or proof that mentions caused a sales change. Promotions, stockouts, price changes, seasonality, returns, and missing data can affect the relationship. Check the dates against your campaign and inventory records before making a business decision.
No external service or paid data source is required to run the analysis.
