Tech Startup’s Daily Active Users (DAU): Weekly Trends & Statistical Insights

Analyzing daily active users (DAU) is critical for tech startups aiming to understand user engagement and growth. Recently, a promising startup reported its DAU over a seven-day period as follows: 12,500, 14,200, 13,800, 15,100, 16,400, 15,900, and 17,300. These numbers reveal not only user interest but also offer a rich opportunity to assess consistency and volatility using statistical tools like the Mean Absolute Deviation (MAD).

Weekly DAU Breakdown

Understanding the Context

Here’s a summary of the DAU data for easy review:

| Day | DAU |
|-----|---------|
| 1 | 12,500 |
| 2 | 14,200 |
| 3 | 13,800 |
| 4 | 15,100 |
| 5 | 16,400 |
| 6 | 15,900 |
| 7 | 17,300 |

Total DAU over the week:
12,500 + 14,200 + 13,800 + 15,100 + 16,400 + 15,900 + 17,300 = 105,000

Calculating the Mean (Average DAU)

A tech startup’s daily active users (DAU) over a week were: 12,500, 14,200, 13,800, 15,100, 16,400, 15,900, 17,300. What is the mean absolute deviation (MAD) of DAU from the mean?

Key Insights

Mean = Total DAU / Number of Days
Mean = 105,000 / 7 = 15,000

The average daily active user count is 15,000 — a strong baseline indicating consistent user engagement.

Mean Absolute Deviation (MAD) – A Measure of Variability

MAD quantifies how much DAU deviates from the mean, offering insight into user activity volatility. It is calculated as follows:

  1. Compute absolute deviations of each day’s DAU from the mean (15,000):
    | Day | DAU | |DAU – Mean| |
    |-----|--------|-----------|------------|
    | 1 | 12,500 | |12,500 – 15,000| = 2,500 |
    | 2 | 14,200 | |14,200 – 15,000| = 800 |
    | 3 | 13,800 | |13,800 – 15,000| = 1,200 |
    | 4 | 15,100 | |15,100 – 15,000| = 100 |
    | 5 | 16,400 | |16,400 – 15,000| = 1,400 |
    | 6 | 15,900 | |15,900 – 15,000| = 900 |
    | 7 | 17,300 | |17,300 – 15,000| = 2,300 |

Continue Reading

Begin computations—this basic integral hides a secret that changes everything
Integral of 1 over x: The mind-blowing truth no algebra textbook shows you1. A researcher studying pollination observes 12 different insect species visiting flowers in a meadow. Each insect visits an average of 25 flowers per hour. If the researcher observes the meadow for 6 hours, how many total flower visits are recorded during the observation period?
Total visits = 12 species × 25 flowers/hour × 6 hours = <<12*25*6=1800>>1800 flower visits

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Final Thoughts

  1. Sum of absolute deviations:
    2,500 + 800 + 1,200 + 100 + 1,400 + 900 + 2,300 = 8,100

  2. MAD = Total absolute deviations / Number of days
    MAD = 8,100 / 7 = 1,157.14

Interpretation

With a Mean Absolute Deviation of approximately 1,157, the DAU exhibits low to moderate variability around the weekly average. This means user counts tend to hover closely near 15,000, suggesting strong and stable daily engagement—ideal for a growing startup. Such consistency strengthens confidence in user retention and product-market fit, and helps inform predictable planning for marketing and development efforts.

Conclusion:
Tracking DAU is essential for tech startups, and combining raw numbers with statistical measures like MAD provides a clearer, data-driven picture. For this startup, daily active users remained remarkably consistent over the week, with an average of 15,000 and minimal swing—marking a solid foundation for sustained growth and scalability.

Keywords: DAU analysis, tech startup metrics, daily active users mean absolute deviation, user engagement statistics, startup growth tracking