Veritone (VERI) Accumulated Expenses (2016 - 2019)
Veritone (VERI) reported Accumulated Expenses of $12.41 million for Q2 2019, up 56.3% from $7.94 million a year earlier but down 7.0% from the prior quarter.
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Analysis
Veritone (VERI) Accumulated Expenses (2016 - 2019) Analysis & Trends
At the end of FY2018, Veritone posted Accumulated Expenses of $7.42 million, up 23.6% from FY2017.
- By year, Accumulated Expenses came in at $6 million in FY2017 (-15.1%) and $7.06 million in FY2016.
- Five-year quarterly Accumulated Expenses spans a low of $6 million in Q4 2017 and a high of $14.13 million in Q3 2018.
- Year over year, Accumulated Expenses has now increased in each of the last four quarters, with growth averaging 24.8% over the last seven quarters.
- Per Business Quant data, the three quarters before Q2 2019 came in at $13.34 million (Q1 2019), $7.42 million (Q4 2018) and $14.13 million (Q3 2018).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 242.71 Bn | 227.79 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 226.31 Bn | 206.71 Bn | 1.10 Bn |
| 3 | Snowflake | 101.65 Bn | 88.97 Bn | 1.04 Bn |
| 4 | Fortinet | 89.39 Bn | 73.64 Bn | 1.64 Bn |
| 5 | Datadog | 64.14 Bn | 44.69 Bn | 959.92 Mn |
| 6 | Zscaler | 32.12 Bn | 18.27 Bn | 689.22 Mn |
| 7 | Okta | 30.80 Bn | 20.90 Bn | 641.00 Mn |
| 8 | MongoDB | 26.36 Bn | 16.83 Bn | 569.77 Mn |
| 9 | Axon Enterprise | 25.15 Bn | 19.68 Bn | 546.45 Mn |
| 10 | Veritone | 49.13 Mn | -42.04 Mn | 15.46 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2019 | 12.41 Mn |
| Mar 31, 2019 | 13.34 Mn |
| Dec 31, 2018 | 7.42 Mn |
| Sep 30, 2018 | 14.13 Mn |
| Jun 30, 2018 | 7.94 Mn |
| Mar 31, 2018 | 6.91 Mn |
| Dec 31, 2017 | 6.00 Mn |
| Sep 30, 2017 | 9.06 Mn |
| Jun 30, 2017 | 8.98 Mn |
| Mar 31, 2017 | 9.66 Mn |
| Dec 31, 2016 | 7.06 Mn |
API Access
Veritone Accumulated Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=VERI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "VERI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=VERI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();