Interpretation notes
domain_renew is treated as the strongest observable proxy for retention (customers paying to keep domains).
domain_create is interpreted as attempts/interest rather than confirmed purchases.
Transfer flows are used to decompose domain base changes: ΔDomains ≈ organic_growth + net_transfers, where
organic_growth ≈ ΔDomains − net_transfers.
Domains over time
Absolute daily domain count attributed to the registrar (stock variable from daily_stats).
Step changes often indicate portfolio migration or acquisition.
Market share over time
Daily market share (%) = registrar domains / total .cz domains. Normalizes out overall market growth.
Retention signal: domain_renew (daily)
Daily renewal operations (flow). Aggregates to window totals and supports renewal-intensity comparisons.
Acquisition vs interest (daily): contact_create vs domain_create
contact_create approximates onboarding/new customer objects; domain_create captures attempts/interest. Ratios may exceed 100% due to decoupling (pre-created contacts, reuse, API workflows).
Transfers: gain / loss / net
Migration signal based on registrar-to-registrar moves. Loss is negative; net = gain − loss.
Daily change (first difference): ΔDomains(t)
ΔDomains(t) = Domains(t) − Domains(t−1). Highlights shocks, step changes, and high-volatility periods.
Monthly renewal share vs last-year domain base (100% stacked)
For each month, we compare domain_renew to the registrar’s average domain base in the same calendar month one year earlier.
The stacked view estimates “renewed” vs “not renewed” share relative to that last-year base (capped at base for visualization).
Important: this does not account for multi-year renewals (renewing for multiple years reduces observable renewal operations later),
therefore this is a comparative proxy, not a true renewal rate.
Monthly: Renewals / last-year base (%)
Renewal intensity expressed as percent of last-year monthly base:
100 × domain_renew_month / avg(domains_month_(t−1y)).
Can exceed 100% due to operational effects (including multi-year renewals and data decoupling).
Transfer counterparties (competitor matrix)
| Competitor | Incoming | Outgoing | Net |
|---|---|---|---|
| Forpsi | 34 | 531 | -497 |
| VEDOS | 40 | 135 | -95 |
| Subreg | 15 | 36 | -21 |
| Webglobe | 32 | 12 | +20 |
| Media4web | 7 | 11 | -4 |
| Active 24 | 22 | 18 | +4 |
| REG-OPENPROVIDER | 0 | 4 | -4 |
| REG-KRAXNET | 3 | 0 | +3 |
| regZone.cz | 9 | 6 | +3 |
| REG-WEBSUPPORT | 0 | 3 | -3 |
| REG-TELE3 | 1 | 4 | -3 |
| REG-THINLINE | 9 | 11 | -2 |
| REG-BANAN | 2 | 0 | +2 |
| REG-PIPNI | 1 | 0 | +1 |
| REG-WINSOFT | 1 | 0 | +1 |
| REG-WEB4U | 0 | 1 | -1 |
| REG-SEZNAM | 3 | 2 | +1 |
| REG-DYNADOT | 0 | 1 | -1 |
| REG-OVH | 1 | 0 | +1 |
| REG-KEYSYSTEMS | 1 | 1 | +0 |
Aggregated registrar-to-registrar transfer flows within the selected window. Positive net indicates dominance of inflow from that competitor; negative indicates outflow.