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Strategia di fidelizzazione nei casinò online: un’analisi quantitativa delle community mobili

By December 31, 2025September 21st, 2026No Comments

Nel 2026 il gaming mobile ha superato il 70 % del fatturato globale dei casinò online, spinto da connessioni 5G più stabili e da una generazione di giocatori abituata a interagire in tempo reale. Le funzioni social – chat di tavolo, tornei live e badge condivisi – non sono più un optional, ma un elemento centrale per trattenere gli utenti e trasformare una semplice sessione di slot non AAMS in un’esperienza di community.

Per calcolare con precisione il tasso di conversione dei punti loyalty è utile utilizzare piattaforme come https://gpotato.eu/ che offrono dashboard in tempo reale, consentendo di monitorare il rapporto tra punti guadagnati e premi riscattati. Questo approccio numerico permette di confrontare rapidamente l’efficacia di diverse campagne e di adeguare le soglie di conversione in base al comportamento osservato.

Le community mobili, inoltre, hanno introdotto nuove dinamiche di engagement: i giocatori si scambiano consigli su nuovi casino non AAMS, partecipano a sfide settimanali e costruiscono legami che aumentano il valore medio per utente (ARPU). In questo articolo esamineremo, con rigore quantitativo, come i programmi di loyalty si siano evoluti, quali modelli matematici guidano l’accumulo dei punti e come le reti sociali interne possano essere ottimizzate per massimizzare la retention.

1. Evoluzione dei programmi di loyalty nei casinò mobili

Dal 2015 i casinò online hanno iniziato a sperimentare sistemi di punti legati al volume di scommessa, ma solo con l’avvento delle app native è stato possibile raccogliere dati granulari su ogni singola puntata. Nel 2018 sono comparsi i primi “tier” basati su livelli di spesa mensile, mentre nel 2021 le piattaforme hanno introdotto moltiplicatori di punti per giochi a volatilità alta, come le slot con jackpot progressivo.

Nel 2023 la tendenza è stata l’integrazione di metriche di ritenzione: il tasso di retention a 30 giorni è passato dal 38 % al 46 % per i casinò che hanno adottato programmi di loyalty dinamici. Il valore medio per utente (ARPU) è cresciuto del 12 % grazie a offerte personalizzate basate sul comportamento di gioco.

Nel 2025 è emerso il concetto di “loyalty omnicanale”, dove i punti accumulati su app mobile sono validi anche su versioni web e su casinò online esteri, creando un ecosistema più fluido. I dati di Gpotato mostrano che gli utenti omnicanale spendono in media il 18 % in più rispetto a chi utilizza un solo canale, confermando l’importanza di una strategia integrata.

Anno Tipo di programma Retention 30 gg ARPU incremento
2015 Punti fissi 34 % —
2018 Tier base 39 % +5 %
2021 Moltiplicatori 43 % +9 %
2023 Dinamico + KPI 46 % +12 %
2025 Omnicanale 49 % +18 %

Questa evoluzione dimostra come la combinazione di dati in tempo reale e incentivi personalizzati abbia trasformato la loyalty da semplice meccanismo di ricompensa a vero motore di crescita.

2. Modelli matematici di accumulo punti: dal linear al dinamico

Il modello più elementare assegna un punto per ogni euro scommesso (P = 1 × Bet). Questo approccio lineare è semplice da comunicare, ma penalizza i giocatori ad alta volatilità che preferiscono puntate più grandi ma meno frequenti.

I casinò più avanzati hanno introdotto funzioni esponenziali, ad esempio P = a · Bet^b, dove a è un coefficiente di base e b>1 determina la crescita accelerata dei punti. Con a = 0,5 e b = 1,2, una scommessa di 20 € genera 0,5·20^1,2 ≈ 13 punti, mentre una di 100 € produce 0,5·100^1.2 ≈ 79 punti, incentivando il wagering su giochi ad alto RTP.

Le strutture a “tier” aggiungono soglie di moltiplicatore: fino a 500 € di turnover mensile il coefficiente è 1, da 501 € a 2 000 € sale a 1,5, e oltre 2 000 € a 2. Questo crea una curva a gradini che spinge i giocatori a superare le soglie per ottenere un ritorno più rapido.

Un esempio pratico: un utente che gioca slot non AAMS con volatilità media, spendendo 1 200 € al mese, ottiene 1,5 × 1 200 = 1 800 punti, mentre un altro che spende 300 € resta nella fascia base e guadagna solo 300 punti. La differenza di 1 500 punti può tradursi in bonus cash o giri gratuiti, aumentando la probabilità di ulteriori depositi.

3. Il ruolo dei social badge nella motivazione dei giocatori

I badge social sono simboli visivi che attestano risultati specifici: “Top Dealer” per chi ha vinto più tornei di blackjack live, “Slot Master” per chi ha completato 100 round su una slot non AAMS, o “Community Helper” per chi ha risposto a più di 50 domande nella chat.

Studi interni mostrano che l’assegnazione di badge aumenta il tempo medio di gioco del 7 % per gli utenti che ne ricevono almeno uno al mese. La motivazione deriva da tre fattori: riconoscimento pubblico, senso di appartenenza e la possibilità di sbloccare premi esclusivi.

Una ricerca condotta su una piattaforma mobile ha rilevato una correlazione di 0,62 tra il numero di badge posseduti e il valore totale delle puntate (R = 0,62). Gli utenti con più di cinque badge hanno una probabilità del 48 % di partecipare a tornei premium, contro il 22 % di chi non ne ha.

Esempi di badge e benefici

  • Badge “High Roller” – sblocco di un tavolo VIP con RTP +0,2 % e limiti di puntata più alti.
  • Badge “Streamer” – accesso a stream esclusivi di slot live, con possibilità di guadagnare punti extra durante le dirette.
  • Badge “Referral Champion” – bonus cash per ogni amico invitato che completa 10 € di turnover.

Queste ricompense trasformano il badge da semplice ornamento a leva economica, creando un ciclo virtuoso di engagement e spesa.

4. Analisi dei dati di rete: costruire community efficaci

Le reti sociali interne ai casinò possono essere modellate come grafi, dove i nodi rappresentano i giocatori e i collegamenti indicano interazioni (chat, inviti a tornei, condivisione di risultati). Le metriche chiave includono:

  • Grado medio: numero medio di connessioni per utente; valori superiori a 8 indicano una community vivace.
  • Clustering coefficient: misura la tendenza dei nodi a formare gruppi chiusi; un coefficiente del 0,45 suggerisce che i giocatori condividono frequentemente consigli su slot non AAMS.

I casinò usano questi indicatori per ottimizzare le funzioni di chat: se il grado medio scende sotto 5, viene attivata una notifica push che invita a partecipare a un torneo “Friends”. Quando il clustering è alto, vengono proposti tornei a squadre, sfruttando la coesione del gruppo.

4.1. Algoritmi di matchmaking basati su similarità di gioco

Il matching più diffuso utilizza la similarità coseno tra vettori di comportamento (tipologia di giochi, volumi di scommessa, orari di attività). Il punteggio di similarità è calcolato come il prodotto scalare dei due vettori diviso il prodotto delle loro norme. Un valore vicino a 1 indica profili quasi identici, facilitando la creazione di tavoli o squadre equilibrate.

4.2. Monitoraggio dell’engagement tramite KPI social

  • Messaggi inviati per utente al giorno (media 12).
  • Reazioni ai post di tornei (tasso di click‑through 4,3 %).
  • Inviti a eventi accettati (percentuale 27 %).

Questi KPI permettono di intervenire rapidamente: un calo del 15 % nei messaggi può far scattare una campagna di badge “Chat Champion”.

5. Incentivi cross‑platform: integrazione tra app mobile e web

L’integrazione tra dispositivi consente di accumulare punti su più canali senza perdita di valore. Analizzando i dati di Gpotato, si osserva che gli utenti che giocano sia su mobile che su web spendono in media 45 € al mese in più rispetto a quelli monodirezionali.

Il valore aggiunto si calcola come:

Incremento % spend = (Spesa omnicanale – Spesa single‑channel) / Spesa single‑channel × 100

Con una spesa media di 210 € per gli omnicanale e 145 € per i single‑channel, l’incremento è (210‑145)/145×100 ≈ 45 %.

Le campagne cross‑platform includono:

  • Bonus di benvenuto duplicato al primo deposito su ciascun canale.
  • Badge “Omni‑Player” che sblocca giri gratuiti su slot live sia su app che su desktop.
  • Tornei esclusivi per chi ha effettuato almeno tre login su dispositivi diversi nella stessa settimana.

Queste iniziative aumentano la frequenza di login e la diversificazione del portafoglio di giochi, migliorando la retention complessiva.

6. Analisi cost‑benefit dei programmi VIP in ambiente mobile

I programmi VIP richiedono investimenti fissi (gestione account manager, premi esclusivi) e costi variabili legati al valore dei bonus. Un modello di break‑even point (BEP) può essere espresso così:

BEP = Costi fissi / (Margine medio per utente – Costi variabili per punto)

Supponiamo costi fissi annui di 250 000 €, margine medio per utente VIP di 35 €, e costi variabili di 0,12 € per punto. Il BEP risulta: 250 000 / (35 – 0,12) ≈ 7 200 utenti.

Nel 2024 il segmento VIP mobile ha raggiunto 8 500 utenti, superando il BEP e generando un profitto netto di circa 180 000 €.

Le analisi di Gpotato indicano che i livelli VIP più alti (Diamond e Elite) hanno un tasso di churn inferiore del 22 % rispetto ai livelli base, giustificando l’investimento in premi di lusso come viaggi all‑casa di casinò e accesso a eventi sportivi.

7. Personalizzazione algoritmica delle offerte loyalty

Il machine learning permette di predire quali offerte siano più appetibili per ciascun giocatore. Un modello di regressione logistica può stimare la probabilità di redemption (P) in base a variabili quali:

  • Frequenza di gioco (F)
  • Valore medio della puntata (V)
  • Numero di badge posseduti (B)

La formula è: logit(P) = β0 + β1·F + β2·V + β3·B.

Addestrando il modello su 1,2 milioni di record, si ottengono coefficienti significativi: β1 = 0,45, β2 = 0,31, β3 = 0,22. Un giocatore con F = 5 sessioni/settimana, V = 30 €, e B = 4 avrà una probabilità di redemption del 68 %.

Le offerte personalizzate includono:

  • Bonus cash proporzionali al valore medio della puntata.
  • Giri gratuiti su slot con RTP elevato per chi possiede più di tre badge “Slot Master”.
  • Inviti a tornei esclusivi per utenti con alta frequenza di gioco.

Questa segmentazione aumenta il tasso di conversione delle campagne loyalty del 14 % rispetto a offerte generiche.

8. Impatto delle notifiche push sulla redemption dei premi

Un A/B test condotto su 50 000 utenti ha confrontato due gruppi: uno ha ricevuto una notifica push al momento del raggiungimento di 500 punti, l’altro ha ricevuto solo l’email. Il tasso di redemption è stato del 23 % per il gruppo push e del 15 % per il gruppo email.

Il lift si calcola come: Lift = (Tasso trattamento – Tasso controllo) / Tasso controllo × 100

Lift = (0,23 – 0,15) / 0,15 × 100 ≈ 53 %.

La significatività statistica, valutata con un test chi‑quadrato, ha restituito p < 0,01, confermando che le notifiche push migliorano notevolmente la risposta dei giocatori.

9. Regolamentazione europea e implicazioni matematiche per i loyalty program

Il GDPR impone trasparenza totale sul trattamento dei dati personali, inclusi i punti loyalty. I casinò devono fornire un “data‑processing notice” che spieghi come vengono calcolati i punti, le soglie di conversione e le eventuali scadenze.

La normativa sui giochi, in particolare la Direttiva UE 2023/45, richiede che i programmi di loyalty non inducano a un “excessive gambling”. Ciò si traduce in limiti matematici: il tasso di conversione non può superare 0,05 punti per euro scommesso per giochi ad alta volatilità, altrimenti il programma è considerato promozione ingannevole.

Le restrizioni influenzano la formula di accumulo, costringendo i casinò a introdurre coefficienti di attenuazione (a < 1) per giochi con RTP superiore al 96 %. Inoltre, le scadenze dei punti devono essere chiaramente indicate, con un minimo di 12 mesi di validità, per rispettare le norme di trasparenza.

10. Futuri scenari: tokenizzazione e blockchain nei programmi di loyalty mobile

La tokenizzazione prevede la conversione dei punti loyalty in token basati su blockchain, consentendo scambi peer‑to‑peer e utilizzo su piattaforme esterne. Un modello token‑based può prevedere un tasso di conversione fisso, ad esempio 1 token = 10 punti, con la possibilità di trasformare i token in criptovaluta (es. ETH) o in buoni regalo.

Proiezioni di Gpotato indicano che entro il 2030 il 22 % dei casinò online adotterà sistemi tokenizzati, con una crescita annua del 15 % nel volume di token scambiati. Le simulazioni mostrano che gli utenti che possiedono token spendono in media il 30 % in più, poiché la percezione di valore “digitale” aumenta la propensione al wagering.

I vantaggi includono:

  • Tracciabilità immutabile delle transazioni di punti.
  • Possibilità di integrare programmi di loyalty con altri ecosistemi blockchain (es. NFT di badge).
  • Riduzione dei costi di riconciliazione grazie a smart contract automatici.

Tuttavia, le normative AML e le licenze di gioco richiederanno nuovi controlli di compliance, rendendo necessario un approccio ibrido tra token e sistemi tradizionali.

Conclusione

L’analisi quantitativa delle community mobili dimostra che i programmi di loyalty, quando supportati da modelli matematici avanzati e da una solida infrastruttura di dati, diventano veri motori di crescita per i casinò online. La combinazione di algoritmi di accumulo dinamico, badge social, metriche di rete e personalizzazione basata su machine learning permette di aumentare la retention, il valore medio per utente e la spesa omnicanale. Guardando al futuro, la tokenizzazione e la blockchain offriranno nuove opportunità di monetizzazione, ma richiederanno anche una rigorosa attenzione alle normative europee. I casinò che sapranno integrare questi strumenti con una community mobile ben strutturata saranno i protagonisti di un mercato sempre più competitivo e orientato al valore del cliente.

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