EGR Global is teaming up with data providers to bring our customers even more of the gaming intelligence they need

Egamingmonitor is a B2B service provider, founded by industry veterans. They provide a large-scale data warehouse of online studios, games, platforms, and operators across the casino, bingo and lottery sectors. 

Data is accessed via interactive charts, allowing companies to analyse country markets by which operators are active there, which studios, which studios on which operators, which game types, games and even which game features such as volatility or game themes are popular. 

Operators and studios can also zoom in on the detail for specific operator groups, sites, pages or even position on pages of casino content. For bingo suppliers and operators, the warehouse also allows access to active player numbers and prize amounts per multiplayer bingo room per hour.

Their unique data is for studios, aggregators, operators and the financial community. They currently run EGR’s global online gaming charts and their data powers industry awards.

They have five main products that allow companies to make many key tactical and strategic decisions:

Casino game, supplier and operator data

Four core databases of: 

  • 47,000 casino games of all types including slots, table games, live games, video bingo etc. 
  • 1,500 suppliers to the industry, especially game studios and platform providers or aggregators
  • 4,000 operators
  • 10,000 operator URLs scanned weekly for game positions on page

Decision types:

  • Games… which games are topping the charts? What features or themes are successful by country? How are my games performing in terms of distribution across operator pages and also their ranking on those pages?
  • How do operators compare on nos of studios and promotion of specific contentDealmakers.. who are the biggest studio or aggregator dealmakers? 
  • Which aggregator partners should I target or which studios should I add?

Hourly data on bingo rooms allowing for room comparisons of:

  • Ticket prices, nos of tickets bought, average buy-ins plus game nos or types by day/time of day etc
  • Active player numbers and revenues by hour, by room, by operator by…

Decision types: 

  • How do suppliers and/or operators compare in terms of active players by day, hour, room type, game type?
  • How do they compare in financial terms, e.g. average turnover by day, hour, week, game type etc?
  • What are the market shares by supplier and/or operator?
  • What configuration of stakes and prizes would improve active user and revenue numbers?

Daily data on sales, rtps, jackpot sizes, FOWs, winner nos by draw:

  • 60 Lottery operators
  • 300 lottery draw products
  • 30 different countries
  • 20 lottery product suppliers
  • 5000 instant win game products

Decision types: 

  • Ticket numbers sold by draw product by day
  • Value of tickets sold by product by day
  • Add on or upsell draw volumes by operator by day
  • Theoretical and actual RTPs by lottery by draw
  • Frequency of win comparisons of all lotteries globally
  • Per capita comparisons of draw sales by product by country or region

Affiliate mentions of operators, studios and games by affiliate, by affiliate type, by country

  • EGM curate exclusive game theme, colour and feature data for all games
  • Game data used by aggregators and operators for site content, user filters and game recommendation engines