3 data analytics lessons SMEs can learn from top casinos

Big data analytics for SMEs are no longer part of the future. Organizations of all sizes across Australia and New Zealand can look to the world’s giants to see how this technology is being implemented and what they have to learn from it.

Casinos are perhaps some of the best in the class at using big data to improve their operations. So what are they doing and what big data lessons can organizations take from it?

1. Use analytics to get real-time feedback on products

Casinos around the world use real-time analytics to determine which games are or are not popular, and more importantly, when they become one or the other. For example, MGM Resorts International uses its intelligence to monitor games and swap them off the floor if they start to lose popularity. “

Our job is to find out how we can optimize the selection of games so that people get a positive experience as they walk through the door, “LM O’Donnell, Director of Corporate Slot Analytics, told Rewrite.” We can understand how games work, how well they are received by guests, and how long they should be on the floor. “

-Big data analytics tip: Imagine if you were monitoring each of your products, either in-store or online. You can watch in real time as some products become more or less popular. You push the popular products to the front of the store (maybe even offer a special deal), and pull back everything people aren’t interested in. Your store will be dynamic, changing to your audience’s wishes when and when needed. The opportunity to exploit insights from data has never been greater.

2. Create heat maps of popular places and schedule them accordingly

Similar to monitoring the popularity of the slot machine, casinos are also able to take this concept to physical space and track real locations in the building.

“You can analyze the crowd flow used by real estate these days,” said Caesars Palace vice president of security and surveillance Tom Flynn, speaking with urgent communications. “It can be looked at for safety, convenience and marketing – understanding what guests are interested in what they are not. Do they go to a particular restaurant at times, go to the bottom, [or to] parking lot? “

3. Encourage loyalty through personalized experiences

Caesars has also been at the forefront using business information creating personalized customer experiences that encourage loyalty in its customers. Its loyalty program, Total Rewards, provides rewards to customers as they spend money at a Caesars Entertainment establishment, and the more they spend, the more data Caesars can collect. Customers rank through different levels of loyalty and earn bigger and better rewards, and the company gets more data about this person to provide a tailored reward experience.

With this information and the platform available to deliver it, even if a protective Caesars is having a bad game day, they could still travel home with a reward. This encourages repeat business.

-Big data analytics tip: Customer loyalty programs are by no means a new concept, but you can’t just offer stamp cards and meaningless gifts without data behind it. By using analytics, you learn what customers want and when they want it, so you can tailor their individual experience to it. This is not just for retailers or consumers either. B2B companies and anyone with a variety of channel partners should also analyze data from their customers and channels – if anyone is willing to offer money for your products or services, you must know who they are and what they like.

In conclusion: Take advantage of the opportunity for big data to present

Australian and New Zealand smaller business owners can use big data in a wide variety of ways, and now you know how. In the end, understanding your customers and their habits can only be beneficial so you can tailor your displayed products, loyalty rewards and even your marketing campaigns to the needs of the right people.

If you would like to talk more about using modern big data tools in your business, Contact SAS today.

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