Every business that regularly deals with the public, from restaurants and hotels to retail stores and service providers, might think they can readily spot their unsatisfied customers. Some patrons choose to take their anger out on a manager or staff face to face. Others choose to post bad review on Yelp. Any online search will show you that. However, how can your enterprise identify the more elusive silent patron – those consumers who visit your establishment once or sign up for your services only later to never show up again or unsubscribe without a complaint?
It can be a difficult guessing game, especially for businesses in the hospitality industry, to serve a customer they assume is happy with the service, but truly isn't. Predictive modeling software, though, could be the solution to helping companies identify customers at risk of cancelling their services and drifting away, Information Management noted.
"Predictive analytics can cut down on customer churn."
Picking up on subtleties
Finding those quiet customers that do not voice their complaints requires a predictive analytics solution that can pick up on subtleties in patrons' behavior. Businesses live or die by their customer attrition or churn rates. These big data tools can examine multiple factors from bad customer support and service, high prices or just poor marketing that can all contribute to a patron taking his or her dollars elsewhere, Forbes related.
Information Management pointed out predictive analytics can alert companies if certain customers haven't visited their stores as frequently as they once did. Picking up on these cues gives the enterprise enough time to re-engage those patrons who might have fallen off the business's radar. Therefore, the enterprise can reestablish relations with these customers and find a workable path to bring them back into store, restaurant or hotel.
Personalizing the experience
Since there are a whole host of factors that could cause silent customers to drift away from your business, simply slashing prices and offering discounts won't cut it. In fact, lowering your prices to entice customers to come back can just hurt your bottom line and it presumes the sole reason why they ceased their business with you is due to your prices.
Using predictive analytics can keep these assumptions from blinding you and your business and spot those unhappy, yet quiet, patrons from hitting the unsubscribe button or from leaving your store or eatery for good.