Many marketers struggle to keep pace with sudden shifts in consumer behavior and market trends. For many organizations, it comes down to a lack of follow-through on the use of real-time customer and market information.
Wow Customers with Right-Time Marketing
The use of real-time data streams and analytics provide marketers with opportunities to “wow” their best customers with the right messaging at the right time.
In an article on AdvertisingAge, Altimeter Group analyst Rebecca Lieb shares the story of Paull Young, director of digital at charity: water. Young was riding a Citi Bike in New York City when he took a spill in the rain. His khakis were ruined and he shared the news on Twitter with #PLEASESENDPANTS as a hashtag.
After enlisting the help of J. Crew, Citi Bike quickly delivered Young a gift certificate that he was able to immediately use to buy new pants at a J. Crew store. That type of relevant and personal real-time marketing can enable a company to not only delight customers, but potentially turn them into brand advocates and generate positive publicity, incremental revenue, and other business benefits.
You Have Customer Data, Now What?
Only 9 percent of North American marketing executives believe their companies are making use of customer intelligence in real time, according to a CMO Council study.
But companies such as Starbucks, American Express, and Dell are among those organizations that are succeeding with real-time marketing, as Lieb notes in a separate post on the topic that was published by Marketing Land.
For its part, Starbucks is renowned for location-based marketing. For example, when its customers are approaching or passing one of its locations, a customer is sent a real-time offer based on that customer’s purchasing history and preferences (e.g., “Come in now and receive 20 percent off a Hazelnut Macchiato.”).
Still, there are numerous ways that marketers can make use of real-time data streams and cloud-based analytics tools to send relevant messaging and offers to customers and prospects.
For instance, a casino/hotel operator can apply analytics against a blend of information from its customer loyalty program and real-time data to make relevant offers to high-value customers as they’re checking in (e.g., “We’d like to offer you a 25 percent discount on dinner if you dine in one of our hotel restaurants tonight.”).
Alternatively, the casino can use real-time data analytics to trigger an appropriate offer to a high-value customer at the right time based on a customer interaction.
As an example, if a high-value customer uses a loyalty card to purchase $5,000 in chips, the casino can send that customer an SMS notification with an invitation to an exclusive high-stakes poker game. The offer might be based on historical information about the customer’s interest in playing poker along with other information, such as the mathematical likelihood for that particular customer to accept the offer.
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