Companies amass a ton of information about their customers’ behaviors, preferences, and interests through data that’s gathered from customer interactions in various channels.
Whether a customer is browsing a company’s product pages to gather information about a product or she engages in a chat discussion with an agent about a service issue, companies can use this information with analytics to gain a richer understanding of each customer and to better tailor offers, messaging, services, and products for them.
Companies can make clever use of historical transaction data and recent behavioral information to provide customers with proactive communications that are personalized and relevant, as Don Keane notes in a recent blog post for Business2Community.
Amazon is famous for doing this. Let’s say an Amazon customer places an order for a Stephen King book he has previously purchased from the e-tailer. Drawing off the customer’s purchasing history, Amazon detects that fact and then sends the customer an alert, asking if he really means to purchase the same book.
By looking out for their customers’ best interests, Amazon and other companies that use analytics to provide customers with personalized, proactive communications stand to strengthen their customers’ trust and reinforce their loyalty.
There are numerous ways that companies can use customer data and data analysis to provide customers with relevant and personalized messaging and experiences.
If a customer orders a 55” big screen TV online from an electronics retailer, the retailer could analyze the customer’s previous purchasing history and send the customer an offer for a package of related components such as a TV stand, home theater seating, speakers, etc.
Maybe the customer has already purchased some or all of these items from another retailer or maybe the customer just isn’t interested in them. Still, the retailer stands a better chance of cross-selling at least some of the equipment to the customer based on the relevance and timeliness of the offer.
Contact center interactions conducted through various channels (voice, chat, email, social, mobile) also give companies a lot of information about consumer channel usage, preferences, and behavioral insights they can use to craft personalized support experiences for customers, especially high-value clients.
Relationship managers and other decision makers for a regional bank could use analytics to determine exactly when a high-value customer uses the bank’s interactive voice response system to check account balances.
The bank could use this information to offer to push account balance updates to the customer through SMS alerts to his mobile device or via email during those times.
By customizing this service for the customer and by offering the service proactively, the bank demonstrates its understanding of what the customer wants while making it easier for him to access the information he needs.
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