Not only do marketers need to consider these micro-moments, but also the consumer's preferences for how and when to shop. For marketers, successful personalization relies more and more on the intelligence of algorithms. Customers are being given more control over recommendations based on data they provide retailers. Through the use of algorithms and predictive analytics, retailers can track behavior so every online activity, such as a click, search, or purchase, feeds back into the algorithm. This allows for a retailer to keep an accurate, dynamic profile of the customer, and keeps recommendations fresh and current. Personalization solutions access the holy grail of one-to-one customer relationships. Beyond solutions that provide this service to retailers and marketers, there are simple steps retailers can take to support even early-stage personalization efforts.
Have a plan
Think about what site activity, customer data, and third party data matters most to your business, and use this data appropriately. Do a sanity check of the results to make sure that even the most basic recommendations make sense to the customer. And always keep in mind what customers have already purchased, especially recent purchases. There's nothing worse than seeing a recommendation of an item that you just purchased and haven't even paid the credit card bill for.
Start with segmentation
Separate premier and loyal customers from one-time customers, and market to them differently. This is an age-old customer-segmentation strategy, but surprisingly one that has been lost in online marketing. In addition, hyper-segment these groups, if you're able to. It's one of the first steps toward creating a true one-to-one relationship with your customer.
Tune in to the right channel
Businesses that have a loyalty program, for example, should be able to match up online and offline purchase behavior to help more effectively target individual customers when and where they want to be reached. Also, be sure to consider additional data as well as including mobile-channel data. There are nuggets of information contained in the core subscription data (geographic region, gender, etc.) that can be beneficial in making more relevant recommendations.
Test, tweak, optimize
Regardless of how and where you get started, always test to see what works and what doesn't. And always continue to optimize. Personalization is an ongoing process of improvement. Consumer behaviors change, your product catalog changes, and the marketplace changes. With all due respect to Benjamin Franklin, death, taxes, and change are the only certainties in life. Your algorithms -- which are powering your ecommerce life -- should adapt accordingly.
Marketers with personalization solutions that use shopping-related behavioral data in the most skillful way to understand their customers are the ones who will ultimately win the customers over. These solutions can match customers with extremely precise recommendations and guide consumers in the right direction -- whether the purchase is a gift or an every-day item. Marketers that don't have this capability and remain inaccurate in their targeting efforts are at a great risk of losing sales and, even worse, customers.
Online shopping allows us to learn more about consumer behavior than ever before. Couple this with powerful algorithms and predictive analytics, and marketers can accurately predict what the consumer will likely be in interested in next.
Getting to know your consumer's likes and dislikes, and differentiating between gift- and personal-purchase behaviors is crucial. They will begin to view you not just as a retailer, but as a resource that can help make their buying decisions easier. It's the loyalty game, and you want to be in it to win it.
Millie Park is VP and general manager at ChoiceStream.
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