Providing Accurate Online Recommendations Post Mother’s Day

According to a recent study from the National Retail Foundation, 83% of the nation had plans to celebrate Mother’s Day this year, and 26% were projected to buy their Mother’s Day gifts online. This brings to mind one of my favorite mother quotes – “A mom’s hug lasts long after she lets go.” However, that hug doesn’t have to turn smothering when it comes to online recommendations.

Now that Mother’s Day has passed, consumers who purchased gifts for mom will no doubt go back to focusing on their own online shopping needs. However, one major challenge for online retailers is distinguishing between when consumers are purchasing for themselves and when they are purchasing gifts, like the aforementioned Mother’s Day purchases.

Unfortunately, these gift-giving “micro-moments” can skew consumers’ online profiles, leading to a series of irrelevant recommendations for kitchen gadgets and perfume that could haunt the online shopping experience for the rest of the year. That’s why most savvy marketers are now turning to algorithms to identify behavior and appropriately adjust their online recommendations.

Through the use of predictive analytics and algorithms, retailers can track behavior so that almost every online (and even offline) activity feeds back into the algorithm. This permits retailers to keep an accurate and dynamic profile of the customer. Integrating behavioral history with in-session intent keeps recommendations targeted and fresh.

Even if you don’t consider yourself a savvy retailer and your use of predictive analytics and dynamic personalization isn’t necessarily in your genes don’t fret: your mom still loves you!

To avoid these poor experiences, online retail marketers should keep in mind some simple rules their mothers taught them. After all, a mother knows best:

Have a plan
Consider what customer data, site activity, and what third-party data matters most to your business, and use this data appropriately. Review the results for editorial quality – even the simplest recommendations should make sense. Always keep in mind what customers have already purchased, especially recent purchases.

Do the right thing
The right channel that is. Businesses that have a loyalty program, for instance, should be able to sync offline and online purchase behavior to help more successfully target individual customers through the appropriate touchpoint. Also, consider data from touchpoints such as mobile, tablet, and even direct mail response to personalize the entire experience.

Always seek to improve
Regardless of how and where you get started, always test to see what’s working and what’s not, and always continue to optimize. Personalization is an unending process of improvement. Consumer behaviors change, your product catalog changes and the marketplace changes.

Marketers that follow these tips and use technology that analyzes behavioral data to drive meaningful recommendations are the ones who will succeed in winning the customer over in the end. Marketers that make the mistake of being inaccurate in their targeting efforts – confusing a “micro-moment” for consistent behavior – are at great risk of losing sales and customers, not too mention a mother’s scorn.

Mille Park is vice president and general manager of CONNECT at ChoiceStream.

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