Consumers are increasingly skipping the malls and turning to online shopping for gift purchases. For marketers, even gift-giving presents an opportunity to get to know their consumers and nurture those relationships throughout the year. Observing consumer activity should be second nature for the online retailer. Even the most rudimentary ecommerce systems allow retailers to track what consumers are searching, clicking, and buying. One would naturally assume it would be easy enough to make sense of each consumer's behavior and use this information to offer quality product recommendations. But you know the old saying about assuming things. One major challenge for retailers is distinguishing between when consumers purchase for themselves and when they purchase gifts. These gift-giving "micro-moments" can easily skew an individual consumer's profile.
Consumers want online retailers to guide them in the right direction. One of the benefits of shopping online is that it's easy to discover all of the relevant products and services available. Personalized recommendations make product discovery and purchasing that much easier, getting you in an out of the online store with time to spare. Often, retailers miss the mark and turn off consumers with irrelevant recommendations. This can incite frustration, leading a consumer to think, "This brand doesn't know me" or "I'm wasting my time here because I'm not finding what I want." Not only are those retailers missing an opportunity to make a sale or drive a cross-sell or upsell, they are also missing the opportunity to build a lasting relationship with the consumer that will keep them brand-loyal.
The key for marketers is to ingest various types of behavioral data and understand contextually what the consumer's intent is at a particular moment in time, regardless of the touch-point. For intelligent retailers, this means understanding a number of variables that go into creating an individual's precise consumer profile.
For example, recently my friend visited the site of a top online retailer and purchased a new wine refrigerator for his wife. He recently complained to me that since his purchase, he continues to receive recommendations for wine refrigerators. And not only that, but the retailer also continues to recommend the same one he already purchased. What are the chances he needs to buy another?
To avoid frustrating consumers and permanently turning them off of your brand, online retailers should consider the following wavelengths of consumer behavior:
Passions: These are long-term bedrock behaviors that don't change often (for example, brand affinities).
Interests: These are behaviors that change periodically but stay relatively stable (for example, a new hobby or interest).
Intent: These are behaviors in the moment, when the consumer is providing real-time purchase-behavior data, such as clicks and views (for example, if I am on a camera product detail page, you can assume, at that moment in time, I'm looking for a camera. This can be classified as shopper context).
Successful behavioral targeting leverages information collected on an individual, based on their online activity across each of these wavelengths. With the growth of behavioral targeting, before a recommendation is even made, a marketer can determine if the consumer is likely to respond. Clearly, the retailer my friend purchased the wine refrigerator from is not applying each of these wavelengths to its recommendations.
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.
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