The Evolution of Personalized Shopping Experiences
In 2012, Target sent coupons for baby products to a high-school girl in the United States. The father found out and expressed his frustration to the company, as he was certain Target had made a mistake.
What he didn’t know is that she was pregnant, and the incident demonstrated the power and accuracy of Target’s data mining. The tool examined the purchases the daughter was making, and offered coupons for personalized shopping opportunities based on those transactions.
How have other companies followed suit since then, and how much have we, as consumers, become accustomed to more highly curated promotions and product offerings? What can content marketers learn from these experiences?
Amazon’s recommendation engine
When you buy a book or headphones or a laptop from Amazon, take a look at the bottom of your screen. You’ll see recommendations from the company’s all-knowing, all-mighty marketing engine. According to Fortune, when Amazon first launched the platform in 2012, the majority of its 29-per-cent sales increase was attributed to the machine-learning-based recommendation capability.
It was relevant, omnipresent and easy.
Last year, Amazon announced it would provide this service to other businesses, making browsing products online more seamless and relevant.
If you’ve visited a grocery store owned by Loblaw Companies Ltd., you have definitely encountered marketing collateral promoting PC Plus. It’s similar to other loyalty programs, such as Shoppers Drug Mart’s Optimum card, Starbucks rewards, or Indigo plum rewards: the more you shop, the more points you can apply toward groceries.
Loblaws has not disclosed the impact of PC Plus on revenue, but it has 10 million active members. For some perspective, it represents nearly one in three Canadians. That number alone represents success, considering it was only launched officially in November, 2013.
So, how did Loblaws do it?
Similar to Amazon, the offers on the app rely heavily on a customer’s past purchases. PC Plus collects them all, analyzing brands and categories, and then sends the customer personalized offers. In turn, customers keep going back to maximize their offers and earn more points, boosting repeat visits and average basket sizes.
According to a global survey done in 2015, only 23 per cent of consumers felt that the offers and communications they receive from companies are highly relevant to them. Loblaws is using its loyalty program and technology to fill a gap in the marketplace.
After you browse, shop and check your basket online, do you always make the purchase?According to a study by Baymard Institute, average ecommerce cart abandoment rate is 68.63 per cent. That’s an incredibly high number and many retailers are still trying to understand why.
They can make changes to their checkout pages, eliminate unexpected costs or offer free shipping, but many retailers are also targeting customers who have not completed purchases by sending out customized e-mails.
According to Listrak, when an e-mail is sent three hours after a customer abandons a cart, an average of 40 per cent opened the note and 20 per cent clicked a link. VWO’s survey showed that an average of 54 per cent of customers came back and made a purchase when they were offered a discount for what was in their shopping cart.
Not all retailers can afford or want to offer discounts for every abandoned cart, but it is important to understand purchasing behaviour to tweak pages, discount offers and e-mail communications in an effort to increase sales.
What all this has to do with content marketing
Content marketers can learn a lot from retailers and their efforts to reach out to customers with personalized coupons and communications. Readers are continuously seeking relevant content, so making recommendations based on past behaviour encourages readers to consume more content and spend more time on site.
When partnering with a sponsor, e-mail frequent site visitors with offers that can help boost the brand exposure a sponsor is looking for.
Personalized coupons and communications have been around for a while, but retailers and content marketing studios now have the capability to truly understand their audiences through big data and algorithms.
Customized offers and content can be deployed with a simple swipe.