Customers are asking for personalized, relevant experiences, and when retailers listen, it pays off. Here are some recommendations for personalizing the shopping experience using Salesforce.
This is the first in a series of blog posts on frequent use cases that span the shopper journey across commerce, marketing, and service. It will cover industry best practices, as well as how to’s around setting up these journeys with Salesforce. Check back for additional posts around common marketing and commerce use cases like personalized recommendations, abandoned carts, transactional emails and coupon redemption, and commerce and service use cases such as order-on-behalf-of and view order history & cancellations.
When I meet with customers, I’m frequently asked how businesses can improve customer experience. I tell them that the best way would be to ensure that it’s personalized and efficient; that shoppers can find what they need, and that they can checkout quickly.
One way to jumpstart this discussion is asking our customers to recall their own shopping habits and expectations — and to share both excellent and not so excellent experiences they’ve had.
Over many customer conversations, themes emerged that match what we see in our research including The State of the Connected Customer: 72% of customers want companies to personalize interactions according to their needs, and 59% of customers believe that tailored engagements based on past interactions are a key to winning and maintaining their business.
Bottom line: customer expectations are growing in importance, to the point that 80% believe the experiences that brands and retailers provide is just as important as their products and services. Customers are asking for personalized, relevant experiences, and when retailers listen, it pays off. In a recent report, Salesforce found that personalized product recommendations drove just 7% of visits but an astounding 26% of revenue.
Here are some recommendations for personalizing the shopping experience using Salesforce:
Why leverage Artificial Intelligence to create personalization at scale?
Artificial Intelligence (AI) isn’t just a buzzword; it’s the easiest way to make sense of the millions of clicks, taps, views, and products browsed and purchased, to create more unique campaigns and site experiences that are personalized to your customers.
Another great benefit? Your marketing and merchandising teams are freed from the tactical burden of manual tasks, allowing them to become more strategic, including adopting a testing practice to stay on top of customers’ shifting expectations.
The paths to personalization using AI
Whether customers start their shopping journey with you from an email, or your commerce site, there are many ways to create personalized experiences.
Embed personalized recommendations in email for a consistent drumbeat of relevant products
A “welcome to our brand” email series or abandoned cart program are just a couple of ways to leverage personalized recommendations. Some brands have reported a 5-10% lift in clickthrough rate when they did so. Other brands have also started embedding recommendations into post-purchase emails, with impressive results. We’ve discovered that half of repeat buyers make their second purchase within 16 days of initial purchase, so it makes sense to continue offering recommendations well beyond a purchase.
By leveraging Einstein recommendations in Marketing Cloud, you can define strategies specific to your marketing objectives. For example, personalize an abandoned cart email by showing complementary products to what they left behind, like wool socks with hiking boots. Post-purchase emails can showcase newly-released products, and a welcome email can feature top sellers.
Surface relevant product recommendations and personalized experiences onsite
When customers visit your site, Einstein takes stock of every action: views, taps, add-to-carts, saves, likes, device type and location, and immediately starts personalizing the site experience. Meanwhile, those clicks are building a unique profile that is constantly evolving, to hone in on the products and categories that each shopper prefers. This approach is a proven growth driver. In fact, during Holiday 2018, 28% of the season’s revenue was attributed to shoppers that tapped on a product recommendation!
Since Einstein offers flexible strategies, I always encourage our customers to leverage recommendations across their site — and define strategies for each zone based on context. For instance, on the home page, I recommend showcasing top selling and recently viewed products across your catalog influenced with 1-to-1 personalization. For category landing pages, brands should define a similar strategy, but ask Einstein to focus on surfacing products specific to that category and child pages.
Of course, showing recommendations on product detail pages is a must have, and the “right” strategy comes down to your business priorities. Does it make sense to show upsell products, complementary products or a blend of the two? If you’re not sure, test it!! Our A/B testing tool takes clicks, not code, so your merchants can easily test and validate.
Use your site’s search functions to serve up hyper-relevant recommendations
Lastly, it’s important not to forget search. The search bar is one of the most effective ways to help shoppers find what they’re looking. Einstein Search for Commerce can supercharge search and sorting rules – showing search results that are personalized to each shopper for the most relevant results that drive conversion.
Another often overlooked, but highly effective area to target are the dreaded “No Search Results Found” pages. I recommend including product recommendations on that page that are highly focused on real-time personalization (i.e., the products the shopper has most recently clicked on). It’s a great way to re-engage the shopper with products they’re more likely to want and prevent them from bouncing from the site. We’re also seeing brands explore putting these recommendations in the shopper’s Order History area — where a customer goes to check on order status, see recommendations and may consider making an additional purchase.
These are a few examples of how AI-powered product recommendations provide relevant and personalized experiences to lapsed, returning or even brand new customers whether they engage via email or on site. You can find more data about how personalization is transforming the shopping experience and driving sales in our report: The Power of Personalized Shopping.
The great part of my job is every time I meet with a customer I hear a new story of how they are taking the power of Einstein to the next level. In the next post in this series, my colleague, Mihir Panchal, will get more into the specifics to ensure you’re set up to take advantage of some of these ideas.