E-Commerce Marketing Reimagined: Maintaining Connections During COVID-19

Throughout the uncertainty and changes, brands should keep a constant strategic focus on digital experiences. Research VP Sheryl Kingstone of 451 Research puts it well: “This current crisis could place more emphasis than ever before on the growing primacy of the digital experience as we try to adhere to ‘social distancing’ requirements, but also increase the efficiency and effectiveness of meeting the immediate needs of thousands, if not millions. …In effect, this is forcing the evolution of the entire technology stack and organizational culture to enable real-time, contextually relevant experiences.”

Kingstone notes that relevant and helpful digital engagements are becoming even more critical in today’s environment. Personalization drives these engagements and provides a way to connect with customers and show that you understand them. In a time of high anxiety and limited face-to-face contact, customers know that they matter because the brands they love recognize them, and make them feel like they matter. At Salesforce, we find great meaning in lessening the burden on our customers by helping them connect with their consumers.

Personalization platforms driven by machine learning offer companies a unique opportunity to engage their consumers with relevant digital experiences and automatically adjust to changing sentiment and behavior in real time. At the same time, machine learning needs to be managed and guided by marketing staff who are likely experiencing the greatest challenges of their professional lives.

As companies examine every aspect of consumer interaction and uncover new and innovative ways to engage people from anywhere, we wanted to share a few valuable examples. There are many ways that retailers are using technologies to communicate rapidly and effectively, alleviate customer pain points, and deliver personalized experiences that fortify connections, help shoppers get what they need and want, and assure deliverability.

Nowadays, inventory levels are changing rapidly and unpredictably. Supply chain issues, manufacturing delays, and warehouse challenges mean out-of-stock items that previously came back in-stock quickly may not be available for quite some time.

It’s always irritating for shoppers when they reach a “dead end” (such as an out-of-stock page). The feelings of frustration are amplified now, given heightened demand for some items and the ensuing scarcities. Using personalization, retailers can factor up-to-the-moment inventory and shifting consumer interests in their machine-learning-driven product recommendations, whether deployed on the web, in their mobile app or in outgoing emails (which can be updated at open-time). That way, consumers receive recommendations for items that are relevant to them, are not on backorder or require being drop-shipped, and can actually be shipped today.

You can also use personalization to boost products (such as those featured in on-site recommendations to shoppers) that have over a certain threshold of products available. This figure can be customized to key categories, and you can also ensure that items with limited inventory are not featured prominently across key points of interaction in email, in your app, on the web, etc.

We’re also seeing retailers use personalization technology to omit drop-ship and backorder items on their product listing pages (PLPs). This helps to prevent visitors from engaging with items that may be unavailable for immediate shipping.

With many people still socially isolating at home and steering clear of unnecessary interactions, it’s more important than ever to not only display relevant products but also amplify content related to that particular product or category. This product-to-content curation strategy can help to increase site exploration, category/range awareness, and conversion.

Skincare and beauty site Dermstore does this well, prominently featuring above-the-fold content and guides on its site. For example, the retailer provides “Sunscreen 101” expert advice, with articles and tips from dermatologists about choosing the best SPF, while also making it easy for visitors to shop and explore sunscreen products.

Many retailers are expanding or accelerating their “buy online, pick up in store” (or BOPIS) strategy as we transition to a phased re-opening. The first step is identifying which stores will be open and when, and sharing that information with local consumers. The challenge arises: how do you market BOPIS locations when BOPIS openings will be implemented in a phased approach?

Recently, Academy Sports + Outdoors observed increased interest in BOPIS products in the backyard entertainment category. Previously, a website visitor would have to scroll through the product category to determine if an item was BOPIS eligible. Now, they can pre-select the “Store Pickup” filter, enabling shoppers to see BOPIS availability in their saved store location.

Undoubtedly, marketing campaigns in this era need to have extra scrutiny applied and more review cycles factored in. Showing empathy and togetherness is important. There’s also a fine line between exhibiting appropriate (and appreciated) levity, and being tone-deaf.

In addition, to take your content to the next level, consider that machine learning can detect behavioral patterns in a way humans can’t – delivering 1-to-1 relevance at scale in, for example, promotions and product recommendations. Algorithms can adapt to changing behaviors in the moment too. For example, a previous shopper of high-end fashion items may be more interested in casual, comfy leisure clothes or casual-but-professional video-conference-appropriate wear. At some point, too, that shopper may be returning to the office and want business attire again. All digital experiences should reflect that person’s changing preferences (as evidenced from their recent browsing behavior, buying habits, brand, department or category interests, etc.) and adjust to further changes in behavior in real time.

Online men’s retailer Huckberry provides examples of marketing and machine learning done well – engaging shoppers with relevance (e.g., socializing employees’ own work-from-home set-ups) and tying compassion into the products they recommend (e.g., “when you purchase the 72-hour tee donation bundle, you’ll get your own tee, and we’ll donate one to a frontline worker on your behalf”). They’ve also successfully established a dialogue around “the new work clothes” (sweats and other athleisure) and the work-from-home mullet (business up top, sweats on the bottom).

See a few email examples below:

Retailers now have a marked focus on rapidly securing sales and fulfilling orders. The prevailing strategy is often aggressive, deep discounting – and a lot of it. As even more business moves online, managing markdowns will become more common and strategic.

Personalization engines that apply advanced machine learning can help with dynamic offer management, based on the individual customer. For example, free shipping might incentivize most customers to make a purchase; another subset, though, could find specific promotions like discounts on select styles, single-day deals, or buy-one get-one offers more compelling. Machines can pick up on these cues at scale, in a way humans cannot, to drive more discovery and conversions.

In the example below, a luxury retailer uses machine learning to identify customers who may need promotional offers to get them to convert – and then tailors the promotion displayed to eligible customers, based on their affinities.

Bounce prevention has always been important for retailers. In today’s climate, it’s especially strategic for those companies that sell commodity-type items that are available through other sites.

To help close transactions as quickly as possible, e-commerce teams should show messages to shoppers who display exit-intent behaviors (moving the cursor to exit a page, highlighting/copying a price – presumably to comparison-shop, etc.). These messages could be promotional offers, free shipping reminders, information about flexible return policies, and more.

Through troubling times, it’s been inspiring to see how many companies are pitching in to make a difference and thinking creatively, precisely, and deeply about how to drive customer connections during the pandemic.

Many are also pivoting to new ways of running their businesses (being impelled, for example, to translate in-store practices such as personal shoppers and shopping advisors into equivalent online options). To be successful, these changes in mindset need to be accompanied by support for a digital-first posture at the leadership- and infrastructure-level. Many retailers have already undergone digital transformations; many others are rising to the challenge under the most difficult of circumstances.

In addition, we’re already seeing a focus on extended planning – not just on “How do we get through this?” but “What happens next?” and “How many phases of recovery will we experience?” While much remains unknown, a silver lining is that the business agility, creativity, planning, and technology best practices displayed will persist even after the crisis has resolved.