One analysis of this year’s holiday shopping encapsulates why it’s so important for retailers to engage the omnichannel consumer with personalized content and offers. According to the International Council of Shopping Centers, omnichannel retailers were the beneficiaries of 88 percent of all spending on Thanksgiving and Black Friday. Furthermore, 27 percent of omnichannel shoppers chose to buy online and pick-up in-store, and roughly two-thirds of those who did made an additional purchase once in-store.
While traditional brick-and-mortar retailers might think beefing up an online presence will solve all their problems, the truth is that it’s about more than presenting customers with options; rather it’s about being able to recognize and engage with the customer in real-time across increasingly complex customer journeys.
The changing model for omnichannel really underscores how vital it is for retailers to weave personalization into an optimized path-to-purchase for the always-on, always-engaged retail consumer. The retailer that shows a customer they can recognize their preferences and deliver a superior omnichannel customer experience along every step of the customer journey will be in a far better position to attract and retain a loyal customer base.
National Retail Federation Conference 2019
In my presentation at the National Retail Federation (NRF) Conference next month, I will explore some of the innovative ways retailers can engage with the omnichannel consumer. NRF 2019: Retail’s Big Show begins Jan. 13 in New York, and many of the approximately 16,000 retailers and close to 40,000 attendees are trying to answer the same burning question: how can we optimize the path-to-purchase and market to a segment-of-one at scale when the traditional, linear customer journey is becoming a thing of the past?
The opportunities I’ll explore in greater detail at NRF 2019 that will help shine a light for marketers include some of the use cases RedPoint Global is helping retailers with today. These issues and challenges include buy online and pick up in-store, cart abandonment, product recommendations, mobile app push, and path-to-purchase optimization.
The following examples highlight some of the cross-selling use cases that a leading retailer is exploring to enhance brand recognition and loyalty, increase customer satisfaction, and deliver a superior customer experience across multiple touchpoints.
Buy online, pick-up in-store
Delivering a superior customer experience across multiple channels requires synergy between different portals. For the retailer that can eliminate data silos, the buy online and pick up in-store model presents an excellent cross-selling opportunity with great potential to deliver high customer satisfaction.
For a data-driven retailer, this could take the shape of providing a personalized online shopping experience based on previous purchase history, followed by the customer receiving a cross-selling discount coupon when picking up items in-store, based on the item purchased online. A customer who buys a bag of grapefruit, for example, might be presented with a 50 percent coupon for a juicer from another of the retailer’s brand when she arrives to pick up her order.
Generating fulfillment from an abandoned shopping cart is an age-old challenge for retailers who struggle to determine the winning follow-up formula, one tailored to the individual customer’s journey. According to research by Baymard Institute, $260 Billion is potentially recoverable through checkout optimizations. The challenge is compounded with trying to recognize the owner of the abandoned cart across multiple channels in real-time. Is the retailer prepared to present a next-best action for the customer who abandons an online shopping cart and shows up in-store within the hour? What is appropriate and what is creepy?
Envision a scenario where a customer abandons a cart because she hasn’t reached a limit. Personalized and relevant content could include a reminder email for cart checkout, with a savings code that drives the customer to fill the cart with additional items and encourages repeat purchases. This could help reduce the 69 percent of online users who never complete a purchase after adding a product to their shopping cart.
At a basic level, product recommendations are generally thought of in the context of recommendations based on purchase history or best-selling products. Cross-brand product recommendation engines take this category to the next level by analyzing a customer’s purchase history across sister brands and tailoring relevant recommendations accordingly.
It’s the grapefruit example in reverse, but instead of generating a coupon, a customer who buys a juicer from a sister brand might then shop the online grocery to discover a page of product recommendations that includes a mix of produce items. Or a customer who purchases a 70-inch TV just before the Super Bowl might be pleased to see product recommendations that include snack items and a recipe for nachos.
Mobile app push and in-app messaging
Mobile engagement is also an important way for retailers to drive engagement. With geo-fencing capabilities, the retailer could recognize the proximity of a recently lapsed customer and drive awareness with a mobile push message, encouraging a personalized in-app shopping experience based on previous purchase history. Personalized, relevant in-app messaging has been shown to lead to higher customer satisfaction, increased referrals, and higher retention.
According to Accenture, 91 percent of consumers are more likely to shop with brands who recognize, remember, and provide relevant offers and recommendations. With more consumers using the smartphone as a key shopping tool, getting mobile messaging right is an imperative. In the Customer Experience Tipping Point survey from earlier this year, more than half of all respondents said that it was important for brands to have a real-time response on the customer’s preferred channel of interaction, a frictionless flow of information between channels, and consistent levels of service across physical and digital channels.
For our data-driven retailer, path-to-purchase optimization extends beyond being able to provide a next-best action along an omnichannel customer journey. In this case, path-to-purchase isn’t just about recognizing the customer through interactions with a single brand, but through engagement touchpoints with various brands to maximize cross-selling opportunities throughout a customer lifecycle.
Let’s say the retailer offers a credit card and financial services, for example. An optimized path-to-purchase suddenly becomes a lot more complex, where a next-best action might factor in financing or interest rates in addition to cross-sell analysis across multiple brands and business units.
The examples shared here are not futuristic scenarios beyond most retailers’ wildest dreams. These are concrete, real-life examples of innovations that data-driven retailers are doing today to help shape the non-traditional customer journey. It all starts, of course, with data, and part of my presentation will focus on how marketers can use artificial intelligence (AI) and machine learning as allies in managing these opportunities to deliver a superior customer experience at scale.
With analytics, marketers can evaluate each customer at every step of the customer journey and always deliver the next-best action that has the highest propensity to result in a satisfied, and ultimately loyal, customer.
If you will be at NRF 2019 next month, come visit us at the NRF 2019 Big Show Expo Hall, Javits Center, Floor 2, Booth 841 or email Laura Ackerman (email@example.com) if you would like to schedule a meeting during the show!