ai and retail: 4 factors that will influence...
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SPECIAL REPORT
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THAT WILL INFLUENCEAdoption
AI AND RETAIL:
4 Factors
AI AND RETAIL: 4 FACTORS THAT WILL INFLUENCE ADOPTION2
“If there are three Victoria’s Secret stores within 15 minutes of each other, how can we use AI to differentiate and customize what happens in that particular store?”
- Joe Hasenzahl, High Street Collective
AI and machine learning have definitely moved from the realm of science fiction into retail fact. Brands already are using these technologies to improve operating efficiencies and the customer experience, and as many as 45% of retailers plan to use AI through either chatbots or digital assistants within three years, according to a survey from Boston Retail Partners (BRP).
Many retailers are leveraging AI for business processes that include tailored merchandising strategies, demographic targeting, personalized offers, inventory management and even expedited delivery and fulfillment. But there’s even more that AI can contribute. This special report will reveal:
• Why retailers should begin AI implementations focused on basics such as product recommendations;
• The long-term projected benefits from AI implementation, including: higher customer satisfaction, increased conversions and higher revenues;
• How the growth of mobile will spur widespread AI adoption;
• How Mall of America leverages chatbots to bridge AI with human concierges; and
• How company culture can hold back successful AI deployment.
As virtual assistant platforms such as Siri and Alexa continue to gain popularity, more consumers are becoming comfortable with AI technology in their everyday lives. This gives retailers a golden opportunity to bring machine learning and natural language processes into their ecosystems, whether in the retail store or online. Used effectively, AI can facilitate personalization and store-level localization, according to industry experts.
For example, “If there are three Victoria’s Secret stores within 15 minutes of each other, how can we use AI to differentiate and customize what happens in that particular store and make it a different experience from one right down the street?” asked Joe Hasenzahl, Principal Consultant, Technology Strategy at High Street Collective, in an interview with Retail TouchPoints. “We can start to take all this information that comes from social, traffic counts and the POS to personalize the product assortments and even store layouts, based on the people that are actually shopping there. That’s where I think AI can really start to demonstrate use to retailers.”
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“Don’t try to solve every single personalization issue at once, but understand what moves the needle and start there.”
- Shelley Bransten,
Salesforce
THINK BIG, START SMALLAI already has benefitted retailers in the most basic ways. Shoppers who have accessed an AI-driven product recommendation spent an average of 12.9 minutes on a site vs. just 2.9 minutes for those who didn’t click recommendations, according to data from Salesforce. And “basic” is still the best way to start, particularly for retailers that are new to AI technology.
“One of the biggest pieces of advice I give to our retailer customers is ‘think big, start small,’” said Shelley Bransten, Senior VP of Retail Industry Solutions at Salesforce. “If it’s about creating a more personalized journey from discovery to browse to purchase, then get after that. Don’t try to solve every single personalization issue at once, but understand what moves the needle and start there. People often get so caught up in the task at hand that they don’t just start with test and learn. All the great brands now have this understanding that they’re testing alongside the consumer.”
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“By 2019, 40% of retailers will have developed a CX architecture supported by an AI layer.”
- IDC RETAIL INSIGHTS
AI BOOSTS CONVERSIONS, REVENUE AND CUSTOMER SATISFACTIONRetailers will take big steps toward AI adoption within the next few years, and reap significant benefits from these digital transformation efforts, according to IDC Retail Insights. By 2019, 40% of retailers will have developed a CX architecture supported by an AI layer. These platforms will enable hyper-personalization across the CX; IDC estimates that they will provide up to 30% conversion increases and 25% higher revenue.
When combining AI with augmented reality (AR) and IoT platforms, retailers will improve the experience for both consumers and employees. Through 2021, IDC forecasts that retailers leveraging these three technologies for employee and customer engagement will see:
• Customer satisfaction scores rise by up to 20%;
• Employee productivity rise by up to 15%; and
• Inventory turns rise by up to 25%.
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150 MILLION SHOPPERS PROVE THE OUTSIZED IMPACT OF AI ON RETAIL AND REVENUEBy Heike Young, Manager, Industry Strategy & Insights at Salesforce
Revolutionary change in retail has become as unsurprising as a store associate asking you for your email address.
And with artificial intelligence (AI) shaping a bigger share of everyday consumer experiences — from trusting Siri for navigation to relying on Netflix for binge-worthy TV suggestions — it’s clear that AI will drive the next wave of change.
Rather than wait for the fallout, many retailers are getting ahead of the machine- learning curve and applying these technologies in their customer touch points, including unique product recommendations, dynamic email and web site content, and personalized pricing.
Based on analysis of the shopping activity of 150 million shoppers across 250 million site visits on the Commerce Cloud platform, personalized product recommendations have emerged as one of the best tools for driving revenue in a retailer’s toolkit. Take a look at data from Salesforce’s Personalization in Shopping report to understand the material impact of personalization.
PERSONALIZATION IS A REVENUE POWERHOUSE
Back in 1999, Amazon gave customers book recommendations based on previous purchases, giving many their first taste of digital personalization. But product recommendations have come a long way since then.
These ‘you-might-also-like’ suggestions might be the unsung heroes of the product detail page. The numbers prove it:
• Product recommendations drive revenue. E-Commerce site visits where a shopper clicked a recommendation comprise just 7% of all visits — but that small portion of visits drove 24% of orders and 26% of revenue.
• Shopper spend soars with personalization. The per-visit spend of a shopper who clicks a recommendation is five times higher.
• Recommendations lead to longer shopping visits. Shoppers that clicked a product recommendation spent an average of 12.9 minutes on-site vs. 2.9 minutes for those that didn’t click recommendations.
Bottom line: personalization drives sales. And for e-Commerce sites with unwieldy product catalogs browsed by distracted shoppers, that’s great news.
E-Commerce site visits where a shopper clicked a recommendation comprise just 7% of all visits — but that drove 24% of orders and 26% of revenue.
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PERSONALIZATION WINS ACROSS DEVICES
In micro-moments — those brief blips of time between activities when a shopper checks her phone — personalization connects on-the-go shoppers with ideally suited products in short order on small screens.
Fortunately, our data shows that personalization gets results across devices: Mobile shoppers that click recommendations complete orders at a higher rate than desktop shoppers (25% vs. 23%, respectively). And although tablet sales and usage has slowed in recent years, tablet shoppers that clicked a recommendation accounted for 30% of total tablet orders and 33% of revenue, despite comprising only 9% of total visits.
Still, visits by computer shoppers that click recommendations are strongest when it comes to visit duration (15 minutes on average), conversion rate (9.8%), and their propensity to create a basket (24% do so). Every device benefits from a personalization strategy.
AI-POWERED PERSONALIZATION IS IN REACH
If you’re not already realizing the benefits of intelligent recommendations, you’re missing a major revenue opportunity. Even if you’re using recommendations, you can probably improve your strategy. Here’s how:
• Start with clean data. This isn’t a once-and-done effort; make data quality priority #1 over the long term.
• Lean on AI for tactical execution. Despite the headlines, AI isn’t here to replace you. Instead, allow tactical and micro-level decisions to be made by machine learning so you can focus on strategy and problem-solving.
• Optimize for mobile. Make sure product recommendations are easily visible and engaging on small screens. With 7% of visits driving 26% of revenue, you don’t want this powerful tool at the bottom of a mobile page.
• Think outside the “you might also like” box. For example, outfitter Johnston & Murphy says, “Recommended by Em, our style expert.” Use copy and design to help these recommendations jump off the page.
• Incorporate recommendations outside the PDP. Seek other places to show customers 1:1 suggestions: category pages, empty cart, emails, social ads, and beyond.
AI is changing the game for meeting shoppers’ needs in an intuitive, inherently 1:1 way. Because intelligence grows over time, you’ll be offering even smarter shopper journeys a year from now. That is, if you start today.
Computer shoppers that click recommendations are strongest when it comes to visit duration (15 minutes on average), conversion rate (9.8%), and their propensity to create a basket (24% do so).
Download the Salesforce Personalization in Shopping report for more details on crafting seamless and intelligent journeys, no matter what the future of AI holds.
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“Shoppers who click a product recommendation after searching on a mobile site are 4.2X more likely to convert than those who only search.”
- Salesforce
MOBILE WILL HELP AI FLOURISHAs more shoppers continue to demand personalized experiences, retailers will benefit from integrating AI at every step. With the start of the 2017 holiday season confirming that mobile is becoming more important by the day, it makes sense that mobile will be the next major touch point for AI.
Leveraging the fact that mobile devices are used primarily for personal activities, retailers will be able to gather more relevant data and shopping history information to help improve the customer experience.
Starbucks has been at the forefront of this strategy, adding an AI platform to its mobile app. Within the app, AI allows customers to place their orders via voice commands or a messaging interface. The platform also uses algorithms to recommend specific orders, accounting for factors such as order history, current weather conditions, time of day, day of the week, and even if it’s a customer’s birthday.
Starbucks is taking advantage of the fact that AI-driven mobile product recommendations actually outperform those from other devices. Shoppers who click a product recommendation after searching on a mobile site are 4.2X more likely to convert than those who only search. This conversion increase is 3.7X across all devices, according to the Salesforce report.
“Given the smaller form factor of the mobile device, shoppers who clicked on and engaged with recommendations spent more time shopping than those who didn’t get a recommendation,” Bransten said. “These technologies are all coming together. Given how important mobile is as the first screen for mobile shoppers, embedding AI in those experiences to drive the shopper, to convert, to drive average order size and also spend time with your brand is a big takeaway.”
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MALL OF AMERICA CHATBOT MERGES AI WITH HUMAN CONNECTIONEven as consumer familiarity with AI climbs, it’s still vital for retailers to deliver a human “feel” when using AI — particularly when any kind of customer support is needed. As many as 60% of shoppers want AI to provide human-like recommendations for automated customer support/advice, according to a survey from Infosys.
Mall of America recently launched a chatbot designed to integrate the human and AI experiences, making it accessible via its web site, mobile app, Facebook page and even as an Amazon Alexa skill. The platform, developed by Satisfi Labs, is designed to:
• Provide directions to all the stores, restaurants, attractions and services based on the user’s current location, using Mall of America’s location API;
• Answer customer inquiries on deals and holiday events in the mall; and
• Recommend the mall’s top gift items and brands, as well as direct the user on which stores these brands are located in.
If shoppers can’t find the answers they are looking for through the chatbot and need a more in-depth conversation, they can connect with a human concierge in real time for a 1:1 conversation.
“We’re able to see through Satisfi’s chatbot portal where guests are falling off or getting a suboptimal experience,” said Sarah Townes, VP of Marketing at the Mall of America in an interview with Retail TouchPoints. “It gives us the ability to immediately connect them with our digital guest service representatives. For us, there’s this technology solution on the front end, but there’s still that personalized high-touch experience on the back end, if needed.”
Justine Santa Cruz, VP of Strategic Partnerships and Alliances for Satisfi Labs, noted that in developing the chatbot, the company sought to eliminate barriers to entry often associated with the technology. With natural language processing, shoppers don’t have to type in specific keywords, and can instead ask appropriate questions.
“We did all the heavy lifting in terms of interpreting what shoppers’ words meant, what the customer’s intent actually is and then matching that up to the right answer every time,” Santa Cruz said. “The first thing that was important to us was to start with the user, and build our AI based on how they actually interact and what’s most helpful to them.”
The success of the bot hinges on the fact that the technology has access to dynamic feeds, including every shopper request. Therefore, the chatbot pulls answers from a data source and presents them in real time.
“If a customer asks, ‘Where can I buy a gift for my mom?’ then we actually have a data source that gives us the top retailers in the mall that sell gifts for the holidays,” Santa Cruz noted. “From a retail perspective, that’s really important because there’s no way a single person could know all that information at the touch of their fingertips. That’s where bots are going to be the most helpful in a mall setting — getting all that directory information, all the food and dining attractions and displaying that to the customer in an instant.”
“If a customer asks, ‘Where can I buy a gift for my mom?’ then we actually have a data source that gives us the top retailers in the mall that sell gifts for the holidays.”
- Justine Santa Cruz, Satisfi Labs
CASE STUDY: MALL OF AMERICA
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MY TRAILBLAZER STORY: IAN MARQUIS, ECOMMERCE MANAGER, STONEWALL KITCHEN On the web site Creative Portland, a non-profit agency supporting the arts in Portland, Maine, Ian Marquis described himself like this: “I make things. Sometimes practical. Sometimes beautiful. Always interesting.”
Among the interesting things Ian makes are music (he’s got five independent albums to his credit), copious amounts of digital art (his extensive portfolio “sits at the crossroads of procedure, aesthetic and intent”) and, as eCommerce Manager of Stonewall Kitchen, a beautifully-functioning web site.
Ian has been blazing trails in music and the digital arts for almost two decades, and he’s been blazing new trails in commerce since he joined Stonewall Kitchen, a 25-year old specialty food producer, in late 2015.
“The drive to create art in one form or another has been a big part of my identity for as long as I can remember,” Marquis said. “Although I initially considered pursuing computer science as a focus due to my love of logic, problem solving, architecture and interactivity, I ultimately received my BA in New Media, which gave me a strong full-spectrum introduction to the space that I still inhabit as a professional to this day.”
Ian brings an artist’s sensibility to the form and function of Stonewall Kitchen’s digital storefront, looking at customer interactions not in isolation as a sales conversion or interaction point but as “moments that can come together to create something bigger, more emergent and ultimately more satisfying, both to the customer and to us as e-Commerce professionals.”
“Salesforce has contributed enormously to my growth both as an analytical person, a creative person and an e-Commerce professional,” Marquis said. “The relationships I’ve formed with division, project and team leaders, the Salesforce Commerce Cloud Retail Practice team, and fellow Commerce Cloud Digital customers have pushed me to broaden my strategic thinking, given me new insight and perspectives into both my industry and the digital space as a whole, and are a continual source of inspiration and challenge to grow.”
One example: offering its online customers the same level of personalized service they may get in one of its stores.
Both channels carry the full gamut of Stonewall Kitchen products: salsas and syrups, preserves and pastas, beverages and baking mixes, and much more. With such a diverse (and delicious) array of products, it’s important that customers not get overwhelmed, and find exactly what they are looking for quickly and easily.
“Artificial intelligence is a feature we knew would be increasingly important in e-Commerce,” Marquis said. With a five-person e-Commerce team, Stonewall Kitchen is able to leverage Commerce Cloud Einstein to power 1-to-1 personalization without hours of manual merchandising or segmentation — and without a data scientist.
Marquis looks at customer interactions not in isolation as a sales conversion or interaction point but as “moments that can come together to create something bigger, more emergent and ultimately more satisfying.”
CASE STUDY: STONEWALL KITCHEN
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Stonewall Kitchen uses Einstein to serve as a virtual sales assistant for online shoppers, offering them unique product recommendations based on their browsing history and preferences. They use Einstein to fill gaps in the customer journey that they can’t bridge with their own expertise or manpower.
For example, if a shopper hits any curated story on its web site, Stonewall Kitchen leverages AI to show shoppers complementary add-ons; a breakfast story would include pancake mix, jam or a syrup.
“It might not be the one that my team would’ve picked, but it’s going to be one that will resonate, because the data says that it will,” said Marquis. “We’re comfortable with Einstein serving an experience that we can’t always fully control. No one knows our brand better than we do, but Einstein enables digital depth, variety and novelty of experience that we couldn’t deliver consistently otherwise.”
Einstein Product Recommendations influenced 14% of customer purchases during the summer of 2017, driving an average conversion rate of 44.3% and an average add-to-cart rate of 39.6%.
“Salesforce technology has enabled my team to be highly agile in creating incremental strategic improvements to our e-Commerce experience, even as we hold down the fort with business-as-usual projects,” Marquis said.
There’s nothing business-as-usual about Marquis’ approach to creating customer experiences online. In fact he sees it as his responsibility to create extremely nuanced, subtle experiences that render conversion virtually effortless.
“We serve the right experience to the right person at the right time, and we let conversion just happen,” Marquis said. “We can’t possibly design all of that level-by-level; the experience will be shallow, forced, and transparent to the customer. Instead, I think our real challenge is to build models for customer interaction, and for serving up commerce experiences that are robust enough to fill in the blanks. That’s an enormous challenge, but it’s one that genuinely excites me.”
A crucial cog in that wheel is the partnership with the Salesforce Commerce Cloud and its Retail Practice team, which he says has played a “huge role” in helping the company prioritize feature improvements and experience iterations, benchmark its performance against best practices and Salesforce customers as a whole, and much more.
All along, Stonewall Kitchen has been a fast mover, and unafraid of failing. “I’d rather we do something interesting and flawed today than wait until next year to do something better,” Marquis said. “We can always learn from the flaws in our first iteration, but we can’t always make up for lost time if we delay ideation in search of the perfect.”
At the heart of it all, Ian says, is practical but beautiful design, a completely holistic approach to customer engagement - and inspiration.
“Because of Salesforce, I am continually inspired to create better, smarter, more out-of-the-box experiences, and am enabled to actually do that.”
CASE STUDY: STONEWALL KITCHEN
“I’d rather we do something interesting and flawed today than wait until next year to do something better.”
-Ian Marquis, Stonewall Kitchen
For more insights about using AI and personalization to power the shopping experience, download the Salesforce Personalization in Shopping report.
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“The biggest roadblock comes in the form of cultural readiness within the organization.”
- Joe Hasenzahl, High
Street Collective
LACK OF IN-HOUSE KNOWLEDGE AND CULTURAL READINESS HOLD BACK AI ADOPTIONAt the moment, there are some significant barriers holding retailers back from deploying AI, according to the Infosys survey:
• 61% lack in-house knowledge;
• 52% lack financial resources; and
• 47% lack a clear implementation plan for AI.
This lack of in-house knowledge often comes from organizational issues, especially when disparate departments haven’t worked together to understand how AI can be implemented within the company.
“The good news is that the tech is affordable,” Hasenzahl said. “The processors can keep up and we’re at the point where AI can really contribute. The biggest roadblock comes in the form of cultural readiness within the organization. This is truly where everybody needs to start to come together. Merchandising has to be open to the idea that maybe the way they’ve always done it isn’t the way that’s resonating with new shoppers in the marketplace. This idea of cultural readiness is a much bigger stumbling block than the technology itself.”
Retail TouchPoints is an online publishing network for retail executives, with content focused on optimizing the customer experience across all channels. The Retail TouchPoints network is comprised of a weekly e-newsletter, special reports, web seminars, exclusive benchmark research, an insightful editorial blog, and a content-rich web site featuring daily news updates and multi-media interviews at www.retailtouchpoints.com. The Retail TouchPoints team also interacts with social media communities via Facebook, Twitter and LinkedIn.
The Salesforce Commerce Cloud empowers retailers to unify customer experiences across all points of commerce, including web, social, mobile and store. From shopping to fulfillment to customer service, the Commerce Cloud delivers 1-to-1 shopping experiences that consistently delight customers, driving increased engagement, loyalty and conversion. With embedded predictive intelligence and a robust partner ecosystem, the Commerce Cloud delivers customer satisfaction and growth from planning to launch and beyond.
Salesforce Commerce Cloud is part of the world’s #1 CRM platform. Salesforce, the global CRM leader, empowers companies to connect with their customers in a whole new way. For more information about Salesforce (NYSE: CRM), visit: www.salesforce.com.
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