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It’s Easy for Customers to Leave the Digital Path to Purchase

June 26, 2018


Thanks to smartphones, the digital path to purchase has become the preferred consumer journey in the United States. Sandy Skrova reports, “Roughly three-quarters of Americans own a smartphone today, according to Pew Research Center, and many are being used to research products, compare prices and download coupons, among other things, while shopping in a physical store. In fact, digital interactions now influence 56 cents of every dollar spent in brick-and-mortar stores, according to Deloitte Consulting.”[1] Other countries with high smartphone penetration are probably witnessing a similar phenomenon. Although the digital path to purchase opens new avenues to reach potential customers, it’s a path easily abandoned if consumers have a bad experience. According to analysts from Linnworks, “89% of consumers refuse to deal with brands after experiencing poor customer service.”[2]


A Path easily Abandoned


In a famous Robert Frost poem entitled “The Road Not Taken,” the final verse reads:


I shall be telling this with a sigh
Somewhere ages and ages hence:
Two roads diverged in a wood, and I—
I took the one less traveled by,
And that has made all the difference.


Retailers don’t won’t potential customers to sigh or take the road less traveled. They want them to continue on the path to purchase and they want them to travel that path time and again. Keeping them on the path is what makes all the difference to retailers. To achieve that goal, retailers must ensure consumers have a good digital experience. Dan O’Shea reports, “Consumers are getting pickier: 48% of 8,000 consumers surveyed by Accenture Interactive said they have left websites because shopping experiences were poorly curated, according the consulting firm’s 2018 Personalization Pulse Report. And, as Linnworks analysts reported, once a consumer has left the digital path as a result of a bad experience with a retailer, he or she will likely never return. Karen Sage (@KarenSage4), MercuryGate’s Chief Marketing Officer, writes, “Companies retain customers by providing good service and poor customer service results in lost business. Further, the cost of acquiring new customers is much higher than maintaining positive relationships with existing customers. Data consistently supports these theories. A Business Insider Intelligence Report about customer service states that 66 percent of U.S. consumers are willing to spend more money with a company that provides excellent customer service. However, up to 60 percent of potential consumers have not completed an intended purchase because of a poor customer service experience.”[4]


Personalization and Good Consumer Experience


Linnworks analysts assert, “Big data allows businesses to optimize their customer service. By compiling data from previous online interactions, social media information, and purchase history, the business can create a 360 view of the customer. Big data makes it possible to create this enriched view and empowers customer service teams to provide an enhanced customer experience.” While that is true, there is a fine line between personalization and creepiness. O’Shea reports the Accenture survey found “35% of consumers surveyed admitted to getting creeped out when they see ads on social networking sites for products they earlier viewed on a brand’s website.” Nevertheless, O’Shea reports, “Shoppers want some level of personalization or curated shopping experiences. As the Accenture report further showed, 91% of those surveyed said they would be more likely to shop with brands who recognize and provide relevant offers and recommendations, and 83% said they were willing to share their data to make this work.”


As Linnworks analysts noted, the key to personalization is big data. Challenges associated with big data include volume, variety, and velocity. Those challenges mean manual analysis of the data is no longer a viable option. Fortunately, advanced analytics platforms, like cognitive computing platforms, are capable of dealing with the various types of data needed to personalize customer experiences. Cognitive computing is a sub-set of artificial intelligence (AI) and it can help with lots of business challenges. Lisa Loftis (@lisamloftis), Principal management consultant with the SAS Best Practice team, notes, “In the context of digital transformation and customer experience, artificial intelligence already has a foot in the door. And that foot is poised to kick the door wide open. IDC predicts that by 2019, 40 percent of digital transformation initiatives will be supported by some sort of cognitive computing or AI effort. Servion predicts that AI will power 95 percent of all customer interactions by 2025, and it will do it so effectively that customers will not be able to ‘spot the bot.’ Gartner says that 85 percent of customer relationships will take place without human interaction by 2020.”[5]


Anil Kaul (@anil_kaul), CEO of AbsolutData, claims there are three parts to a successful customer engagement formula: Decision Engineering + Advanced Analytics + Cutting-Edge Technology.[6] He defines those components this way:


  • Decision Engineering: “Marketers typically streamline data, then analyze it for insights to aid decision-making. A decision engineering approach turns that process on its head, identifying decision opportunities first, then conducting analysis and using technology to develop scalable, sustainable customer engagement campaigns.”
  • Advanced Analytics: “Smart algorithms and sophisticated analytics are a must-have in today’s marketing toolkit. With advanced analytics, marketers can increase customer engagement by segmenting customers based on their lifestyles rather than demographics. This allows marketers to target customers more efficiently and effectively.”
  • Cutting-Edge Technology: “Advanced technologies like artificial intelligence can help marketers take the friction out of interactions with the brand, which improves sales. Chatbots, for example, allow customers to interact with brands on their own timetable. The use of chatbots is mainstream thanks to the convenience they offer and widespread customer acceptance.”

Although Loftis agrees AI is an important new tool in the marketer’s kit, she believes the human touch is required to prevent PR disasters and disgruntled customers. She explains, “Despite the dire predictions and well-publicized missteps, AI — when implemented correctly — can be a great boon to customer experiences and digital transformations. AI can improve response time, provide contextually relevant personalized recommendations, incorporate sentiment into responses, eliminate bottlenecks and automate routine inquiries, freeing up humans to deal with more complex problems. In all cases, a blended approach — one that combines man and machine — is the key to avoiding missteps and viral mistakes.” Her best advice is: “Don’t chase the cost savings so far that you risk lowering customer satisfaction. Relying on bots to handle too many interactions, particularly those involving complex problems, can cause frustration for both customers and the human agents who must eventually deal with them.”




Cognitive technologies can help retailers and their marketers present the right product to the right customer at the right time. However, getting too personal can push consumers away. The Accenture study found, “Eighty-three percent of consumers are willing to share their data to enable a personalized experience as long as businesses are transparent about how they are going to use it and that customers have control over it. … Of the 27 percent of consumers who reported a brand experience that was too personal or invasive, almost two-thirds (64 percent) say it was because the brand had information about the consumer that they didn’t share knowingly or directly, such as a recommendation based on a purchase they made with a different business.” As I noted above, there is a fine line between personalization and creepiness. Cross the line and you will find out just how easy it is for a consumer to abandon the digital path to purchase.


[1] Sandy Skrova, “How shoppers use their smartphones in stores,” Retail Dive, 7 June 2017.
[2] Danny Asling, “6 Ways to Use Big Data in Ecommerce,” Dataconomy, 14 July 2017.
[3] Dan O’Shea, “Consumers walk away from poorly personalized experiences,” Retail Dive, 9 May 2018.
[4] Karen Sage, “Is it Time for Businesses to Rethink Path to Customer Satisfaction?Logistics Viewpoints, 30 January 2018.
[5] Lisa Loftis, “The Future of Customer Experience Is AI: Are You Ready?CMS Wire, 9 April 2018.
[6] Anil Kaul, “Three Components of a Data-Driven, Future-Focused Customer Engagement Strategy,” Marketing Technology Insights, 26 April 2018.

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