Retail news is again awash with new buzzwords. Retail clients and media have asked many terrific questions about conversational commerce, the latest trend in high-tech retail. These questions include:

“What is conversational commerce?”
“What are
chatbots, and what do they have to do with retail?”
“What are message platforms, and how are they different from social networks?”
“Is this somehow related to AI or machine learning?”
“Is a chatbot the same thing as Amazon Echo?”
“What is Kurt Salmon’s perspective on this relative to our clients?”

Conversational commerce refers to the emerging use of text/message platforms to conduct retail. You have probably seen commercials of pizza-ordering emojis and the like. If you haven’t tried a retail-based message platform, try typing “Whole Foods” into Facebook Messenger. (If you don’t have Facebook Messenger, get it.) Within seconds, you can interact with Whole Foods’ simple chatbot to find a recipe so that you can use some of those ingredients sitting in your pantry.

A chatbot refers to the automated system (as­sisted intelligence/AI) that receives the customer’s chat message. This bot interprets the request and then answers or refers the message to a human to answer.

“What are message platforms, and how are they different from social networks?”

You’ll notice I didn’t ask for recipes for black beans on my Facebook wall, where I could have polled everyone I have “friended” and waited for their response. Instead, I used the social network’s Mes­senger platform, which allowed me and Whole Foods to have an immediate and direct conversa­tion—private from the rest of my Facebook social network. One-to-one communication is the essence of a message platform. Siri, Google Allo, Amazon Echo, Google at Home, WeChat, SMS text, etc., are all message platforms.


What Do Chatbots and Message Platforms Mean to Retailers and Brands?

If you try the Whole Foods example yourself, you’ll quickly experience how limited/early a current chatbot feels. However, imagine the many ways you’d like to use it:

Could it …

Read the recipe instructions to me through my Echo?
See my specific ingredients via my camera?

Show me recipes/products based on my wellness/nutrition plan?
Tell me which products are highest rated by my Yummly friends?
Order the missing ingredients I need to complete this recipe?
Connect me to a personal cooking coach who can teach me how to perform a new technique?

One possibility you can quickly envision is an explosion of connections that enable a meaningful, ongoing, private one-to-one conversation between you and your trusted retailer/brand … but only if the retailer can implement an AI chatbot to provide meaningful answers to individual customer ques­tions. They are not YET ANOTHER new platform. Chatbots and their foundational AI systems are how we will evolve the future of all digital-supported retailing.

Why Now?

The volume of these types of questions from our clients rose this summer, particularly spiking after BI Intelligence’s chart showing message app usage surpassing that of social networks made headlines. The messaging platform that passed Facebook (and others) was WeChat. WeChat is largely limited to China, so this news was more of a wake-up call for the United States’ and Europe’s future than a reflec­tion of what exists today. However, this data coin­cided with significant announcements by Facebook, Google and Apple that they were releasing open integrations for each of their messaging/AI plat­forms: Messenger, Assistant and Siri.

Simultaneously, while funding and valuations for e-commerce startups fell off a cliff in 2016, early rounds and strategic acquisitions of chat/AI tools and platforms exploded. As we’ve seen over the last decade, where innovation capital invests, traditional retail will have to follow—begrudgingly and cau­tiously maybe, but sure enough in the end.

Why Does Conversational Commerce Matter?

Digital (non–brick-and-mortar) commerce has gone through several evolutionary steps; each has led to large shifts of consumer spending preference by channel. While purchases specifically from digital channels have grown to only 8% overall, the per­centage across many product segments of retail is many multiples of that, with estimates that more than 60% of ALL purchases are first influenced by visits to a digital channel.


Clarifying the new language...

Conversational Commerce: Largely pertains to utilizing chat, messaging or other natural language interfaces (i.e., voice) to interact with people, brands or services and bots that heretofore have had no real place in the bidi­rectional, asynchronous messaging context.

Chatbot: A type of conversational agent; a computer program designed to simulate an intelligent conversation with one or more hu­man users via auditory or textual methods.

Social Network: A dedicated website or other application that enables users to com­municate with each other by posting infor­mation, comments, messages, images, etc.

Message Platform: Online chat systems that support real-time text transmission. Source may be text platforms or emerging natural language platforms.

AI/Assisted Intelligence: Artificial intelli­gence system that involves the taking over of monotonous, mundane tasks that machines can do more efficiently than humans.


So How Is Conversational Commerce Different?

Retail adoption of message platforms is not the real message here. What is important is that emerging AI-supported message handling tools will be able to deal with 80% to 90% of all customer interactions. After all, retailers will not be able to scale one-to-one customer communications if they have to hire live associates to handle every individual request. This connection to customers through both text and voice channels differs dramatically from their pre­decessor digital platforms (internet browsers and mobile apps/web) in one significant way: Previous digital platforms began as document-sharing tools, HTML specifically. Yes, those websites and apps act dynamically to tailor their underlying framework/document based on the visitor, but they still remain one-to-many communication tools. From inception, message platforms serve as one-to-one communi­cation tools.

From a technology standpoint, this is a tremendous shift. Historically, digital offerings have been static solutions designed, built and implemented over multiple years. The results are monolithic software solutions—from e-commerce sites to mobile appli­cations—that reflect how the retailer “hoped” would best serve the most customers. Changing these systems took additional months or years, making retailers less than responsive to the evolution in cus­tomer behaviors, preferences and market conditions.

This new AI-embedded environment will be adap­tive. Even today’s early version AIs can learn from customer requests, and machine learning can advance in real time. Beyond just understanding whether it answered the customer’s question cor­rectly, an AI-bot’s learning can extend to the best techniques to funnel the customer toward conver­sion and apply that learning to the next customer interaction. With adaptive technology as its founda­tion, individualized retail communications will erode share from channels that are not individualized, whether digital or brick-and-mortar.



1:1 Individualized Retailing involves more than tailored websites/recommendation engines and shrinking segment sizes for email campaigns. The next generation of 1:1 Retailing requires rethinking how to apply strategies like pricing, promotion and marketing in a future retail environment where the customer (or their bot) will often start customer-brand communications instead of the retailer. Customers will expect personal responses to what has traditionally been handled at the market level: pricing, promotions, services, availability, etc.

The Future Platform

We won’t get to this dreamy future overnight, but it is important to have a larger vision of what Individu­alized Retailing will look like when fully developed in order to prioritize the essential components. So what are the building blocks of an individualized conversational retail platform?

  1. Engage the Customer

The first step that all retailers/brands will take is to create simple AI chatbots to engage custom­ers through their favorite message platform. Many already have. Like the Whole Foods example earlier, engagement strategies can be as simple as providing recipe content or a process to reorder the customer’s favorite pizza by using an emoji (Pizza Hut).

Facebook, Apple, Google, Amazon, etc., all offer development tools and templates to build interactions. However, building interaction with each new service is unscalable. Emerging AI engagement bots allow retailers to develop as­sisted- response systems that do three things:

a. Connect quickly to multiple bot platforms

b. Reuse the functionality that they will or already have built within their enterprise systems

c. Expand quality of service as new message platforms and environment sensing (IoT) support is added

All will be essential for retailers/brands to build and manage the increasing number of integrations required to keep up with customer communication preferences.

  1. Engage the Enterprise

The second step for most retailers/brands will be to increase the usefulness of these interac­tions. Instead of just providing the customer with a chicken recipe, the AI platform will know that …

My friends preferred the chicken marsala recipe.

The ingredients meet my dietary preferences.

My preferred location can have my missing ingredients packed and delivered to my house to be ready for use this evening.

Amazon Echo is exploding in market share be­cause it is useful. Every month that the device spends in your home makes it harder to switch away from the platform because the Echo learns your preferences and habits.

Initial AI-enterprise connections will be rela­tively simple look-ups of product content, store locations and generic promotions. However, the development of useful as well as profitable connections will be an arms race. As retailers become sophisticated with conversational commerce, the bar will rise quickly to more complex interactions that use analytics to drive INDIVIDUALIZED customer offers and recommendations. For example, instead of just providing the customer with a chicken recipe, the AI platform will …

Know that I’m a loyalty member.
Connect to the inventory position at my local store.

Suggest that I pair dinner with my preferred pinot noir using my loyalty benefits.
Individualized offers won’t just drive better answers for the customer, they will drive better financial performance for the retailer.

  1. Engage the Digital Workforce

Lastly, retailers will connect customers directly with digitally enabled employees. In this case, an enterprise AI-platform will serve both the customer and the associate:

The Customer: By making the appropriate useful connection

The Associate: By providing individualized ser­vices, promotions and loyalty benefits available to the customer in a manner easily actionable in the moment

For decades the industry has advocated for reworking physical stores to be centers for engagement, but with few exceptions, we have progressed very little. Store engagement still exists largely as an anonymous experience and often relies heavily on a high-turnover/reluctant workforce that is not empowered to best repre­sent the brand.

As customers grow their willingness to engage with retailers individually through these AI/mes­sage platforms and retailers provide customers the value to make it worth doing, expect a growing share of retail space to be devoted to value-added services, facilitated by a digitally connected and, most importantly, an EMPOW­ERED workforce.



The world’s largest tech companies own these mes­sage platforms and will continue to invest in scaling these popular communication tools regardless of individual retailer adoption. Unlike apps in 2010, the channels/technologies necessary to communicate with chatbots already exist on every customer’s smartphone, so there is likely to be a first-mover advantage to any retailer/brand that builds early conversation services, invests to grow the function­ality and integrates this technology and 1:1 Individu­alized Retailing into their offerings. Retailers will need to tackle three key hurdles to succeed:

  1. Technical Capability (CRM, Analytics, Innova­tion Labs, Etc.): While the basic concepts be­hind chatbots are fairly simple, architecting and “training” the AI system to deliver in a way that is conversational, personal and that passes the “Turing Test” with the consumer is something entirely different.
  2. Organization: This new world of conversational commerce will force the retail organization to rethink how it performs all of its functions—mar­keting, ordering, customer service, merchandis­ing, pricing, inventory and fulfillment. These functions will need to be integrated and ex­posed to the customer in near real time. Orga­nizations with divided ownership of their digital and physical experiences will continue to be significantly disadvantaged.
  3. Customer Experience Strategy: Kurt Salmon’s Brand Devotion Index research shows that highly devoted customers spend nearly 50% more than average customers and that devo­tion happens when the brand feels authentic, tribal and personally valuable to the customer. Measuring what makes customers feel personal devotion and designing meaningful individual­ized digital and physical retailing experiences that drive customer devotion and loyalty are beginning to be possible with these new tools.

This next evolution in retail will be a big step for even the most advanced retailers, but Kurt Salmon can help. If you or your organization would like to talk about conversational commerce, chatbots or AI technology, please contact Kurt Salmon’s subject matter experts.

16 März 2017