Breaking down the conversational commerce model

Every day it seems there’s a new Assistant-for-X service, messaging-based business, or A.I.-powered chatbot. It can be difficult to keep up, so we wanted to put together a clean overview and a maintainable list. You can access the raw data and make suggestions at GitHub.com/ArgoHQ/List.

Above: Conversational services

Image Credit: Argo HQ

In defining our criteria for inclusion, we began by looking at Chris Messina’s foundational article on conversational commerce, where he offers the following definition:

[It] 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.

Let’s break that description down piece-by-piece:

Chat, messaging, or other natural language interfaces (i.e. voice)

The critical element of this new suite of services is that customers can now engage using natural language. It’s the difference between opening up the Uber app, navigating the UI, and tapping “Request Pickup” and simply declaring “I need a ride to this address” in Facebook Messenger.

The conversations can take place in established messaging channels (SMS, WhatsApp, Slack, Telegram, etc.), through IP messaging (in-app, web live chat), or even by using voice-enabled hardware (Amazon Echo, Siri, etc.).

Interacting with people, brands, or services and bots

The recipient on the other side can be another person, such as a therapist in TalkSpace; a brand, like Sephora on Kik; a service, like AndChill, which provides movie recommendations; or a bot, such as the Whole Foods recipe recommendation engine.

It can be completely staffed by humans, as with Sensay; fully automated, like Poncho’s weather bot; or it can take a hybrid approach — using humans plus A.I. tools and suggestions, as is the case with Operator.

In a bidirectional, asynchronous messaging context

These services provide two-way conversations, both grounded in natural language. This allows for a give-and-take dynamic; for instance, instead of navigating static gift recommendation lists, you can engage in a personal 1-to-1 exchange with a Mezi shopper to narrow your search.

The conversations can be asynchronous (“Amy, please schedule this meeting.”), not requiring an immediate answer, or they can take place in real time (“I like them, do you have a pair available in size 12?”).

Themes

Segmenting by industry, of course, isn’t the only useful way to organize these services. We also sliced them up by how they serve the parent company.

A few examples in each category:

New, messaging-enabled companies

The last few years has brought a sudden rise in companies inherently enabled by new messaging technologies. These aren’t services utilizing conversation as a form of customer support or an additional contact point; instead, these are companies built entirely around the dynamic of messaging.

Consider Magic or Awesome, text-message assistants that will take care of anything from desk research to travel plans. If you remove the conversational identity from these businesses, you unplug the entire service.

Established companies

We also looked at established companies dabbling in the promise of conversational commerce. The most basic example is achieved by simply using a messaging channel as a new interface for the core business: Order from Domino’s by texting a pizza emoji.

A more interesting and meaningful approach views messaging as fertile ground to try something new. Sephora has built a powerful bot (available on Kik) that hosts sophisticated interactions with customers. It can gather information about you and your shopping habits, offer tips and reviews about products, and even let you purchase items, all without leaving the messenger.

In this way, Sephora sees its product as a revenue-generating growth opportunity. This approach is not limited to fully automated chatbots. For instance, Bonobos has embraced live chat to connect shoppers with trained “Ninja” stylists, helping to improve the shopping experience and thus drive sales.

Tech companies adding a conversational channel

Between the two ends of the spectrum are tech-first companies that have added a supplemental messaging product or tie-in. They’re native to your phone or desktop, and they are working to add a conversational channel in order to achieve greater ubiquity. The messaging interface isn’t essential to their business, but it’s another useful way to interact with their core offering.

Take Uber and Lyft, for instance, which you can access directly within Facebook Messenger after clicking on an address. The service is folded into the messaging interface, but its output (the ride) is unchanged from the conventional hailing experience.

We put this list together because we wanted to inform our perspective on conversational services and improve our understanding of companies, bot frameworks, and best-practices within the space. Finally, if you’d like to make a suggestion or add another service to the list, head to GitHub.com/ArgoHQ/List.