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Growing Your Conversational Commerce Capability

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How to Optimize the Latest Major Digital Touchpoint

Growing Your Conversational Commerce Capability

GUEST POST from Howard Tiersky

Conversational commerce means interacting with your customer in an automated dialog via voice or text.

Usage of voice-based conversational interfaces such as Alexa and Siri have been exploding for years. Meanwhile, over 100,000 active bots were created on FaceBook’s messenger platform during its first year several years ago.

“Digital” began to truly scale with the web, then expanded even further via apps and social. Is conversational commerce (CC) the next major touchpoint? Conversational commerce is defined as interacting with your customer in an automated dialog via voice or text. Based on our experience consulting large brands on the implementation of their digital innovations, and given trends on consumer adoption and technology-readiness, it is fair to say that we are at the dawn of the first wave of the broad implementation of conversational commerce.

For several years, IBM has been painting a fanciful picture of its Watson technology’s ability to digest volumes of information, understand questions, and provide truly insightful answers. Meanwhile, consumers are becoming more and more comfortable with dialog-style interactions via Siri, Google voice search, and Alexa.

In fact:

  • The number of commands (“skills”) that Alexa can respond has increased past 100,000
  • 34 percent of all smartphone users say they turn to Siri and Google voice search at least weekly.

But conversational commerce does not necessarily have to involve voice recognition.

2017 represented the one-year anniversary of the launch of Facebook’s chatbots, which enable brands to engage in text-based automated interactions with their customers and audience. In 2017 its Messenger platform alone had already reached about 100,000 active bots, and a survey then found that nearly 80 percent of companies use or plan to use chatbots by 2020.

At the Shoptalk conference a few years ago, eBay President and CEO Devin Wenig announced the launch of eBay’s new chatbot called ShopBot, which advises customers on items they might like to buy via automated chat dialog.

This pattern makes sense, as we see that millennials — 38 percent of whom prefer texting as their number one form of interaction, according to a study from Think with Google — have elevated this type of communication to an art form.

Will Siri or SMS-like automated dialog with your brand become the next big consumer touchpoint? If so, what do you need to do to prepare?

The answer, as some of the stats above suggest, is that conversational commerce is poised to be a major and preferred interaction model for many future brand interactions.

The good news is that if your brand has built a reasonably flexible and integrated digital stack, it can often be quickly leveraged to enable high-value CC capabilities without requiring that you install “Deep Blue” in your data center.

Here are five key things to know about getting started with conversational commerce:

1. The Core of Conversational Commerce is Very Similar to Search.

If you already have a strong search platform that permits parametrization, you can use it to drive a key portion of your chat experience. When you tell eBay’s chatbot you are looking to buy a voice recorder; it asks you questions such as the size and memory capacity you need. These questions are simply the metadata parameters eBay has available for voice recorders. You can utilize the product metadata in your existing catalog to make your chatbot appear to ask smart questions, and even more importantly help the customer find what they need, but in reality, the results are very similar to what they would experience if they simply entered structured search queries.

Of course, not all queries involve the quest for a product. Some may be asking a question, such as about your return or cancellation policies, but this too is very similar to search. You can parse chat questions against your full-text index and return intelligent answers by, again, leveraging your search engine.

2. The Next Step of Conversational Commerce is About Enabling Transactions.

Once a customer has found what they are looking for, they may wish to buy, reserve, add to a wish list, or take some other action. Your chat flow needs to know when to pivot from searching to asking the customer to take action. In many cases, or in your initial releases, you may simply choose to branch to existing web screens to complete transactions, as eBay is doing with ShopBot. More sophisticated conversational commerce implementations allow the customer to take action via voice or text, such as Domino’s, which allows the customer to order a pizza by text.

3. In Text Conversations, You Generally Know Your Customer.

One of the advantages of most forms of conversational commerce, such as SMS or Facebook Messenger, is that your customer is identifiable. If the customer has a profile in your system, you can use this knowledge to make the conversational interaction simpler — and also smarter. Picking up again on our Domino’s example, when the customer texts them a pizza emoji, the bot matches their telephone number to its database and confirms that it will be placing the order with toppings based on their past preferences, and will deliver it to their home address on file. The customer will then have the opportunity to override any of these defaults if they are in the mood for Hawaiian pizza that day.

4. You Can Make the Language Parsing Easier by Giving Multiple-choice Options.

Many successful chatbots are more of a string of multiple-choice questions than a free-form dialog. This substantially reduces the challenge of “comprehending” the customer and furthermore reduces typing for users on mobile devices. Naturally, you will want to support customer-entered text strings, but a considerable number of interactions can be handled via a series of multiple-choice questions. In some ways, chat is similar to IVR systems at call centers, and can often use similar types of decision trees.

5. It Doesn’t Have to be Perfect.

There is still some novelty to automated interactions, so customers don’t expect them to be perfect. Furthermore, as with any digital platform, you have the opportunity to improve it over time iteratively. Siri has grown tremendously over the last few years in the range of queries it can handle.

A fantastic resource to help guide your prioritization of new capabilities are the chat logs themselves, which will give you a sense of the types of interactions that your customers are attempting that may not yet be supported by your platform. And in the meantime, as you become aware of such chat or voice requests, you can create short text responses to those categories of inquiries, letting the customer know what other touchpoints currently support that action. So if a customer, for example, uses a chatbot to check their account balance but then wants to transfer funds, and that is not yet supported via conversational commerce, you can supply the URL for the website or app and the toll-free number to call, so they know where to go next.

6. Develop a Core Conversational Engine, and Leverage it Across Many Different Touchpoints

It makes sense to invest in conversational commerce platforms and tie them to your existing catalog, customer data, business logic and transaction capabilities. In doing so, think of creating one central CC “engine” that will connect to a variety of conversational endpoints. To begin with, you may want to focus on enabling a chatbot on your website(s) and in your apps, and integrating with the Facebook chatbot API to allow customers to chat with your automated system via Messenger the same way they would chat with their friends. But in future iterations, it makes sense to support SMS, Skype, WeChat (if you do business in Asia), and possibly other similar platforms. Longer term, as Apple’s Siri, Google Voice, Microsoft’s Cortana, and Amazon’s Alexa continue to open up their APIs, the same conversational engine you created for text can be leveraged with relatively small modifications to support voice interactions.

Conversational commerce is already here, and most major brands have either implemented or are in some stage of planning around an implementation. You can probably leverage existing systems and data sets to create a reasonable starting point for conversational interaction without requiring sophisticated AI or language parsing. Over time, you can learn from your customers’ queries how they want to interact with you and evolve your conversational capabilities accordingly.

This article originally appeared on the Howard Tiersky blog

Image Credits: Pixabay

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Good Design Makes Technology Disappear

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Good Design Makes Technology Disappear

by Braden Kelley

The late Clayton Christensen wrote a little book called The Innovator’s Dilemma that many of you I’m sure have read. Many people think of it as a book about disruptive innovation, but it can be much more than that if you shift your perspective.

The Classic Disruptive Innovation Example

One of the case study examples is that of mini-mills disrupting the rolled steel producers in the steel industry by starting at the bottom of the food chain with the production of low margin re-bar and then moving upwards into higher margin steel products. This is seen as the blueprint for how you disrupt an industry. You go first where the incumbents are least likely to be concerned about new entrants – low margin products – a market that incumbents might actually be happy to lose, because their average margins will actually increase and wall street will potentially reward them in the short-term with higher stock prices.

But if you shift your perspective on this case study and apply it to emerging technology, something new emerges.

Learning and Adoption Require a Compelling Use Case BEFORE They Can Occur

I’ve been listening to a lot of podcasts while I work lately. Podcasts with leading scientists from around the world. One of the core themes that continuously emerges is that innovation is really hard and takes a long time. I was really struck by iRobot co-Founder Rodney Allen Brooks speaking about how they had a target of launching the Roomba at $200 and this meant that he had FIFTY CENTS per unit to spend on a piece of silicon to power their invention. He told the story of running around Taiwan looking for a chip that was cheap enough and was handicapped in ways that wouldn’t matter for their particular application – as ALL chips in that price range are going to have severe limitations. This is a great story for highlighting some of the unexpected challenges in turning an invention into an innovation.

Another interesting innovation case study – on the failure side – is that of Google Glass. The smart glasses arrived as an overhyped and underwhelming product and died on the vine in a very short period of time. One of the key reasons for their failure was the lack of a compelling use case, and another was that technology was too front and center – so much so that Google Glass seemed like a creepy invention.

“Making access to information just instant and intuitive. By doing that, technology fades into the background, and we’re more connected with the people and things around us.”

This quote is pulled directly from the video below about Google’s reboot of their smart glasses initiative:

Google’s Live Translation Glasses arrive this time without a product page, without a formal product name and promising much less.

One of the things that really struck me in this short video is that while it is super easy to anchor on the value of the translation piece – displaying Mandarin on screen from an English voice for example – they have several other powerful uses cases, including:

  • People who have single-sided deafness
  • People who don’t want to wear hearing aids, or for whom hearing aids don’t work
  • People who are fully deaf
  • People who are trying to learn a new language

Do One Thing Really Well and Build From There

Google’s Live Translation Glasses remind me of another pair of smart glasses launched a little while back in the glow of the Google Glass failure – Amazon’s Echo Frames.

Amazon’s Echo Frames build themselves around the compelling use case of hands-free searching and calling. They have speakers and a microphone, connect to your iOS or Android smartphone, and can even be fitted with prescription lenses.

Amazon Echo Frames

Don’t Strip the Gears on Your Innovation Machine

Our ability to imagine usually outpaces our ability to execute and it can be a challenge to rein in our imagination to match our ability to not just execute, but to do so profitably and at a pace that our customers can see their way to adopt it.

When we look at my Innovation is All About Value methodology, we can also see that companies fail less often at value creation, and more frequently at value access and value translation.

When your start small and build around a compelling use case it is easier to get the value translation right and it is easier to build the key value access components to support your value creation.

Timing matters…

Price matters…

Compelling use cases matter…

What’s yours?

Keeping the end in mind and the future in sight – is important – but it is more valuable to identify where to start and add value as you go.

Don’t strip the gears on your innovation machine and keep innovating!

Image credit: The Verge, Amazon

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At What Point Does Smart Become Stupid?

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At What Point Does Smart Become Stupid?

In addition to 2020 being the year of the Coronavirus COVID-19, some would also say that it was the year of the voice-activated smart device. Sales of smart speakers in 2019 reached 146.9 million units and 2020 will likely approach 200 million units or more. The final number depends on how many showed up under Christmas trees as the 4th quarter. In addition, during 2020 we started to see Alexa advertised for other contexts, including in Buick automobile advertisements. Which brings up a couple questions.

Question 1: Is the advertisement below a real advertisement or an April Fool’s Day fake advertisement?

Question 2: At what point does the trend that smart speakers began reach the point of stupidity?

To answer that question I recommend that we revisit my definition of innovation:

“Innovation transforms the useful seeds of invention into widely adopted solutions valued above every existing alternative.” — Braden Kelley

The one thing that many product managers often forget is that invention and innovation are not the same thing, and so at some point product managers are likely to invest past the invisible line on different value dimensions beyond what people are willing to pay for.

This leads to products being designed and launched that while they might be revolutionary and inventive, they actually end up being unprofitable and not innovative at all because the foundations of the new offering never reach wide adoption.

Are we approaching this point with smart devices?

Let’s try and answer this question by answering the first question about the video.

YES – This is in fact a real product.

Now, how many of you are going to rush out to your home improvement store and purchase one of these faucets to replace your existing kitchen faucet?

What if I told you that it would cost you $800-1,000 compared to very nice kitchen faucets that can cost under $100?

Very few people are likely to replace their kitchen faucet unless it stops working or starts leaking profusely.

At the same time, Moen will definitely sell some of these faucets to people who must have the latest gadgets.

If you were the product manager or innovation manager involved with this product, before launching it you should ask:

  1. Will we sell enough of this smart faucet to justify the cost of developing and marketing it?

  2. Will this smart faucet create enough of a brand halo to help us sell more of our traditional faucets?

The answers to these questions may very well be – yes.

But if not, then we have reached a point where SMART starts to become STUPID.

But, don’t stop there. You should also ask yourself questions like:

  1. Does it take longer to get a glass of water using the smart method than the easy manual way?

  2. Could my grandmother install and use it without reading the directions?

  3. Is this new capability valuable enough to drive replacement?

If you are an inventor or a product manager, these kinds of questions are the type that you must always be asking yourself – even if you don’t like the answers.

If you still decide to go ahead with a product that will be unprofitable, you will at least do so with open eyes – and for the right reasons.

For more on this topic, please be sure and check out my previous article – Innovation or Not – Amazon Echo Frames

Keep innovating!


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Innovation or Not – Amazon Alexa Pay for Gas

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Amazon Alexa Pay for Gas

You can now use the Alexa app on your phone or Alexa-enabled device in your car for an easy way to pay for gas at Exxon and Mobil stations nationwide.

Here’s how it works in a nutshell:

  1. Drive your vehicle up to the pump at your Exxon or Mobil station.
  2. Use the Alexa-enabled device in your car or Alexa app on your phone and say “Alexa, pay for gas.”
  3. Follow Alexa’s prompts to activate the pump.
  4. Fuel up and drive away. Payment is handled automatically.

I’m not sure whether they’re using Near Field Communications (NFC) or cellular data to communicate, but basically what’s happening is that in the same way a card swipe or tap to pay reader on the pump receives payment method information and validates payment, the pumps at select Exxon Mobil stations can now receive Amazon Pay default payment information, validate it and unlock the pump in the same way.

It’s a nice convenience and a clever way of trying to increase the adoption of Amazon Pay, but is it an innovation?

What do you think?


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