Understanding chatbot marketing in the ever-changing world of Facebook

 


When Mark Zuckerberg speaks, digital entrepreneurs and marketers listen very carefully. It’s no surprise, then, that when he announced a major change in the Facebook News Feed algorithm during the company’s January earnings presentation, the world of social media immediately reacted with extreme attention, some raised eyebrows, and a bit of anxiety. Continue reading “Understanding chatbot marketing in the ever-changing world of Facebook”

How to Easily Introduce Chatbots to Journalism Students

If I had a penny for every piece of technology fleetingly considered the “future of journalism,” then I suppose I’d have quite a lot of pennies by now, if not quite enough to retire on. Chatbots are one such technology, with CNN, the Wall Street Journal and the Guardian among those launching experimental versions within Facebook Messenger….

Read full post How to Easily Introduce Chatbots to Journalism Students on MediaShift.

Designing a Chatbot

I have been extremely lucky to get a chance on designing a chatbot for one of our clients and the learning in the process has been massive. Most of the notions that I thought were true were discarded by research and a whole new world of possibilities just opened wide. Below, I have shared some of my crucial understandings along the path of designing a bot, hope you like it. Continue reading “Designing a Chatbot”

4 things I learned building chatbots for major brands in 2017

In 2017, my team powered chatbots and voice skills for leading brands like Nike, Vice, Jameson, Marriott Rewards, Simon, Gatorade, and more. We witnessed new user behaviors and uncovered an evolved set of best practices to build a chatbot. Here are four actionable learnings from our work that you should consider when launching your own chatbot in 2018.

1. Personalization drives engagement

Bots that are designed to segment and engage customers throughout the entire conversation drive higher metrics than chatbots that do not personalize the conversation. For example, in our testing, personalized results yielded the highest click-through to website, up to 74 percent in some cases.

This year, a leading athletic brand set out to inspire a sneaker style for girls across the globe. The brand launched a customized sneaker builder where the user uploads of a photo of her outfit, and magically, in an instant, the bot pulls up a pair of shoes that matches the uploaded picture. This experience drove a click-through rate 12.5X higher than the global brand average.

Bud Light launched a chatbot with the goal of driving demand and purchase of Bud Light’s team cans on game day throughout the NFL season. A personalized data model and chatbot powered the ordering and delivery of team cans every game day during the NFL season. The Bud Light chatbot acted as a utility to remind fans that it was game time, and to order Bud Light before the game. Bud Light saw an 83 percent engagement rate with personalization.

2. Get to the point quickly

Across multiple chatbots, about half of the first actions that users take is free text entry. Updating the onboarding copy to manage expectations — “this is a bot that can do X and Y,” for example — lowers that initial friction. If the first intent is help-related or a long-form text entry, you can provide a customer service number, FAQs, or an option to “talk to a human” from the very beginning.

When users get into the designed experience, point of sale should be within five clicks. For example, after A/B testing a chatbot across 250,000 users, we noticed a significant drop-off occured when the core focus (click to purchase, etc.) was beyond five clicks.

3. Chatbots go beyond mobile devices

Bots are an effective tool to drive real-world activities or offline conversions, with coupon redemption rates as high as 30 percent.

A leading quick-service restaurant brand launched a new bot that drove users through an immersive content experience with videos, quizzes, recipes, and coupons. This high engagement led to over 71,000 coupons redeemed from the chatbot.

The Jordan Brand aimed to reach elite high school football, basketball, and baseball athletes with an ongoing training chatbot experience for pre-season training. Jordan delivered nightly prep videos and daily workout series to a targeted group of high school athletes in advance of basketball season on Facebook Messenger. Athletes loved receiving push notifications reminding them to work out. Jordan saw an extremely high completion rate as well as a high re-engagement rate compared to regular customer relationship management programs: Over 70 percent of users surveyed enjoyed the experience.

4. Truly understand your users

Understanding why people did or did not enjoy the experience is key. One way to do this is using free text analysis to understand sentiment and drop-off. For example, we launched a new bot with a leading shoe retailer. Most people came to the bot knowing what specific shoe they wanted to buy or with a question about the shoe they already bought. Cater to the specific pain points and make sure your bot handles customer intent at every stage.

Finally, make sure to survey users and learn from both your best purchasers as well as your qualified no’s. One way to do this by asking your users directly. You can use a chatbot for net promoter score surveying.

Jonathan Shriftman is the director of business development at Snaps, a mobile messaging service.

Everything Amazon’s Alexa learned to do in 2017

Amazon’s Alexa is leading the AI assistant pack. Echo devices are dominating smart speaker sales, and that was before Amazon brought the devices to more than 80 nations around the world. To defend its crown, Amazon moved fast this year to outpace competitors like Google Assistant and Microsoft’s Cortana. Apple’s delayed HomePod is due out next year, while Samsung and Facebook are also reportedly planning to debut smart speakers. It can be challenging to keep up with all the features Alexa has added to stay ahead of some of the largest tech companies on the planet, so here’s a rundown of everything Alexa learned to do this year. Continue reading “Everything Amazon’s Alexa learned to do in 2017”

5 tips to humanize your chatbot

Chatbots are an increasing part of our daily lives, redefining how we engage with the internet and with businesses. Canadian messaging company Kik explains it like this: “First there were websites, then there were apps. Now, there are bots.” Just like the early internet, bots are set to transform commerce as we know it, making it easier than ever for consumers to reach, engage, and transact through instant commands. Continue reading “5 tips to humanize your chatbot”

Can Facebook Messenger help you build a deeper relationship with your audience?

Maybe, but it’s a lot of work. Here’s what Annenberg Media tried.

Chatbots seem to be popping up everywhere. You can find them on chat apps, on your SMS platform or in apps of their own. If you’ve used Siri or Amazon’s Alexa, you’ve used a chatbot.

Many news organization use chatbots to deliver the news, but few use it to have a conversation. The options for what a user can do beyond asking for the organizations’ top stories tends to be fairly limited.

Continue reading “Can Facebook Messenger help you build a deeper relationship with your audience?”

Amazon Alexa skills to accept payments

Developers and businesses making skills for Amazon’s Alexa will soon be able to accept Amazon Pay and make purchases directly within voice apps from the Alexa Skills Store. The news was announced today during the Alexa State of the Union at AWS re:Invent in Las Vegas. Other Alexa news shared today includes plans to bring Alexa to Australia and New Zealand in early 2018 and adding $100 million to the Alexa Fund for international investment. Continue reading “Amazon Alexa skills to accept payments”

7 metrics for monitoring your chatbot’s performance

Researchers estimate we will speak to chatbots more than we speak to our spouses by 2020. Obviously, companies that implement chatbots are doing something right. However, businesses still have a hard time determining whether or not their bots are up to snuff. While there are plenty of effective chatbots on the market, there are also many that don’t quite meet consumers’ needs. So how do you measure the success of your chatbot?

This is the dilemma facing an increasing number of companies that use chatbots as part of their customer experience. 80 percent of businesses want to implement a chatbot by 2020, but many still face the challenge of gauging the efficacy of the technology.

Google’s Chatbot Analytics platform recently opened up to all, but it is still necessary for businesses to develop and understand their own chatbot success metrics to effectively use the platform.

The process of defining the best KPIs for your company’s bot will depend on your business goals and the functions you want your bot to perform.

Here are seven metrics of success you can use to identify opportunities for improvement in your company’s chatbot.

Revenue growth

The first question any prospective investor wants to know about a company is whether or not it makes money. Therefore, the best indicator of a chatbot’s value is its financial benefit.

There are many ways to evaluate a bot’s impact on revenue – the best one for your bot will depend on its purpose. Another interesting wrinkle is that your chatbot can have a knock-on effect on a number of areas.

For example, you can measure a customer service bot’s profitability growth by the amount of money it saves the company compared to maintaining a customer service team 24/7. But you will want to take the bot’s impact on customer service into account. If self-service rates are higher and clients are more satisfied, that will result in repeat customers and higher online sales, thus impacting top-line revenue growth.

Self-service rate

Nirvana comes for businesses the moment a user gets exactly what they want from the chatbot without any human input.

If your chatbot’s goal is to change a user’s password, you would measure success by the percentage of user interactions that end with this as a result.

The self-service rate closely correlates the cost savings aspect of revenue growth – in other words, how much money did your chatbot save?

Satisfaction rate

What better way to find out exactly how well your chatbot is doing than to ask the very people who use it?

Your chatbot can help you determine this metric by asking the key question for the Net Promoter Score – “On a scale of 1-10 how likely is it that you would recommend our chatbot to a friend/colleague?” As a lead indicator of growth, the NPS provides a crucial foundation for understanding your chatbot’s customer experience performance.

Activation rate

At this point, it’s worth reflecting on AARRR and its importance in measuring the success of your business.

The activation rate in the context of a chatbot refers to when a user responds to its initial message with a question or an answer which is relevant to your business goals.

For example, a chatbot designed to provide you with weather updates would receive an activation rate when you enter your location – thus allowing the bot to provide you with the information.

How can this KPI help? If for some reason people were not responding when the weather chatbot first reached out to them, the botmaster would be able to tinker with it to enable a more satisfactory outcome.

Confusion triggers

Unfortunately, even bots with the most robust natural language processing are unable to understand everything a user says.

These errors are a useful indicator for measuring whether or not you need to improve your chatbot’s matching.

Bear in mind there are three different triggers, each of which necessitates its own type of response.

There is first the simple confusion from the bot if it cannot understand a comment. A basic “Sorry, I didn’t understand that. Can you ask again in a different way?” response would suffice.

Second is if the user sends a number of messages which are outside the remit of your chatbot. After a couple of attempts, it would be worth programming your bot to relay a message that reminds the user of its exact purpose.

The final trigger is if the bot forces a user to speak to a customer service agent after the interaction. Each of these will tell you something different about how your chat agent is performing.

Retention rate

Once again referring to AARRR, the retention rate represents the percentage of users who return to the chatbot over a specified period of time.

This timespan would vary between the bots depending on their purposes. For example, a fitness chatbot would require daily interaction and would benefit from analyzing its 1-day retention.

Artificial intelligence/machine learning rate

How strong is the AI in your chatbot? You can use the percentage of user questions that are correctly understood to measure this.

Which leads us the million, if not billion dollar question — can my chatbot learn independently?

Chatbots with machine learning can measure progress by comparing the improvement in self-service rate over a period of time without human intervention.

An agent with robust machine learning will be able to continually run its own gap analysis to highlight potential areas of improvement.

The demand for chatbots among Millennials is clear. Consumers are asking for simple and effective customer service, but not every chatbot is capable of delivering on this promise without a few tweaks. In a market that is becoming increasingly crowded, these KPIs can help you keep your chatbot one step ahead of the pack.

Jordi Torras is CEO and founder of Inbenta, an artificial intelligence technology company.

3 questions marketers must answer before launching a chatbot

Bots are gaining lots of attention, thanks to the momentum in artificial intelligence and natural language processing. In fact, according to this Business Insider study, 80 percent of businesses are using, or intend to use, chatbots by 2020. While simplified rules-based bot builders like QNAMaker.ai make entering the realm of bots easy, truly conversational and awe-inspiring brand experiences need to come with a thoughtful and strategic approach. This means that before you jump in and start writing (or hiring out) a single line of code, you’ll want to do some planning. Let’s start with the most obvious question. Continue reading “3 questions marketers must answer before launching a chatbot”

Google gives developers more tools to make better voice apps


Google Assistant received some major upgrades in recent days, and today Google Assistant product manager Brad Abrams announced a series of changes to help developers make voice apps that interact with Google’s AI assistant, including ways to give them more expressive voices and send push notifications, as well as new subcategories for the Assistant’s App Directory.

One of the coolest new features coming to Google Assistant is something called Implicit Discovery. Instead of saying “OK Google, talk to Ray’s Auto Shop app” and then asking to schedule an appointment, Implicit Discovery will let you say “Book an appointment to fix my car” then offer an app recommendation. The same should apply if you say “I need to book a flight” to summon something like the Kayak app or say “I need a ride” to interact with Uber or Lyft.

Implicit Discovery may seem simple, but it’s going after one of the biggest challenges for AI assistants, which is: Without a visual interface, how does a user figure out how to get things done or remember the names of favorite or useful apps? Implicit Discovery seems to be an effort to tackle this. It’s also a feature already available in Amazon’s Alexa.

Another feature added today to improve discovery of third-party apps is subcategories in the App Directory, so instead of just being listed in the Food and Drink category, apps can be slated into subcategories like “Order Food” and “View a Menu.”

The App Directory was first introduced at the I/O developer conference this spring.

Other changes on the way for the App Directory include badges to indicate if a voice app is family friendly and support for third-party apps in languages beyond English. Until today, Google’s voice apps were only available for English speakers in the United States, Canada, Great Britain, and Australia. Voice apps will soon be available in Portuguese in Brazil, English in India, and Spanish in the U.S., Mexico, and Spain.

Google announced today that developers in the United Kingdom can begin to make apps that can carry out transactions, a feature that until now was exclusive to the U.S. The Google Payment API expanded to include Google Assistant users in the U.S. in May.

A series of new APIs has also been rolled out, including one that gives apps the ability to send push notifications, first over the phone and in the future with voice or auditory sounds through a Google Home smart speaker. Alexa notifications first launched in September.

An API to link an account to an app for personalized results, and another that gives developers the ability to transfer a conversation from a smart speaker to a smartphone also launched today.

Beyond push notifications, voice apps can now deliver daily updates or notifications about certain kinds of content.

The Actions on Google platform for the creation of voice apps by third-party developers first became available roughly a year ago, in December 2016. Since then, hundreds of voice apps have been made available to do a range of things, from playing ambient sounds like crashing waves to offering local deals for a pizza from Domino’s.

It’s been a pretty busy week for Google’s intelligent assistant. On Monday, Google announced that Home speakers can now be used as an intercom system. The Google Broadcast feature, first announced at the Made by Google hardware event last month, allows you to deliver a message through all your Google Home devices. The app also gained the ability to deliver music and movie recommendations from streaming services and control sound by adjusting things like bass and treble, a clear plus for prospective owners of Google Home Max, which is scheduled to hit store shelves next month.

Taken together, the announcements made today will give voice apps the ability to be a much more vocal, vital part of the Google Assistant experience, and continue to evolve the ecosystem surrounding Google’s AI assistant.

This time last year, Google Assistant was only available in the Allo chat app. Today you can speak to Google in Android TVs, three Google Home smart speakers, Android smartphones, the Pixel Chromebook, and Pixel Buds, the first headphones made by Google that began to roll out last week. Support for Google Assistant in tablets using Android is also reportedly on the way.

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