Over the past few months, there has been a media swarm around chat bots. Some wonder if the simulated computer software programs (most recently popularized within messaging applications like Facebook Messenger) will replace humans in a variety of jobs, while others speculate about just how helpful the technology really is to businesses. It seems that virtually everyone is talking about bots, including marketers.
Chat bots are the latest evolution in a long legacy of technologies changing the way consumers interact with companies. Every invention from telephones to social media has made businesses more accessible to consumers, and chat bots are no exception. I’ve been fascinated by the coverage for two reasons. One, the technology behind bots has been around for years, and some companies are doing a good job of marketing it. And two, bots—when done right—can help us do our jobs as marketers.
Not all bots are created equal, however, and marketers must carefully consider both the strengths and hurdles of bot technology before embracing it with open arms.
This is especially true within messaging apps, which have great potential to change the way businesses and consumers communicate. Messaging apps are perhaps the last remaining space on our mobile phones where users are in complete control of the interactions.
Messaging apps like Messenger and WhatsApp are popular for a reason–they’re easy to use, frictionless and convenient. This makes it all the more important for marketers to get their chat bot implementation right the first time. With already limited budgets, the costs of improving customer satisfaction are high for marketers, and they risk turning consumers away from a technology that has a lot of merit if they release a poor, ineffective chat bot.
In the world of online customer service, even a single bad experience is like food poisoning for marketers. No matter how delicious the food (or digital channel), consumers are not likely to give it a second chance if it has negative side effects. Bots will become yet another fad if they are not engaging and useful, which is why implementing the right bot technology is a business-critical decision.
In addition to choosing intelligent bots, integrating them with agent assistance and future-proofing investments in bot technology, marketers also have to ensure a customer-service experience that allows consumers to resolve challenges online, on their own terms and, ideally, within a single channel.
In today’s wave of “DIY” companies like Uber and Amazon, shoppers want to self-serve, and chat bots can make it easy for consumers to get answers and information on their own terms, and within widely used, convenient channels. Bots are very capable of offering this kind of personalized, on-brand customer service experience, but only if they can understand natural language, predict intent and know when to escalate that person’s query to a live agent.
For example, imagine you’ve hit a roadblock while booking a trip from New York to Chicago on an airline’s website. Rather than just saying something generic such as, “how can I help you?,” an intelligent bot would say, “Scott, I noticed you are trying to book a trip to Chicago, but your usual flight time is not available–is that why you messaged me?” It’s a powerful, compelling moment for the consumer–the kind we (as consumers) want more of.
To provide this level of compelling customer service, bots must be able to predict consumer intent, as well as know when to escalate a service request to human assistance without losing past context. The amount of data available to marketers about consumers is astounding, and businesses do their customers (and themselves) a disservice when they fail to leverage this technology to make real-time decisions about how to deliver the right treatment, and when.
When the app store first emerged on the scene, developers rushed to create an app for just about everything. But the ones that we still use today (and often) are ones that actually help us do something of value.
In the same vein, bot technology will become more mainstream, but its success will be dependent on its usefulness. Smart companies, and smart marketers, are looking at bots as an intriguing piece of an intent-driven engagement strategy that cuts across channels. But it’s only one piece. It’s essential that the front-end–where consumers first interact with a brand–be integrated with a platform that can serve up this predictive data.
Marketers have the opportunity to find great value from the chat bot trend and help solidify the technology as a key part of the customer-service experience, but only if they get it right the first time. In the world of customer service, second chances are no guarantee.
Scott Horn is the chief marketing officer at customer acquisition and engagement provider 7.
Image courtesy of Shutterstock.
Article courtesy of SocialTimes
As the Apple Watch nears its one-year anniversary, customer-acquisition platform Fluent interviewed 2,578 Americans nationwide to determine their opinions on Apple’s smartwatch. Fluent found that 197 of the surveyed users (or around 8 percent) own an Apple Watch. Another 8 percent of respondents said they owned a different kind of smartwatch.
Fluent found that 79 percent of surveyed Apple Watch owners use their device for health and fitness monitoring, as well as to access notifications. Other popular uses include listening to music (75 percent of respondents), accessing email and chat services (66 percent), playing games (63 percent), making purchases with Apple Pay (61 percent) and accessing maps and directions (61 percent).
Overall, 56 percent of surveyed owners said health and fitness monitoring was their primary purpose for using the device (other than telling time).
Of Apple Watch owners, 62 percent said they plan to upgrade to a new Apple Watch when the next edition is released.
Fluent surveyed all users about their likelihood of purchasing an Apple Watch and found that 8 percent of respondents said they “definitely will” purchase an Apple Watch in the next year, while 11 percent said they “probably will.” On the other hand, 24 percent of respondents said they “probably will not” purchase an Apple Watch in the next year, and 35 percent of users said they “definitely will not.”
Breaking these respondents into categories, Fluent found that users who own an iPhone or regularly use an Apple product are more likely to purchase an Apple Watch in the next year than Android owners.
Fluent asked users if they felt that the Apple Watch was a successful product for Apple and found that 47 percent of all respondents said yes, while 53 percent said no. For Apple Watch owners, 77 percent said yes, while 23 percent said no.
Finally, Fluent asked users if they think the “majority of Americans” will have smartwatches in 10 years, and it found that the results were evenly split–50 percent of all respondents said yes, and 50 percent said no. In terms of Apple Watch users, 75 percent said yes, while 25 percent said no.
Jason Cohen, chief marketing officer of Fluent, told SocialTimes:
8 percent of Fluent’s survey respondents said they own an Apple Watch, so with the margin of error baked in (2 percent), that translates into roughly 15 million to 20 million Americans. While that’s a far cry from the number of folks who own iPhones, the inaugural version of the Apple Watch by and large should be viewed as a smashing success. And its future looks even brighter: Nearly one-half of Americans, and 75 percent of current Apple Watch owners, believe that the majority of people will own smartwatches 10 years from now.
The other point I’d like to emphasize is that the Apple Watch is more than just a watch—it is a wearable device, and Apple Watch owners take advantage of the full breadth of features it offers, from fitness tracking, to notifications, to music, chat and payments via Apple Pay. Apple Watch owners say the primary reason they own them is for convenience (46 percent) and features (31 percent). Only 11 percent say “fashion.”
When it launched last year, many pundits were questioning Apple’s ability to tackle the watch market, but I don’t think Tim Cook and his team every seriously thought that “watch people” would dump their Pateks and Rolexes for an Apple Watch. The plan was never really to go after the watch market–it was to launch and lead a whole new category of wearable devices. I think they have succeeded in doing so with the first generation of the Apple Watch, and although it certainly isn’t perfect, and it may not have lived up to the incredible amount of media hype surrounding it when it first was brought to market, the consumer adoption is there, and opportunity abounds for the future of the Apple Watch and the wearables category.
Fluent’s complete findings are available here.
Article courtesy of SocialTimes
A simple caption can boost advertising effectiveness by 17% as measured by effect on purchase intention.
New Ohio State University research published last week in the Journal of Consumer Research (open pre-publication access) by Christopher Summers and colleagues reports that captioning an ad with the words that the ad “targeted specifically to you based on your online activity” boosted ad effectiveness compared to the same ad revealing no information about targeting. There are provisos – the effectiveness boosting effect appears to hold only when the ad actually is behaviourally targeted and perceived by the audience to be accurately so.
Interestingly, the study – picked up by the Harvard Business Review – found that same ad captioned with the words “targeted specifically to you based on your demographic information” had no significant effect on ad effectiveness. It would seem that targeting transparency for behavioural advertising boosts ad effectiveness, but not for demographic targeting.
Why might targeting transparency boost behavioural ad effectiveness? The basic psychology of priming could account for this effect because reminding people of their past behaviour can increase the mental salience of associated behaviours (AKA primes), making these associated behaviours and responses more likely. This behavioural ‘identity priming’ – highlighting aspects of an individual’s behavioural identity – might explain why targeting transparency enhances behavioural advertising effectiveness.
However the authors offer an alternative explanation; they suggest that the bump in ad effectiveness may be due to the effects of ‘social labelling’ – when audiences believe they are being behaviourally targeted (accurately) as individuals (not stereotypes), they perceive marketers as labelling them (accurately), and may adjust their self-perceptions to better match these accurate (and desirable) social labels. This might explain the differences between the effectiveness of targeting transparency for behavioural ads and the non-effectiveness of targeting transparency for ‘demographic targeting’; its the difference between ‘we believe you’re this stereotype (profile/group/persona/market)’ and ‘we believe you’re you‘.
Whatever the reason, (I remain more convinced of ‘priming’ explanation), when it comes to behavioural targeting, transparency and honesty may be the best policy.
Summers, C. A., Smith, R. W., & Reczek, R. W. (2016). An Audience of One: Behaviorally Targeted Ads as Implied Social Labels. Journal of Consumer Research.