Artificial intelligence is already a part of daily life, but for business owners, the key question is, “How can AI improve my marketing and help me sell more stuff right now?”
Throughout the customer decision journey, savvy marketers are already deploying AI at every step to engage customers, predict their needs, personalize messaging and keep them coming back for more. But many business owners have a nagging anxiety that they are falling behind, unable to keep up with the pace of change and they are increasingly fearful that an aggressive competitor will deploy a killer app that knocks them out of the market.
Here is a simple health checkup for your business to make sure you are on track for marketing in the age of artificial intelligence.
1. Voice-enabled customer interactions
If you had a problem recently with your Internet or cable provider there’s a good chance the first “person” you talked to on the helpline wasn’t human. Voice-enabled customer service uses natural language processing (NLP) and machine learning to understand a customer’s needs and address their concerns accordingly. It allows companies to quickly filter and categorize caller issues, resulting in streamlined operations and faster turnaround times. Amazon, BestBuy and UPS are just some of the companies taking advantage of automated customer service powered by AI.
Google’s Duplex is a digital assistant so sophisticated that it can carry out conversational tasks like making a restaurant reservation over the phone without the human receptionists on the other end realizing they are speaking with a computer. We are beyond the Turing Test. Just have your digital assistant contact my automated call center and let them sort it out…
In fact, a recent Forbes article estimates that up to 85% of all customer service interactions will be handled without a human agent by 2020, thanks to advances in conversational AI software and natural language processing.
Are consumers able to interact with your digital marketing using voice?
2. Customer service chatbots
Related to voice-based customer service are AI-enabled chatbots used as an initial response to consumer concerns and inquiries. What voice assistants do for calls, chatbots do for websites and messaging channels. But unlike traditional chatbots with a limited range of predefined responses, AI enables modern chatbots to leverage machine learning to deliver targeted messaging and improve results based on data collected from previous chat interactions. In a world where web access is quickly outpacing mobile and landline calls, chatbots have become an indispensable part of business — so much so that an Oracle survey of 800 business decision-makers found that 80% have or plan to use chatbots by 2020.
Some businesses even integrate chatbots with popular messaging apps in order to engage customers more broadly. Retail brands like H&M and Sephora use bots in the Kik messaging app to address customer concerns instantaneously, while Facebook Messenger has made its full chatbot API available so businesses can create their own chat-based interactions. AI-enabled chat delivers a controlled environment for marketers to test messaging and continuously collect data to dynamically shift chat results toward key performance goals using machine learning.
Does your chat learn and improve based on the data it collects?
3. Digital ad targeting
One of the greatest advances in modern marketing has been targeted advertising. Rather than pushing out mass-market ads, today’s smart ads are personally tailored to your needs, by taking into account your specific characteristics like age, gender and location, as well as your digital footprint such as your browser history and online purchases. Predictive analytics and machine learning are used to segment audiences and score them based on factors like intent and likelihood to purchase. Programmatic ad exchanges allow consumers to be identified and targeted in real time so that digital ads can be delivered to their laptops and mobile devices in a few hundred milliseconds. Thanks to AI, those ads are about to get even smarter.
In 2015, advertising agency M&C Saatchi debuted the world’s first artificially intelligent poster campaign. Using an embedded camera and an initial set of copy and images, the poster tested ads by analyzing viewers’ reactions. Successful ads were retained and improved upon, while ads that generated negative reactions were discarded.
Three years later, Google debuted its Marketing Platform, a unified analytics and marketing ecosystem designed to make smart advertising easier for marketers. Businesses submit up to 15 different ad layouts, which Google then displays using AI. This means that people searching for the same product will see different ads based on their character and preferences. This new form of contextual advertising benefits both the business and the consumer: brands get increased conversions while customers get individually tailored ads specific to their needs.
Are your ads reaching the right audiences at the right times with the right messages?
4. Recommendation engines
If you’ve ever bought something on Amazon or watched Netflix, then you’re likely familiar with recommendation engines. These systems use algorithms to display products or services that you may be interested in, taking into account your recent searches and purchase history. Like targeted ads, the aim is to show only products that are relevant to your needs, instead of bombarding you with unrelated fluff. People who bought this product also bought this one…
Amazon generates 85% of sales revenue from recommended products, making AI-powered recommendation engines a critical tool for the retail giant.
And it works: according to Salesforce, personalized recommendations account for 27% of retail site revenue. For online retail giants, such AI-powered recommendations are even more critical, with Amazon generating 85% of sales revenue from recommended products. If you tend to watch a lot of scary movies, Netflix will start to populate the top of the screen with more horror movies. If you are into crime thrillers, your viewing history heavily influences the recommendations generated by the algorithms. Music discovery on Pandora and Spotify leverages similar algorithms to help you find stations and music collections likely to appeal to your individual tastes.
But recommendation engines aren’t limited to digital media. Clothing retailer Stitch Fix is delivering complete outfits directly to consumers. You pay for what you keep and simply return what you don’t like. The potential for data collection and machine learning to help Stitch Fix match customers to outfits illustrates the capacity for AI-enabled recommendations to impact industries as diverse as wines and vacations. And unlike search, where businesses are beholden to a limited number of popular search engines, like Google, recommendations allow businesses to have more control over the outcomes.
Are you a source of AI-enabled recommendations for your customers?
Speaking of search, thanks to voice assistants like Amazon’s Alexa and Apple’s Siri, voice-based commands are increasingly popular when it comes to web searches. After all, it’s more convenient to just ask Siri about the weather or sports scores, instead of looking it up using the graphical user interface (GUI) at The Weather Channel or ESPN. And the trend toward voice-based search is escalating rapidly.
comScore reports that 50% of all search will be voice-based by 2020.
Google has adapted to this new form of web searching by releasing RankBrain, an AI algorithm that understands speech. By harnessing advances in natural language processing and machine learning, the search giant can quickly interpret voice searches and display the best results. So even search is moving rapidly to voice-based interactions. We no longer have to type an address to get directions, find a restaurant, or buy a pair of shoes. All of this can now be done through voice. For businesses that have just recently mastered website design and search engine optimization, the voice-based interface represents a new challenge and huge opportunity.
Can consumers find you and your products using voice-based search?
6. Content creation and personalization
Until recently, creating content was the exclusive domain of human writers. However, that’s now changing thanks to advances in natural language generation (NLG), an AI system where machines can write natural language from a knowledge base.
Using an initial set of templates, AI-powered software like Wordsmith and Quill can generate unique content that’s indistinguishable from content written by a human. Thanks to their “always-on” nature, AI agents can quickly create content from new information, making it the perfect application for stock quotes, sports scores, breaking stories and news blurbs. The Associated Press, BBC, the New York Times and Reuters are just some of the media outlets that take advantage of AI to push out the latest headlines.
We have reached the age where AI-generated content is indistinguishable from content written by humans, opening new opportunities for content creation and personalization.
The potential to personalize content arms marketers with the ability to customize their web presence on the fly to deliver messaging in real time to consumers. The personalization of web pages, emails, and push notifications makes the messaging more appealing because it fits the immediate needs of the consumer by leveraging detailed information about that user’s preferences and history.
Content can also be curated from the vast expanse of the Internet and delivered as a value-added service to consumers, to keep them informed, up to date, and in tune with trends and current events. And the more the consumer interacts with the personalized information, the better the machine learning gets at finding exactly what types of content keep that consumer engaged.
Is your marketing message personalized to the consumer?
7. Dynamic pricing
It used to be that prices were determined by demand – the cost of products and services fluctuated depending on the market. Thanks to AI, even prices are now getting “smarter” by adapting to real-time conditions, and even changing to adjust to customers at the individual level.
For instance, ride-hailing services like Uber and Lyft already use dynamic pricing by taking into account location, travel distance, time, current traffic and weather conditions, and driver availability. Someone hailing a ride will see a different price compared to someone a few blocks away, even if both are going to the same destination. The same person might even see the cost fluctuate in real time, when its rush hour or snowing. I have.
Thanks to AI, other industries are now adopting dynamic pricing. Retailers like Walmart can change prices up to 300 times a year, much of it automated using sales modeling and predictive analytics. Based on this premise, Amazon was able to drop its price-matching policy of offering the lowest price, instead using a calculated “best price” that’s generated from customer behavior and competitive analysis. Other businesses, like car dealers and airline companies, even offer individually-targeted prices and discounts by tapping into online history and searches to gauge the likelihood of a sales conversion. Credit risk and financial history can be leveraged in real time to offer credit and financing at rates that match the individual consumer. From MSRPs, we are now moving into AI retail pricing.
Is your pricing dynamic and set to real-time market conditions?
If you answered “no” to most of these questions you aren’t alone. Business leaders and corporate marketers are wrestling with these issues right now in an effort to move their marketing efforts into the age of artificial intelligence. Will you be one of them?
**Originally posted at Marketing and AI