This post originally appeared on the Marketing Artificial Intelligence Institute's blog. The Marketing AI Institute was created and is powered by PR 20/20.
For over a decade, savvy professionals have used inbound marketing to grow. Inbound marketing consists of creating and promoting content that addresses customer needs. The goal is to attract, convert, and close more qualified leads by being helpful to consumers. Today, companies use inbound marketing methodologies to market more effectively and cost-effectively.
Marketing automation company HubSpot has defined much of modern inbound methodology. That methodology looks a little something like this:
“Instead of the old outbound marketing methods of buying ads, buying email lists, and praying for leads, inbound marketing focuses on creating quality content that pulls people toward your company and product, where they naturally want to be. By aligning the content you publish with your customer’s interests, you naturally attract inbound traffic that you can then convert, close, and delight over time.”
To achieve these goals, inbound marketers rely on many tools. They include marketing automation software, content management systems, and email marketing systems. They also include CRM systems, content creation tools, and content promotion tools. These systems comprise the inbound marketing tech stack. That tech stack can make inbound marketers more productive, personalized, and performance-driven.
Yet despite all the tools available, inbound marketing is still largely a manual process.
Inbound marketers still create personas, content, and promotion materials. They still envision and execute tactics manually. Even when using marketing automation, marketers hand-pick the rules and requirements for lead scoring and email workflows. Marketers still analyze data and present insights to stakeholders themselves.
The result? Today's inbound marketer cannot realize their full performance potential.
For example, let’s take the case of using a value-driven ebook to attract more qualified leads.
When someone downloads an ebook, a marketer defines a set of rules that tells the machine what to do next (i.e. If visitor downloads ebook, then send three-part email). In isolation, setting this single rule for a single download is very straightforward.
However, what if there are 10,000 downloads, across five personas, originating from multiple channels (social, organic, paid, direct) that require personalized emails and website experiences based on user history?
Humans are unable to conceive of the optimal set of instructions to guide the machine on how to personalize experiences at this scale. And because inbound is still largely manual, this makes personalization and performance at scale extremely difficult and costly to execute.
But imagine the potential if the extensive campaign outlined above—and all the time-intensive tasks and the data-driven decisions you make everyday as an inbound marketer—were intelligently automated and scalable.
It’s possible thanks to an existing and rapidly improving technology called artificial intelligence—and it’s about to change inbound forever.
What Is Artificial Intelligence?
Artificial intelligence is the “science of making machines smart,” according to Demis Hassabis, head of Google DeepMind, the search giant’s AI wing. These machines, in turn, enhance human knowledge and capabilities.
Artificial intelligence is the umbrella term we use to refer to different but related machine systems, which include technologies like machine learning, deep learning, natural language processing, and computer vision. These technologies have different capabilities and are at different levels of maturity, but are all considered AI. Tools that use AI may rely on one or more of these technologies.
The most advanced artificial intelligence doesn’t stop at setting up the initial rules to maximize performance, it uses machine learning to constantly evolve its actions. In other words, it learns, it gets smarter, and it creates its own algorithms.
You use AI everyday, but might not realize it. Amazon’s product recommendations and Netflix’s movie suggestions are powered by AI. Alexa and Siri understand your voice and respond thanks to AI. And it’s likely your latest purchase was delivered to your door thanks to logistics AI used by companies like UPS.
In the past two decades, AI has significantly changed how Wall Street and Silicon Valley do business. Today, recent advances in certain AI technologies have ushered in an “AI spring” of AI-powered startups, acquisitions, and investments. McKinsey says tech companies spent between $20 to $30 billion on AI in 2016 across industries. And there has been a 4.6X rise in deals to AI startups from 2012 to 2016, according to CB Insights.
AI is rolling out across industries as diverse as finance, insurance, healthcare, manufacturing, and professional services. Wherever there exists a highly lucrative opportunity to automate and enhance cognitive tasks with AI, there exists a major market ready to be disrupted and transformed by this technology.
Inbound marketing is just entering its AI moment. The technology now exists to automate and augment inbound marketing campaigns with artificial intelligence, and development is accelerating. (In fact, six marketing companies with more than $500 billion in funding made CB Insights' recent "most promising" AI list.)
In the process, AI will significantly evolve inbound marketing practice. We’re fast approaching an era in inbound marketing, where marketers and machines will work together to plan, produce, personalize, promote, and perform like never before.
Artificial Intelligence in Inbound Marketing
HubSpot defined the term “inbound marketing.” The company is making a play to own artificial intelligence in inbound marketing, too.
At INBOUND 2017, the company’s annual user conference, HubSpot made several announcements that highlighted how AI will transform inbound marketing practice.
To start, the company announced that its AI-powered Content Strategy tool is now available in all versions of the platform. The Content Strategy tool uses AI to recommend “topic clusters,” or groups of topics around which to build inbound campaigns during the Attract phase of inbound methodology. Says HubSpot:
“Influential search engines like Google have changed their algorithm to favor topic-based content. As a result, SEOs are exploring a new way of linking related content under a ‘topic clusters’ model.”
Key to the topic cluster strategy is artificial intelligence. HubSpot’s Content Strategy tool uses AI to surface and recommend topic clusters faster and better than human marketers can. Inbound is now about AI-enabled content planning around topic areas, not specific keywords. As a result, AI will become a linchpin of effective Attract campaigns.
AI isn’t just affecting the Attract stage of inbound methodology. It’s changing the Convert stage, too.
At INBOUND, HubSpot announced a new version of its Sales Professional product. The product relies on machine learning, an AI technology, to find the best leads in your database based on a contact’s history of interactions.
The tool also includes Priority Notifications, AI-powered automatic notifications that show reps the most important contact updates and events first, enhancing their sales productivity. The more reps who use HubSpot’s CRM tool, the better Priority Notifications get at identifying what’s important.
Last but not least, the Sales Professional product optimizes email send times based on a contact’s history of interactions and recommends when contacts are most likely to engage with communications.
Together, AI functionality is making it faster, easier, and more effective to conduct sales operations during the Convert phase.
However, perhaps the biggest, and most exciting, AI-related announcement applied to the Close and Delight stages of inbound methodology.
HubSpot announced a new tool called Conversations that makes it possible to chat at scale with prospects and consumers across channels.
Chat is quickly becoming a game-changer in inbound marketing. Using it, inbound marketers are able to convert and close leads at far higher rates than with gated content alone. Chat also delights prospects and customers by addressing every need or question at any stage of the purchasing journey.
And chat at scale is only possible with artificial intelligence, said HubSpot VP of Product Christopher O’Donnell said during the conference.
The Conversations tool makes it easier to manage human-powered chat across the organization and across any channel, all from a single platform. But it also makes it possible to use AI-powered bots to manage conversations at scale.
“Chat is good when powered by humans,” said O’Donnell. “Chat is awesome when powered by artificial intelligence.”
It’s no coincidence that earlier this month HubSpot announced the acquisition of Motion AI, a company that helps people deploy chatbots at scale without developers, and that Conversations is debuting now.
Why are chatbots critical to the future of inbound? Says HubSpot Chief Strategy Officer Bradford Coffey writing in Medium about the Motion AI acquisition:
“At HubSpot, we study human behavior and then build products to match the way modern buyers shop, learn, and communicate. Observing how people discovered content via search in Google was our first big insight and it formed the foundation what we’d eventually call ‘inbound marketing’. Later, having observed how people consumed content they’d subscribed to, we moved aggressively into marketing automation. In the last few years we’ve observed a new behavior: The rise of messaging and chat.”
Artificial intelligence now powers HubSpot capabilities across the Attract, Convert, Close, and Delight stages of the inbound methodology.
In the past, marketers had to grasp that the customer journey had changed thanks to the internet. They needed to undertake digital transformation, and align their businesses with the search and content habits of modern consumers.
Today, marketers need to understand how inbound specifically has changed in the age of AI. The tools now exist to develop one-to-one inbound relationships with prospects and customers—at scale. It can be difficult to understand just how profound this change will be, because inbound marketing AI is still in its early days.
But other disciplines have already been transformed by AI. If you want to understand where inbound is going, look to finance.
In the 1980s, AI was first deployed on Wall Street. It didn’t change how firms made money; they still profited from advisory fees and successful trades. But it did transform how traders did their jobs.
At first, AI gave superpowers to a select few traders who used it to capitalize on opportunities faster and at scale in ways that all-human teams just couldn’t do. AI traded at speed and surfaced market insights better than people did.
The benefits were so great, adoption was a no-brainer. Today, high frequency trades performed by AI comprise more than 60% of all trades. Quants at investment banks use algorithms to find new opportunities before the competition. And AI is used to do costly, time-consuming back office tasks in a fraction of the time for a fraction of the cost.
In short, you can’t do investment banking effectively without some form of AI.
Expect a similar trajectory in inbound marketing.
The inbound marketers who begin to deploy AI will see outsized benefits. The benefits to using AI will be so great that inbound marketing without some type of AI won’t make economic sense. And the industry movement birthed by companies like HubSpot will finally achieve its ultimate goal:
Attract, convert, close, and delight at scale.
But to realize a bright future in inbound marketing AI, marketers need to evolve.
What Artificial Intelligence Means for Inbound Marketers
So how can inbound marketers evolve in the age of artificial intelligence?
It’s important to start with use cases.
What inbound marketing challenges are you trying to solve? These might include growing traffic, scaling content creation, or generating more leads. In fact, AI can currently produce results across each of the four stages of inbound:
- Attract — Natural language processing (NLP) and natural language generation (NLG) are AI technologies that can automate and accelerate content creation and scaling. Look at solutions like Grammarly, Automated Insights, Acrolinx, and HubSpot’s Content Strategy tool.
- Convert — AI systems can personalize and test pages, improving conversions at scale. Look into OneSpot and Cortex to start.
- Close — AI excels at extracting insights from data that humans miss or can’t find themselves. This intel is invaluable for surfacing new lead opportunities and closing existing opportunities. Check into solutions like Node (backed by Mark Cuban) or Seventh Sense.
- Delight — AI-powered tools can improve the customer experiences by helping buyers. They can also give buyers more of what they like. Look into the recent HubSpot acquisition of Motion AI, a chatbot maker. The platform will now offer bots to delight customers at scale. Also look at Klevu, an AI ecommerce tool that shows buyers products they might like.
Once you determine use cases, start researching potential ways AI can help. The Marketing AI Institute blog is a great place to start. We publish exclusive interviews with AI providers and actionable advice on use cases. Subscribe today to get this content before anyone else.
Don’t be afraid to tap into the expertise of your existing vendors. Companies like HubSpot can offer guidance on AI needs and tools. Marketing AI startups we've talked to are also eager to talk shop with marketers.
Inbound marketing is changing thanks to artificial intelligence. Marketers who embrace AI now stand to leapfrog the competition. In the process, they'll accelerate their campaigns, companies, and careers.
So get out there and research, vet, test, and try the technology that’s available. You’ll discover how AI can give your inbound marketing program superpowers.
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