Digital Marketing

AI is the Future of Marketing

by
Craig Wisneski
,
October 6, 2021

It would be hard to overstate the potential of AI in digital marketing. AI is set to have a transformative impact on many aspects of marketing, transforming how we engage with customers and prospects, how we source leads, develop campaigns, measure our performance, and make strategic decisions. 

To realize these benefits, every company in Big Tech is either investing heavily into AI or already has AI-based products and services on their platform. In fact, 77% of spending on AI was kept stable or increased during the COVID-19 pandemic.

It’s important that SMEs don’t miss out on this AI race, so we’ll explore everything you need to know about AI for marketing, and how you can implement it today.

What is AI Marketing?

The field of AI-driven marketing has been evolving at a rapid pace and is now becoming mainstream. Let’s explore the four main components of AI marketing: big data, machine learning, natural language processing (NLP), and platform solutions.

Big Data Analysis

Simply put, big data analysis refers to the analysis of massive amounts of structured or unstructured data. When you take a step back and consider how much information we produce daily — tweets, blog posts, status updates, emails, usage data — it’s easy to see why so many are trying to figure out ways to leverage this wealth of data across all industries.

While there are many advantages to utilizing big data in marketing efforts, with its history as an art rather than a science, finding actionable insights has definitely been challenging for most marketers.

Thankfully, advances have been made in recent years that have enabled marketers at every level to strive towards the holy grail – true insight from big data. With no-code AI platforms like Akkio now available, we’ve finally reached the point where any marketer can harness the power of big data.

Machine Learning 

Machine learning refers to the ability of computers to learn without being explicitly programmed. It uses algorithms that enable computers to identify patterns in large data sets and make predictions based on those patterns. 

Machine learning algorithms are becoming increasingly sophisticated, enabling computers to automatically improve their performance over time by continuously collecting new data and then using that data to improve their decisions going forward—all without human intervention required.

For example, Netflix uses neural networks to predict whether a user will enjoy a given movie or TV show based on previous viewing history. This allows them to recommend movies and shows personalized for each individual user.

Another company using machine learning is Airbnb, which uses a recommendation engine to help match guests with accommodations based on preferences. 

Neural networks are also used by the likes of Google Search, YouTube, and Facebook to rank and return the right content – making the experience more relevant for each individual user.

NLP

NLP (natural language processing) is a subfield of computer science that studies how computers can understand human language. It's the field of study that powers services like Google Translate, Siri, and Alexa. 

In the past decade or so, NLP has become an increasingly important part of many different industries. From healthcare to law to education, NLP is being used to power some of our most important tools and services. 

And it's not hard to see why – with advances in technology comes the opportunity for marketers to create more personalized experiences for their customers. Marketers can quickly classify text, for everything from negative tweet flagging to targeted nurture campaigns or prioritizing customer support tickets.

The Akkio AI Text Classification demo

Platform Solutions

The idea behind AI is simple: given enough data, computers can learn and make decisions on their own. It’s what makes them so powerful – they can perform tasks that would otherwise be impossible for humans to do at scale.

But there’s a problem with the traditional approach: it requires code. No-code AI refers to the use of machine learning algorithms without any programming required on the part of the user. In other words, instead of writing code from scratch, users can simply drag and drop their data into an existing platform and let the computer figure out how to process it on its own.

This approach has obvious advantages over coding, including massive time and cost savings. You also get access to powerful machine learning tools without having any prior experience using them yourself.

Before no-code, companies had to use programmatic AI tools like Amazon AWS or Microsoft Azure, which put AI technology out of the reach of most startups. Now, any firm with customer data can implement predictive modeling in their marketing processes, improving the customer experience while saving time through marketing automation.

What will the benefits be?

Marketing is an important part of any business. It's the process of communicating your company's message to your target market, and it has a big impact on sales. But marketing has traditionally been a very manual process. Marketers would create content, design ads, run campaigns, score leads…all by hand.

But now, with the help of AI-powered tools, we can automate many aspects of marketing. This means that marketers don't have to spend as much time on repetitive tasks like lead scoring or optimizing ad campaigns — they can instead focus on more thoughtful activities like marketing strategy or creative inspiration.

Automation

The main benefit of AI is that it can be used to rapidly automate tasks that previously took human beings a lot of manual labor to perform. This is especially true for sales and marketing, where many marketers spend countless hours figuring out how to optimize metrics in tools like Hubspot, Salesforce, Mailchimp, and Google Analytics.

With AI-powered tools, you can now outsource these tasks to computers which can then process massive amounts of data at lightning speeds. This means you can now spend your time on other things like strategy development instead of performing menial work. 

Marketing Measurement and Increased ROI

Marketing measurement is a major challenge for any business.

Traditional marketing measurement methods have not kept up with the rapid pace of change in the digital world. Companies are spending more on digital advertising than ever before, but many still struggle to measure its success.

And even when you do measure your marketing efforts accurately, it’s hard to know if your money is being spent wisely. The benefits of AI in marketing are many: It can help you improve your conversion rates by identifying which customers are most likely to become buyers; it can help you predict how customers will respond to different types of content or offers; and it can even help you understand the emotional connection between your brand and your target audience so that you can better connect with them.

Personalization

Ask any marketer, and you’ll find that personalized marketing is far more effective than non-personalized marketing. This makes sense from the consumer standpoint as well: We want to feel like brands and companies care about us and our needs, instead of being treated like just another row in a lead database.

AI allows you to implement personalization quickly and effectively. You can get personalization at a massive scale, very quickly. Previously, you would have to manually analyze personas and create personalized content based on them. AI can generate customer profiles for you and uncover trends that can be leveraged.

Smoother Decision-Making

Decision-making is a complex, iterative process that involves multiple stakeholders and is influenced by many factors. The benefits of AI in marketing are not only about making better decisions faster. They are also about reducing the burden on humans to make more nuanced decisions.

One of the most important benefits of AI is that it can free up time and cognitive resources for more strategic, creative work. The ability to automate repetitive tasks frees up employees’ time to focus on higher-value activities. It also allows them to be more productive by working on projects that require more thought and creativity.

Reduced Errors

Marketing errors are a fact of life. It’s estimated, for example, that over 80% of marketing emails remain unopened.

This is largely because we humans make mistakes when we interact with overwhelming amounts of data and complexity, whether it’s targeting the wrong leads or messaging at the wrong times. The good news is that AI can help us avoid these mistakes and reap the rewards of smarter marketing. 

What fields will be improved with AI?

AI can improve marketing in every area, including CRMs, sales funnels, sales forecasting, churn prediction, lead scoring, and content creation. Let’s look at each of these in-depth.

CRM, Personalization, and Audience Segmentation

CRMs are set to benefit tremendously from AI, as it will deliver on the promise of personalized experiences. Consumers today expect their online experience to be tailored to their unique needs and preferences. And they’re not alone: Companies are starting to wake up to the potential of CRMs for personalization.

The quest for customer personalization is only going to get harder over time, as more data becomes available and consumers move deeper into the “always-on” digital world where they expect an increasingly seamless and engaging user experience across all channels. This represents a huge opportunity for CRMs that can help brands engage with customers in meaningful ways. 

AI will unlock new levels of performance for CRMs through automated personalization that was once reserved only for direct mail campaigns or highly advanced cable TV targeting efforts. With access to large volumes of consumer data, algorithms can now be trained on what actually works when it comes to specific customer segments based on behaviors, interests, buying patterns, location, search history, and so on.

Sales Funnel Optimization

Sales funnel optimization involves optimizing all aspects of your sales process so that each stage drives conversions and generates incremental revenue. The key to achievement lies in identifying the weak links in the sales process, identifying pain points that can be solved with your product/service, and identifying customer touch-points at which you can provide value before they become loyal customers. 

The four stages of the sales funnel: Awareness, interest, desire, and action.

Optimizing the entire sales funnel will maximize revenue by ensuring that every stage of the sales process is running smoothly, and that these leads are converted into customers as soon as possible. In other words, it's about getting prospects through each stage of your sales funnel as efficiently and effectively as possible. 

AI can let you take customers through a personalized sales journey, based on past data that has seen similar customers convert. Further, AI-based chatbots allow a one-to-many sales process rather than a one-to-one form of customer service to help guide users through the funnel.

Sales Forecasting

AI-powered sales forecasting will be a game-changer. We now have access to data that was previously inaccessible or prohibitively costly, and that will enable us to build sales models that were not possible before.

With AI-powered forecasting solutions like those provided by Akkio, these types of insights become possible for any business — large or small — regardless of industry or product/service line focus.

Churn Prediction

Churn prediction is the art and science of identifying customers who are likely to leave your business. Up-to-date analytics can save you time and money by keeping your customer base from shrinking, so you can stay focused on growing your revenue. Your core business may evolve as a result, improving profitability, in addition to adopting more strategic growth initiatives.

While it’s no secret that businesses use data analytics tools to help them understand their customers and market trends, advances in AI promise even greater insights into what keeps users engaged with brands—and which ones are at risk of abandoning ship. 

And while many companies will likely be able to take advantage of these new analytical capabilities with little effort or cost increase—they can also expect a return on their investment within months.

Augmented Lead Scoring

Scoring leads is a complicated act. That’s particularly true in the B2B world, where customers interact with your company on different channels, engage with multiple sales teams, and apply very different needs to every opportunity.

When you add more moving parts to the lead scoring equation, it's no wonder lead quality has been lagging behind as businesses have increased their use of online marketing channels.

...But this is about to change. AI will quickly solve this once-intractable problem by creating customized marketing campaigns based on specific data points that may be available from other sources—including webinars, PDF downloads, industry publications read, social media activity, lead size, contact points, and so on.

Imagine an airline trying to sell tickets for its next flight. It has all of its historical passenger data, which is a treasure trove of information about individual customers and their behaviors: Who bought tickets? How many at once? For how many seats? And so on. All this can be used to predict whether a new lead will convert.

AI-powered Content

Figuring out what content to create is a constant struggle. And the struggle is only exacerbated when it comes to creating engaging, high-quality content that will attract and keep an audience. After all, there are only 24 hours in a day – and quite a few other things vying for your time and attention.

But algorithms aren’t human. So what can we expect from artificial intelligence? With AI, marketers can focus on what they do best: curating engaging, relevant content. With AI, marketers can better prioritize content creation efforts, or more simply, automatically tag existing content to increase its discoverability.

Further, new content marketing tools like CoPilot AI use deep learning to enable use cases like generating email marketing subject lines, LinkedIn marketing messages, or even SEO-friendly e-commerce product descriptions. 

When it comes to content, the use of AI extends to messenger bots to address customer needs in real-time, or even matching voice search queries to relevant search engine results.

Conclusion

How can you be part of the next big trend in marketing? With Akkio, AI-powered marketing is no longer confined to huge companies with dedicated AI teams and huge datasets to draw on. Akkio is a no-code, scalable machine learning solution for everyone. 

Further, Akkio integrates with all of your most commonly used platforms and APIs, from Zapier to Google Sheets to CRMs like Salesforce. In short, you can nearly instantly add AI to any application. Try out a free trial of Akkio to get started implementing AI in your digital marketing strategy.

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