The Ultimate Guide to AI for Marketing

Future of Work
Use Cases

Comprehensive guide to how marketers can use AI, how it works, and where it's headed.

AI, or artificial intelligence, stirs up excitement and fear in equal amounts.

People are excited by the utopian prospect of AI creating massive abundance, to the point where business magnates predict that AI will create $13,500 in value for every adult.

But people also fear the prospect of AI-induced job loss, unethical AI that reinforces biases, or even AI that we can’t control.

AI is Everywhere

After all, AI is already all around us. When you search on Google, you receive AI-powered search results that are tailored specifically to you. Your experience on Netflix, Amazon, or Tinder may be completely different from those around you, as you see AI-powered recommendations that target your interests. There are already over 300,000 bots on Facebook Messenger, and over 100 million Alexa listening devices in our living spaces.

The applications of AI go far beyond consumer apps, and even into loan applications, job applications, and crime.

AI is multiplying, year by year, and the large majority of AI experts—nearly 80%, according to one survey—foresee a technological singularity, in which the power of AI becomes absolute. Max Hodak, co-founder of the revolutionary brain-machine interface company Neuralink, predicts that we’ll reach Artificial General Intelligence by 2030

AI For Marketing

Getting down to earth, there are many ways businesses can make use of AI today, especially in marketing.

Here are 5 practical strategies.

1. Optimizing Email Open Rates

In 2021, we’re all getting bombarded with emails.

Even if we’re genuinely interested in the contents of an email, most of us would never have the time to go through all our emails. Thus, we have to be selective.

This means that email marketers need to stand out, and carefully optimize their emails to maximize the likelihood of them being opened. Given a historical dataset of email open rates, you can build a model in Obviously AI to predict and optimize open rates.

A number of factors can impact email open rates, such as the email word count, the number of links, and the total number of images. Figuring out the complex relationships of these variables manually would not only be inefficient, but even infeasible.

With Obviously AI’s no-code machine learning, you can easily find out how to tweak your emails to get opened.

2. Lead Scoring

We all know that not all leads are equal.

Some leads have virtually no chance of converting, while others are red-hot, even before nurturing.

If your sales and marketing teams are spending an equal amount of time on these leads—as many teams are—then you’re missing out on conversion opportunities. Lead scoring enables teams to laser-focus on the leads most likely to convert.

Traditionally, teams would build a matrix to score leads based on factors like expressed interest levels, disclosed interests, or number of interactions. Now, teams can use Obviously AI to automatically score leads.

Given a marketing dataset with historical conversion or “response” rates, you can predict whether a new lead is likely to convert, and score leads accordingly.

3. Optimizing Direct Mail

If you think direct marketing (sending snail mail) is an outdated technique, then you’re missing out.

In fact, up to 90% of direct mail gets opened, compared to around 20% of digital mail.

That said, direct mail isn’t automatically a golden ticket to getting a lead’s attention, and you need to optimize direct mail, lest it be categorized as physical “junk mail” and thrown out.

Just as with digital mail, a number of complex, inter-related factors impact the likelihood of direct mail getting opened.

With Obviously AI, you can use a historical dataset of direct mail open rates to optimize for the future.

4. Optimizing Sales Calls

Alongside direct mail, sales calls are a surprisingly powerful technique. While many brands are focused on the latest digital strategies, from chatbots to TikTok Ads, if you’re a B2B company that’s not deploying sales calls, you’re likely missing out.

Indeed, over 90% of customer interactions still happen over the phone. Given a historical dataset of sales calls, such as this Kaggle dataset, you can build an Obviously AI model to maximize lead conversion.

The success of a sales call depends on a number of factors, such as the client’s job and education, the salesperson’s date and time of contact, or even broader socioeconomic variables. No-code AI will automatically figure out the right combination of these variables to maximize the odds of success.

5. Optimize Cross-Selling

Cross-selling generates billions of dollars in revenue. If you’ve added a recommended item to your cart on Amazon, you’ve experienced a cross-sale. A cross-sales just means selling one item alongside another that a customer already planned on buying.

If you have a large number of products or services, this becomes impossible to do manually, especially with high accuracy. 

Using AI, you can accurately and instantly recommend the rights products and services to the right people, at the right time.

For example, you could upload this dataset on historical health insurance cross-sales to Obviously AI, and select the “Response” column to automatically predict which customer will be interested in a cross-sale.

Summary

For marketing campaigns to be successful, businesses need to use the latest technologies and meet the expectations of leads. Before AI, the status quo was gut feeling. With AI, you can take a data-driven approach and supercharge your marketing efforts.

To become an expert in marketing, you need to use AI. With that in mind, we hope you enjoyed these five powerful AI-based marketing strategies.

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