How Marketers Optimize Budget Efficiency with Artificial Intelligence

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How Marketers Optimize Budget Efficiency with Artificial Intelligence

I remember when AI was just starting to make some buzz. Everyone was talking about this new tool called ChatGPT, so I made a login and went to town. Well, “went to town” may be putting it generously — I typed the prompt, “Please write an outline for a blog post about call tracking.” “Please” being the operative word because, as the polite midwesterner that I am, I can’t stand the thought of anyone thinking I’m rude — even a large language model. ChatGPT’s output was surprisingly passable — probably because I used the magic word. 

The introduction of ChatGPT showed businesses the vast potential that AI has to increase productivity. Our new State of AI in Digital Marketing Report found that marketing teams have earmarked significant portions of their budgets for AI tools. These tools go far beyond large language models — marketers are also investing in tools that they can use to optimize their digital campaigns. 

In this post, we’ll dive into some of the results from our State of AI in Digital Marketing Report and show you how you can use AI to optimize your marketing campaign budget.

Marketing AI Investment Will Soar in 2024

The recession fears we experienced in the past two years are dying down. Economists predict that the economy will stabilize in 2024 and, as a result, many companies are loosening the purse strings of their marketing budgets.

Marketers are eager to spend their budgets on AI in 2024. Nearly 90% of respondents said that they will increase their investment in AI next year and an equal number said they will have a budget dedicated to AI-powered martech.

Smaller companies will invest more in AI than larger companies with 42% of those at companies with fewer than 1,000 employees saying they will significantly increase their AI investment in 2024 compared to 27% at companies with over 1,000 employees.

Top Areas for AI Investment Include Programmatic Advertising and Conversation Intelligence AI

Marketing teams are going all in on AI in the coming year, exploring a wide range of use cases. In our report, respondents said they planned to use the following tools over the next twelve months:

  • Programmatic advertising
  • Conversation intelligence AI
  • A/B testing tools
  • Recommendation engines
  • Social Listening tools
  • Generative AI for images
  • SEO optimization tools
  • Generative AI for content generation
  • Chatbots and virtual assistants
  • Natural language processing
  • Predictive analytics

Programmatic advertising and conversation intelligence AI are of particular interest in the coming year, with 60% and 53% of marketers saying they plan to use these tools in 2024, respectively. 

Marketing Teams Are Investing in AI to Support Their Top-Level Goal of Improving ROAS

Marketers aren’t just deploying AI because it’s the shiny new thing — they’re selecting AI tools that correspond with their organizational goals. Budget efficiency is definitely top of mind, as one of the most important goals they listed was to improve ROAS.

How to Use Conversation Intelligence AI to Optimize Marketing Budget Efficiency

Our study found that marketers are highly motivated to invest in AI tools in 2024. One of their most important goals is to optimize budget efficiency and improve ROAS so that their marketing dollars go further. 

When marketers think about using AI to improve budget efficiency, they usually think about tools like Google Smart Bidding, which automatically makes the most efficient bids to meet campaign goals. However, automated bidding tools are only one piece of the puzzle. Leading marketing teams are also using conversation intelligence AI to achieve a significant lift in ROAS. Keep reading to learn how it works! 

If You’re Not Using Conversation Intelligence AI, You’re Likely Underreporting Your Conversions

If you’re not using conversation intelligence today and your marketing campaigns drive leads to call and set appointments, make purchases, or get quotes, you’re probably not accounting for 20-50% of the conversions you drive. This results in inaccurate measurement of your ROI, wasted ad spend, and suboptimal performance from your automated bidding tools.

If you’re using Google Ads’ call tracking feature, you have a better idea of how well your campaigns are performing than you would by flying blind. Google Ads can show how many total calls your campaigns drive, but bear in mind it can only count calls and can’t determine call outcomes, so many of those calls might not be conversions. They could be customer service calls, people asking about operating hours, calling for driving directions, or even callers with the wrong number.

Here’s an example of how using call volume instead of conversion volume to optimize campaigns throws everything off. If you’re just looking at call volume, you would put your money behind the “Corp Bank Trust” keyword. But once you can see the conversions that happen on the phone, you’ll see you put the money in the wrong place as “first-time mortgage” was driving more conversions.

If you want a truly accurate picture of campaign performance you need conversation intelligence. Tools like Invoca use artificial intelligence to determine not just that calls occurred, but also if those calls were leads, if the caller converted, and how much revenue was generated. This allows you to calculate your full ROI and report it to your leadership team. It also allows you to allocate your marketing budget more efficiently, so you can double down on what’s working and cut what’s not.

Tracking Calls with Conversation Intelligence AI Enables Better Automated Bidding Performance

If you’re not using conversation intelligence, your automated bidding tools like Google Smart Bidding are likely underperforming. That’s because automated bidding tools work by tracking the number of conversions each ad variation is driving and then optimizing bids based on what’s performing best. If you’re not tracking the phone call conversions your ads drive with conversation intelligence AI, you’re not giving the tool a full picture of your performance. As a result, it could be allocating too many marketing dollars to underperforming ads or failing to prioritize ads that are driving a high volume of phone leads.

Invoca conversation intelligence integrates with Google Ads, allowing you to stream call conversion data to the platform in real time. This allows Google’s Smart Bidding algorithm to make better, more informed bids on your behalf, regardless of what your campaign goals may be and which bidding strategy you use.

How Rogers Communications decreased CPA by 82% with Invoca + Google Ads

A great example of this integration in action comes from Rogers Communications, Canada’s largest telecom company. Rogers used Invoca’s AI to understand not just which customers converted over the phone, but the average value of the conversion for each customer type. With this data, they were able to understand the revenue that each paid search campaign, ad, and keyword was driving — both online and over the phone. They could then feed this revenue data into Google Ads to inform Smart Bidding. Smart Bidding weighs their bids in proportion to their returns, decreasing their cost per acquisition by 82%. They also achieved an 18% lift in net revenue from paid search.

“The results with Invoca have been phenomenal, to say the least,” said Farrell. “The benefits are constantly compounding with such minimal lift for the returns. I’ve never had a product where I spend more time selling people on the results than doing the work to get it going.”

Read the full Rogers Communications case study here

Conversation Intelligence AI Captures Rich First-Party Caller Data to Enhance Retargeting 

Conversation intelligence AI doesn’t just help you improve your bidding strategy, it also enables you to improve ad targeting. First-party data is the backbone of any ad targeting strategy — the more of it you have at your fingertips, the better you can anticipate your customers’ needs and preferences. With conversation intelligence, you can tap into one of the richest available sources of first-party data: phone conversations. 

Phone conversations contain more insights than an online form fill ever could — when your customers call you, they tell you about their needs, preferences, and how to make them happy. Conversation intelligence AI analyzes these conversations at scale and mines them for insights. The beauty of Invoca’s Signal AI Studio is that you can easily train the AI to capture whichever data points are most relevant to your business — for example, you can track products callers expressed interest in, if they were price-sensitive, and if they made a purchase. Check out the graphic below to see more of the data points you can collect with Invoca:

With these deep conversation insights, you can build more complete customer profiles and target your audience with more relevant ads. Below are a few common examples of retargeting and suppression strategies marketers use with Invoca’s first-party data:

  • Retarget callers who didn’t make a purchase with ads for the products they mentioned over the phone
  • Retarget callers who bought over the phone with ads for relevant companion purchases
  • Retarget callers who expressed price sensitivity with ads touting a special discount code
  • Suppress callers who bought over the phone from seeing future ads for that product or service

How AutoNation uses Invoca to retarget customers more effectively

With over 300 locations, AutoNation is America’s largest auto retailer. With Invoca, AutoNation sends buyers personalized marketing campaigns touting the type of features they mentioned over the phone. For example, if a caller mentions safety features, the marketing team can retarget them with ads touting their desired vehicle’s safety ratings. If a caller mentions performance, the team can retarget them with ads showcasing horsepower.

“The car buyer journey is different for everyone — some people want safety features and others want performance. Invoca has helped us tap into phone conversations so we can understand each buyer’s unique needs. As a result, we can deliver a truly peerless car-buying experience,” said Marc Cannon, executive vice president and chief customer experience officer at AutoNation.

Read the full AutoNation case study here

Looking Ahead: Marketers Are Leaning on AI

With digital advertising spend increasing in the coming year, it will be tougher than ever to cut through the noise. Every ad dollar will count, and marketers will need to stretch their budgets even further to keep up with the competition. That’s why there’s such a keen interest in AI tools for budget optimization. Marketers who use AI to make their ad dollars work harder will gain a clear edge in this landscape. Those who fail to adapt, meanwhile, will be left behind.

Download the Full State of AI in Digital Marketing Report 

Want to learn more about how marketers plan to use AI in 2024 and beyond? Check out our full State of AI in Digital Marketing Report

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