Four Big Ways AI is Improving Martech and How You Can Ride the Wave

By: Syed Ahmed, SVP of Engineering & Operations at Act-On Software

Martech can help marketing teams operate at ten times their capacity, and the rollout of better AI-driven solutions opens a whole new realm of possibilities to further boost efficiency. Martech companies everywhere are working to utilize AI developments to improve functions and help clients earn better marketing success.

Whether it’s crafting the perfect email, minimizing churn, polishing lead scoring, or producing training videos, outdated manual processes can gum up the works.?

A December 2021 LeanData survey of more than 1,700 sales, marketing, and ops professionals noted the top method for routing leads was still manual. In the realm of marketing “automation,” that’s not so automated, huh? That’s where AI is helping boost martech performance in ways never thought possible. So let’s break it down!

1. Email Content

Email messaging to customers is an area of ongoing refinement. You’ve no doubt jumped on the ChatGPT trend to churn out messages in seconds. When writer’s block hits, it’s a quick way to jumpstart your creativity through AI.?

Vipul Vyas, Senior Vice President of Go-To-Market Strategy at Persado, recently noted a major airline used the AI platform to improve messaging, which “boosted bookings by nearly 68%.” After a little experimentation with prompts, you too can also develop messaging to better reach and engage with your target audiences.

2. Customer Churn

AI can come in clutch to help companies retain clients, as well. A recent study from SkyQuest noted 25% of clients stop engagement with a company after only one negative experience. Instead of going on instinct alone, companies can use AI tools optimized for productivity like Gong or Wingman to learn about customers’ potential churn warning signs (mentions of competitors, lowered response rates, etc.) before clients fly the coop.??

3. Lead Scoring

Evaluating lead scoring is often trickier than it seems.?Many behaviors can be weighed arbitrarily, based purely on emotion, rather than concrete data-driven frames of reference. Predictive scoring models driven by AI can help suggest wiser choices in the future by digging into past success rates (customers in the Education Industry are trending positive, Lead Source is showing good responsiveness, etc.). There’s a lot of good data already there that AI can analyze in a snap and with more objectivity.

4. Multimedia

SEO is best friends with video and image content. Picture having tutorial videos for your users on new features, not only upping your company profile, but also helping your customers. Before AI, this involved many more steps to accomplish. After writing a script, capturing footage manually, editing the footage, recording voiceover, getting a composer to write custom music, uploading and cross posting on social media, one likely will have spent several hours on what looks like a “simple" TikTok video.

Flipping this process into AI can make a huge time difference. Utilize Copymatic for writing copy for a rough script, ChatGPT for delivering variants, Beatoven for soundtrack creation, Cleanvoice for voice cleanup, and Synthesia for cutting everything together.

A 2020 study showed teachers could save up to 13 hours a week in content creation thanks to the time saved by AI, so why not marketers? When it comes to saving money and time, AI lends a big advantage to regaining control of your workflow.

While inefficiencies may lurk in your current processes, utilizing AI-driven apps can help close the gap. As John Wooden once said, “The main ingredient of stardom is the rest of the team.” Think of AI as a versatile team member, ready to take on tasks that would bog down the rest. This will help your martech business succeed and innovate!

Syed Ahmed is a technology leader with more than 20 years of experience building software that is used by millions of customers every day. He specializes in building scalable software, distributing software architectures and applying big data analytics to synthesize complex real-world problems.?