There are many ways to use AI in marketing, and it seems that for every smart initiative, 10 AI vendors have built a tool to address it.
At the start of this wave, I received more calls and responded to more emails than I do today. Over time, I realized that I was asking vendors the same handful of questions to assess whether their tools were worth deploying.
If you’re in the same boat and overwhelmed by vendor outreach, here are five questions to help you determine whether they’re worth it, along with why I’m asking them and what I’m looking to hear – or not hear.
1. What problem does your tool solve?
This question should help you understand the purpose of the tool and, more importantly, whether the value it creates aligns with actual business results.
If the vendor can’t clearly articulate the challenges or use cases the tool addresses, that means it wasn’t specifically designed to solve a real-world problem your team faces, whether you’re in-house or at an agency. Be wary of vendors who try to dazzle you with feature-rich language but can’t explain the business benefits those features provide.
If a vendor identifies at least one existing team problem that the tool solves and explains how it improves business outcomes, it’s a good idea to keep talking about it. A great follow-up question is to ask for a case study showing how the tool was used and the results it achieved for an organization similar to yours in size and verticality.
Look for benefits like “increases production” or “identifies tracking gaps to speed troubleshooting.” But don’t rush to invest in tools that promise to “save time” (even if they actually do), unless you have a plan for how you will use that extra time.
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2. What expertise do you have in the area where this tool solves a problem?
The answer to this question should tell you if the vendor built this toolForadvertisers or simplyhasadvertisers.
The technical aspects are important, as is understanding how a media buyer actually spends their day. If the vendor does not have personal experience with media buying, they should explain how they researched the media buying market and incorporated that information into the tool.
If they have a superficial understanding or lack expertise, that’s a red flag. It’s okay if a rep doesn’t have this expertise directly, but someone on their team should, and you should have access to that person as soon as possible if you intend to continue talking.
If a vendor has a story or journey that led them to identify a problem you can relate to and decide to create the solution themselves, that’s compelling. A founding mission that addresses your existing challenges provides a solid foundation for a tool that can make a difference in your team’s performance.
3. What case studies, real use cases and results can you share?
I mentioned case studies a few paragraphs above, and they are essential in a new, rapidly developing industry. I would look to understand if the vendor has an attractive track record with customers like me or if we would be an early adopter.
If you fall into the latter camp, there are pros and cons, just like any ad beta you can get to before your competitors. You may get a head start by finding an important growth accelerator before your competitors, you may spin your wheels trying to fix bugs, or you may find that the tool simply doesn’t deliver what it promises.
If you can’t trust a tool or there’s a risk that you’ll need to provide detailed feedback to make it work, it may not be the best use of your time and money, unless you think what it could possibly offer would be a game-changer.
If you clearly plan to be an early adopter and the vendor is not willing to be flexible on contract terms to mitigate risk, this is not a solution. More established tools will likely deliver more consistent value, although they will have less wiggle room on pricing as a result. However, newer tools that take a hard line on pricing and contract terms are unlikely to be good long-term partners.
For established vendors, you should look at specific, relevant case studies with real numbers from advertisers in a similar space, of a similar size, or with a similar use case.
If these are start-ups, the best answer is honesty: “You would be one of our first customers in this industry. Here’s what we’ve seen elsewhere and here’s what that partnership would look like.” This transparency is a green flag.
4. Who owns my data and how is it used to train models?
It’s interesting to see how easily people share data with AI and AI tools in the rush to find a competitive advantage. This is something I strongly advise potential buyers to consider before signing anything.
Watch for any responses that suggest your data is being used to train shared or third-party models without your explicit consent. Another red flag is vague or roundabout answers or terms of service that contradict or confuse what the seller is telling you verbally.
You own your data, period.
The provider should be able to clearly explain its data processing practices, including where your data is stored, how long it is retained, whether it is used for training the model (and, if so, only for refining your own instance), and what happens to your data if you stop using the tool. This should be in the contract, not just a verbal assurance. If not, insist that it be included before signing.
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5. What does implementation actually look like and what does success require from our team?
Before committing money, you need to understand the true cost of adopting this tool. This cost includes more than just the price. It’s time, internal lift (including onboarding, training and quality assurance) and any potential disruption to your existing martech stack.
If it requires resources that your team doesn’t have, or if you can’t realistically dedicate the time to making good use of the tool, it’s not worth the investment right now. Many marketers could avoid unnecessary martech spending if they asked this question and thought seriously about the answer.
No tool should be universal, but easy implementation and intuitive design are essential for your team to adopt and stick with it.
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Don’t let AI hype rush your decision
I know personally that many of these tools seem too good to be true – and they often are. You need to balance ambition for growth and curiosity with a little caution.
Remember, we are still in the early stages of AI adoption. If a tool seems too expensive or difficult to integrate, or if the contract is more rigid than it should be given the tool’s track record, a more attractive solution will likely emerge in the coming months.
If in doubt, request a free trial. Assuming that integrating the tool won’t create too much work for your team, this could be the right next step in determining whether you’ve found your next competitive advantage.
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