How to incorporate the relevant AI tools into your martech stack
AI has become an important part of the marketing landscape whether we like it or not! Luckily, there are some incredibly useful AI tools available, helping marketers streamline tasks, accelerate campaigns, and drive better ROI. One major downside to influx of AI tools is that there are more tools to choose from than time or resources available to vet them in many marketing teams. This can make incorporating new AI tools a challenge for even the biggest teams. However, adopting a strategic vetting process and following a few guidelines can make choosing the right marketing tools for your team faster and more streamlined.
Why AI tools are worth the investment
After the first version of ChatGPT burst onto the scene, all marketing tools started to incorporate AI chatbots and functionalities into existing tools, and SaaS companies started offering new AI-driven marketing tools by the dozen. Each iteration on AI put them leaps and bounds ahead in terms of predictive analytics, automation, reporting, and more. Now, is perhaps the perfect time to invest in AI marketing tools because they have gone through multiple iterations and are at a stage where the cost-to-benefit ratio now works in your favor, meaning you pay less for more!
The benefits of many AI tools can be numerous, as long as they are in line with your marketing objectives. AI marketing tools provide efficiencies in content creation, design, administrative tasks, advertising campaigns, metrics and reporting, and many more areas of digital marketing. We find many of our clients use AI tools to:
- Drive better decision making with predictive analytics and robust reporting
- Help their teams save time on data entry, administrative tasks, and scheduling
- Achieve better personalization for campaigns
- Improve ROI on advertising campaigns through targeting and optimization
- Improve the customer experience with customer support
- Reduce costs on campaigns
One thing to do before investing in a new AI tool is to implement the AI functionalities that exist in the current marketing tools you use to see if that solves some of the initial pain points. Canva, for instance, created an AI Magic tool can update designs, create designs from text inputs, and so much more. Overall AI tools are not going anywhere, they’re only getting better, so it makes sense to start incorporating them into your martech stack with the understanding that they are tools, not replacements for people or good processes.
Getting started with AI tools
The first step when adopting any new tool, AI or otherwise, is to complete a comprehensive team and tool benchmark that includes:
- List of your team’s current tools and their purpose
- Common challenges the marketing team faces
- Marketing priorities for the next few months
- Breakdown of where the marketing team invests most of their time (ie: admin, advertising, content, etc)
Spend enough time on this part of the process to gain a good idea of where you are at, but also recognize that things may change and this does not need to be super precise. Ideally, this will give you a map of your team and their processes and highlight where a tool might be able to provide increased efficiencies, added insights, or better ROI. Most teams decide on tools that can deliver a skill or capability that the members do not have or they choose a tool to cover repetitive or administrative tasks so team members can spend more time on creative or strategy-focused pursuits.
Build a process for vetting tools (across the organization)
The next step in the process is to create a tool vetting process which will allow you to streamline the tools you incorporate and prevent you from adopting a slew of new tools just because they seem innovative or helpful. A robust marketing technology stack should help you achieve more with less, not create more work.
When each tool has to pass through the same screening, you are more likely to get the most from that tool, prevent tool overload, and save money. Typically, a tool vetting process will include defining objectives, discussing the tool with people or organizations that use it, investing in free or paid trials, outlining integrations with current systems and tools, getting feedback from stakeholders, and building out a comprehensive budget. It can get tricky when you are buying tools to be used across multiple locations, but most SaaS providers will be able to offer a corporate or top-tier membership for multi-location businesses or provide some sort of customization. The key here is to look at the overall cost vs benefit and avoid purchasing software and tools that aren’t adding value to your marketing processes.
Organization-wide adoption is key
If the tool gets past the vetting process, the next step will be to create an adoption plan. An adoption plan incorporates the steps needed to get everyone up and running on the tool and perform any customizations and integrations that need to happen. Training users will be a key part of the adoption plan to facilitate team-wide adoption. You should also incorporate ideas for maintaining, optimizing, and evaluating if the AI tool is achieving the objectives you and your team have set forth. Most AI tools will be incorporating new features regularly as the algorithms and capabilities are updated, so it makes sense to keep evolving your use of the tool.
There is nothing worse than putting effort into adopting a new tool only to have it sit unused because it doesn’t have a certain integration or someone doesn’t like the interface. Hopefully, by using the guidelines provided above you can avoid such a fate this time around!
If you have new AI tools you’ve been investigating but aren’t sure if they are the right fit, reach out to MDG. We’re here to help!