Chief marketing officers are under pressure to hit certain KPIs, whether they’re related to revenue, awareness, or costs.
Amidst this pressure, there are opportunities for AI to boost these metrics and help marketers to prove ROI.
For tech buyers in evaluation mode, it’s critical to recognize which marketing KPIs they’ll be judged on, and which tools can improve those metrics.
Follow the Money: Connecting Every Click to Revenue
What it is: This metric looks to measure the qualified business opportunities that have either been sourced or influenced by the work of the marketing team.
Teams measure this by tracking engaged potential customers and the touchpoints they’ve interacted with, whether its demos, landing pages, chatbots, or newsletters, for example.
With this information, CMOs and the board can assess which channels are the most valuable. This allows for resources to then be allocated appropriately.
How AI helps: With its capabilities for advanced data analysis, AI can stitch every meaningful touch back to the account. Whether it’s an ad click, webinar, email, or site visit.
In the past, attribution models prioritized a customer’s first touch (the first interaction they have with your brand) or the last touch (the final step before conversion).
However, AI software can now see the entire complex multi-touch journey of the modern customer. In practice, that means less spreadsheet wrangling and a defensible, CFO-ready number tied to the CRM.
Filtering only successful conversions helps eliminate vanity metrics and reward channels that genuinely drive results. And AI can keep all of this shared data clean automatically, reducing errors and letting sales reps sell instead of sorting through systems.
Predictive AI: Prioritizing the Prospects That Matter
What it is: Marketing teams are often measured on how well they combine with the downstream sales reps. This is usually done by looking at the quality of leads they pass to Sales, and the speed (Lead Velocity Rate) that they do this.
These metrics let decision-makers predict revenue and assess how efficiently demand turns into opportunities.
How AI helps: The first key step to improving lead generation is smarter prioritization of potential customers.
Predictive AI ranks prospects by behavior and intent, helping sales reps focus on high-quality leads faster.
AI can also take a conservational form to handle FAQs and automatically book meetings for high-intent visitors. This shortens the time from website visit to sales meeting, boosting the number of priority leads.
Smarter Spend, Sharper ROI
What it is: Beyond revenue considerations, marketers are also expected to deliver ROI in a financial sense.
One of the most common marketing KPIs is the customer acquisition cost. It measures whether marketing investments deliver strong returns.
These costs can include the spending on paid advertisements, creative production costs, conference travel budgets, and the costs of marketing tools being deployed.
How AI helps: Generative AI reduces the cost of creating marketing content. Marketing text, visuals, and landing pages can all be crafted by AI to suit unique target audiences with ease.
Furthermore, effective audience analytics reveal which channels customers use most. This will help an enterprise to decide whether they should pause or cut underperforming paid campaigns.
AI That Thinks Like a CMO
For buyers in evaluation mode, the mandate is clear: choose AI that does the boring work brilliantly – identity, attribution, prioritization, scheduling, and hygiene.
Whatever KPI they pursue, AI enables marketers to focus on high-value work like positioning, discovery, and closing.
Navigate the sales & marketing landscape
To discover how technology can transform workplace productivity in your marketing team, dive into CX Today’s Ultimate Guide to Sales & Marketing Technology.
