Chief marketing officers are under pressure to hit certain marketing KPIs. Whether they’re related to revenue, awareness, or costs, those marketing targets are getting tougher every year.
Amidst this pressure, there are clear opportunities for AI in Marketing to boost these metrics and help marketers prove ROI.
For tech buyers in evaluation mode, it’s critical to recognize which marketing KPIs they’ll be judged on. From there, they can identify which digital marketing tools in their martech stack can realistically improve those numbers.
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Follow the Money: Connecting Every Click to Revenue
What it is: 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 – a core marketing KPI for most CMOs tracking pipeline and marketing targets.
Teams measure this by tracking engaged potential customers and the touchpoints they’ve interacted with. This includes 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: How AI helps: With its capabilities for advanced data analysis, AI in Marketing can stitch every meaningful touch back to the account – whether it’s an ad click, webinar, email, or site visit. When connected into your martech stack and digital marketing tools, AI creates a defensible, CFO-ready view of where revenue truly comes from.
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 – both critical marketing KPIs when you’re setting quarterly marketing targets.
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 in marketing 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.
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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 (CAC). It measures whether marketing investments – especially spend on digital marketing tools and media – 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 in Marketing reduces the cost of creating content. Marketing text, visuals, and landing pages can all be crafted by AI to suit unique target audiences with ease, especially when these capabilities sit inside your existing martech stack and creative digital marketing tools.
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 in Marketing that does the boring work brilliantly – identity, attribution, prioritization, scheduling, and hygiene – and integrates smoothly into your martech stack.
Whatever marketing KPIs they pursue, the right digital marketing tools and AI enable marketers to focus on high-value work like positioning, discovery, and closing, rather than wrestling with spreadsheets and dashboards.
FAQs
What are marketing KPIs?
- Marketing KPIs are the specific numbers that show whether your marketing is working. These include lead volume, lead quality, customer acquisition cost, and pipeline results. In digital marketing, these KPIs are usually tied to how well your campaigns move people from click to qualified opportunity, and how efficiently you turn budget into revenue.
How does AI in marketing help CMOs achieve KPIs?
- AI in Marketing helps CMOs hit their marketing targets by automating analysis and decision-making that used to be manual. It can connect every touchpoint back to revenue, rank leads by intent, personalize content at scale, and highlight where budget should be shifted to get more impact from the same spend.
What role does the martech stack play in tracking KPIs?
- Your martech stack is the set of tools that collects and connects all your campaign and customer data. When AI is layered onto this stack, it can pull data from multiple tools to give a clearer view of core marketing KPIs. These can include which channels generate real opportunities and which audiences are most profitable.
Which digital marketing tools benefit the most from AI?
- AI adds the most value to digital marketing tools that handle large volumes of data or repetitive tasks. For example, analytics platforms, attribution tools, marketing automation, and ad-buying systems. In those areas, AI can automatically detect patterns, optimize targeting and bids, and create or adapt content so teams spend less time on manual work and more time on strategy.
How should marketing leaders use AI to improve attribution and lead quality?
- Marketing leaders should plug AI into their existing martech stack so it can see the full customer journey, not just the first or last click. From there, they can use AI models to assign credit across touchpoints, score leads based on behavior and fit, and focus sales and marketing efforts on the prospects most likely to convert. This directly improving attribution accuracy, lead quality, and key marketing KPIs.
To discover how technology can transform your marketing team, dive into CX Today’s Ultimate Guide to Sales & Marketing Technology.
