INBOX INSIGHTS, April 30, 2025: AI Integration Strategy Part 4, Marketing Job Market Demand - Trust Insights Marketing Analytics Consulting

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INBOX INSIGHTS: AI Integration Strategy Part 4, Marketing Job Market Demand (2025-04-30)

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Approaching AI Integration Strategically – Part 4: Measurement Framework

In Part 1 of this series, we talked about the STEM framework where the “M” stands for Measurement. In Part 2, we covered the 5P framework where “Performance” is the final P. Today, I want to show you how these pieces come together to create a measurement framework that connects your AI implementation directly to your business KPIs.

The Business KPI Connection: Why It Matters

Early in my career, I led a marketing automation implementation that cost $120,000 annually. Six months in, our CFO asked, “What are we getting for our money?”

I had plenty of activity metrics – emails sent, open rates, click rates – but I couldn’t connect those to business outcomes. I couldn’t tell him if the $120,000 was worth it. Baby Katie was out of her depth.

That experience taught me something crucial: measure what matters to the business, not just what’s easy to measure.

Connecting AI Metrics to Business KPIs

Remember in Part 1 when we defined our AI purpose statement? And in Part 2 when we identified our business problems under the “Purpose” section of the 5P framework? Now we’re going to connect those directly to measurement:

1. Map Your AI Purpose to Business KPIs

Start by revisiting your purpose statement. Your statement should have clearly articulated why you’re implementing AI. Now, identify which specific business KPIs this purpose will impact:

AI for content creation:

Customer acquisition cost
Conversion rate
Revenue growth

AI for customer service:

Customer satisfaction
Retention rates
Support cost per customer

AI for data analysis:

Decision-making speed
Forecast accuracy
Revenue per insight

In Part 2 I asked you to complete the sentence: “As a [persona], I [want to], so [that].” The “so that” part should directly connect to these business KPIs.

Doing the work upfront will save you time on the back end. Gather your information, get organized, and use the frameworks to set yourself up for success.

2. Establish Your Business Baselines

In Part 2’s “Performance” section, we talked about defining what success looks like. Here’s where you put that into practice by documenting current performance:

Business metrics: Current performance on the business KPIs you’ve identified
Operational metrics: Current efficiency, quality, and cost metrics for the processes you’re enhancing

Be specific, just like we discussed in the “Performance” section of the 5P framework. “We currently acquire customers at an average cost of $250, with our content marketing channel performing 15% better than other channels” is much better than “Our content marketing works well.”

3. Define Success in Business Terms

Remember when I said measurement is everything? This is where you define exactly what “success” means in terms of your business KPIs:

Customer acquisition cost:

Current: $250 per customer
Target with AI: $200 per customer
Timeframe: 6 months

Support cost per ticket:

Current: $15 per ticket
Target with AI: $9 per ticket
Timeframe: 3 months

Forecast accuracy:

Current: 75% accurate
Target with AI: 90% accurate
Timeframe: 9 months

This connects directly to your “Performance” P from the 5P framework, where we talked about how you’ll know if you have succeeded.

4. Calculate Business-Focused ROI

In Part 2, we discussed the importance of ROI calculation as part of the “Performance” P. Now it’s time to put that into practice:

AI costs: Platform fees (from “Platform” P) + implementation + training (from “People” P)
Business benefits: Direct revenue increases + cost reductions + margin improvements
ROI = (Benefits – Costs) ÷ Costs

For example, a client implemented AI for customer service with this calculation:

Costs: $125,000 (platform + implementation)
Annual benefits: $576,000 (cost savings) + $400,000 (retention value)
First-year ROI: 680%

This connects your “Platform” costs directly to your “Performance” benefits, completing the 5P circle.

Whew! Still with me?

A Simple Business-Aligned AI Measurement Framework

Here’s a streamlined framework that brings together the STEM and 5P concepts for an AI content marketing implementation:

Purpose (from 5P) / Strategy (from STEM):

Implement AI content tools to scale content production and reduce customer acquisition costs

Business KPIs to Impact (Performance from 5P):

Reduce customer acquisition cost from $250 to $200
Increase conversion rate from 2.3% to 3.0%

Operational Metrics to Track (Process from 5P / Tactics from STEM):

Increase content production from 20 to 60 articles/month
Reduce content creation time from 8 to 4 hours per piece
Maintain quality score (minimum 8.5/10)

AI Implementation Metrics (Platform from 5P / Execution from STEM):

AI tool adoption rate among content team
AI enhancement quality (measured by editor revisions needed)

Measurement Plan (Measurement from STEM):

Weekly tracking of operational metrics
Monthly tracking of business KPIs
Quarterly analysis connecting AI metrics to business outcomes

ROI Calculation (Performance from 5P):

Costs: $56,000 (platform + implementation)
Projected annual business impact: $150,000 in reduced acquisition costs
Projected ROI: 168%

Next Steps: Building Your Framework

Revisit your purpose statement from Part 1
Review your 5P analysis from Part 2
Identify which business KPIs your AI should impact (based on your “Purpose”)
Document current performance on those KPIs (baseline for your “Performance”)
Define success in terms of business outcomes (targets for your “Performance”)
Create a chain connecting your “Platform” metrics to your “Performance” metrics
Establish an ROI calculation focused on business impact

In Part 5, I’ll cover specific AI applications across different business functions, with practical examples of these measurement frameworks in action.

What business KPIs are you targeting with your AI implementation?

Reply to this email to tell me, or come join the conversation in our free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

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In this week’s Data Diaries, let’s take a look at the hiring demand for marketers and other industries, part of our regular check-in to see how things are going. We do these checks every month or two.

First, let’s look at the big picture for marketing. As a reminder, these charts are based off data from Indeed.com transmitted to the St. Louis Federal Reserve Bank. They’re an index of hiring demand relative to February 2020, just before the COVID pandemic.

Hiring demand in France and Canada has gone up; France is now above the 2020 benchmark, as is Australia. Both those markets, for marketing jobs, are improving. The remaining economies are declining. In the USA, marketing job demand is testing a new 4-year low. The UK is experiencing new lows as well.

In the USA, the snapshot of careers in demand remains largely unchanged:

What we see is clear: all forms of healthcare are in very high demand, with therapists remaining the highest in demand, 85% above baseline.

Since our last check-in in late February, demand across all categories has dropped by a percentage point or two for nearly every industry.

What do we do with this information?

For job seekers, most major markets remain a difficult place right now. The best advice remains the advice given many times before: jobs through your personal network are likely the best approach. If your current network isn’t producing results, investing some time each day in that along with more traditional job search methods might be fruitful.

There’s an interesting arms race going on in the job seeking world, especially in tech. The prevalence of ghost jobs has made some seekers develop agentic AI solutions (using tools like OpenAI Operator, Browser-Use, Claude Computer Use, etc.) that simply apply for every qualified job. Thus, the signal to noise ratio in public job applications continues to grow. More ghost jobs means more people automating the application process, in something of a vicious cycle.

For everyone thinking about their marketing and careers, it’s abundantly clear where demand is. In the long term, all industries will be impacted by AI and macroeconomic changes, but industries like healthcare will still be predominantly people-focused. If you’re thinking about what your career might look like in a decade, that’s a strong hint about the industry you might be working in.

Finally, though we may not publish the data every week, hiring demand is a good indicator of the economy. Companies don’t hire if things are not looking good economically. It’s one of the many leading indicators that can tell you about trouble in the overall economic picture, along with things like the Baltic Dry Index. Next week, we’ll revisit common leading economic indicators to see how things are going.

Here’s a roundup of who’s hiring, based on positions shared in the Analytics for Marketers Slack group and other communities.

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