Don't Just Guess: Track Gen AI Success with These 7 Marketing KPIs

If you've started using Generative AI (Gen AI), you might be curious how it impacts your business. You know about the benefits, but how can you tell if it's making a difference?

A great way to assess how a Gen AI solution impacts your marketing and sales processes is to check out your key performance indicators (KPIs) and how they have changed since implementing a Gen AI solution, like Product AIdvisor.

While KPIs can vary based on your business focus, here are seven common KPIs and how Product AIdvisor can influence them.

Seven KPIs to monitor with Product AIdvisor

1. Customer Lifetime Value (CLV)

What it means: CLV measures the total revenue you expect from a single customer. While this number varies greatly depending on your field and your products, a good CLV is generally at least three times greater than the cost to acquire the customer.

Why it matters: This metric helps you understand which customer segments will drive the most revenue for your company. This metric is key to seeing how well your team builds strong customer relationships that lead to reliable revenue.

AI impact: Product AIdvisor boosts CLV by offering personalized product recommendations that keep customers coming back. It can identify cross-sell and upsell opportunities, helping your sales and marketing teams deliver targeted offers that maximize the long-term value from each customer.

Implementing AI should increase this metric.

2. Customer Acquisition Cost (CAC)

What it means: CAC measures the cost of acquiring a new customer. This factors in all associated costs like sales and marketing expenses.

Why it matters: Monitoring this metric can help you better understand what activities and strategies work best for acquiring new customers.

AI impact: Product AIdvisor helps marketing teams personalize their marketing efforts and target audiences efficiently with real-time insights into a lead’s behavior and preferences. In turn, sales reps can leverage those AI-powered insights to engage with prospects more effectively, streamlining the sales process and reducing the time to close deals.

Implementing AI should decrease this metric.

3. Retention rate

What it means: This metric measures the percentage of customers who continue buying your products or services. The average retention rate in the manufacturing industry is around 67%.

Why it matters: Acquiring customers is only half the battle. Analyzing this metric helps you understand your ability to retain customers. If your retention rates are high, it’s a good sign that your products or services are well-received and your customers are loyal.

AI impact: Product AIdvisor improves retention by aligning marketing and sales to deliver consistent, personalized experiences. Marketing teams can use Product AIdvisor to craft targeted campaigns that keep customers engaged, while sales teams leverage AI-powered insights to provide timely, relevant solutions. By helping customers discover products that fit their needs, Product AIdvisor encourages repeat purchases and strengthens customer relationships, building long-term loyalty.

Implementing AI should increase this metric.

4. Conversion rate

What it means: This metric measures the percentage of leads that convert into customers. The average conversion rate in the manufacturing industry is around 2%.

Why it matters: Analyzing this KPI reveals where your leads are dropping off and how you can improve conversions. It’s a critical measure of your sales and marketing strategies.

AI impact: Product AIdvisor improves conversion rates by proactively engaging with customers throughout their buying journey. It reduces cart abandonment by offering instant assistance, answering questions in real time, and providing personalized product recommendations that keep customers moving forward in the sales process.

Implementing AI should increase this metric.

5. Customer Satisfaction Score (CSAT)

What it means: This metric measures how satisfied customers are with your services or products. The average CSAT score typically ranges between 75% to 85%.

Why it matters: High CSAT scores are key to customer retention, positive word-of-mouth, and long-term business success. It’s a direct indicator of the quality of services or products you’re providing.

AI impact: Product AIdvisor improves customer satisfaction by delivering personalized recommendations, helping customers quickly find what they need, and ensuring a smooth buying experience. By effectively addressing customer needs, Product AIdvisor contributes to higher CSAT scores.

Implementing AI should increase this metric.

6. Marketing-qualified lead (MQL) to sales-qualified lead (SQL) rates

What it means: This metric measures how many MQLs convert into SQLs. Average MQL to SQL rates vary, but the general range is from 10% to 30%. For manufacturers, this number is around 26%.

Why it matters: You can use this metric to understand the effectiveness of your lead qualification processes. A high MQL to SQL rate means your lead generation efforts are working, and your marketing and sales teams are working together to target the right audiences.

 AI impact: Product AIdvisor engages leads in real time with personalized interactions and empowers sales and marketing teams with in-depth product knowledge and insights. This helps both teams better address specific lead needs, leading to more effective targeting and communication. By better understanding products and customer needs, teams can move leads through the funnel faster, improving the MQL to SQL conversion rate.

Implementing AI should increase this metric.

7.      Total revenue growth

What it means: This metric measures the total amount of sales across all your products or services.

Why it matters: This is the ultimate measure of your company’s performance. This metric reflects your company’s overall performance and shows how well you meet business objectives.

AI impact: Product AIdvisor helps grow your revenue by identifying cross-sell and upsell opportunities and increasing average order value with targeted recommendations. It identifies additional revenue streams by helping customers discover new products based on their behavior and preferences. With Product AIdvisor, every customer interaction contributes to your bottom line.

Implementing AI should increase this metric.

Use AI to improve your KPIs today

By measuring these seven metrics, you’ll see how Product AIdvisor is helping your sales and marketing processes.

Keep in mind that metrics may fluctuate due to seasonal trends, shifts in customer behavior, or other external factors, so it's important to review them consistently.

Regularly reviewing these KPIs will help you monitor your company’s performance and make informed decisions for continued improvement.

See how Product AIdvisor can improve these metrics today!