Framework for Sales Teams to Assess the Quality of AI Outputs

As AI continues to make headway into sales processes, teams are faced with a new challenge.

Making sure that AI content meets professional standards.

AI excels at creating new content quickly, but that content needs to be carefully reviewed and assessed to ensure it helps you toward your sales goals.

The key is to have a systematic method for assessing outputs.

TLDR: 

• The goal: Evaluate the quality of AI-generated sales copy
• The tactic: Use an AI evals framework for sales
• The result: Confirmation that AI sales copy meets your standards

Step 1: Check accuracy

When you’re using AI-generated content in sales, getting your facts right is critical.

Look at the facts and numbers in your AI content. Do the outputs match reliable sources, industry reports, or your own findings? If not, you can add correct, relevant data in the prompt.

At the same time, pay attention to any statistics or research the AI mentions. For instance, if the AI cites a study saying “73% of companies are adopting AI in sales”, check that (a) the study exists and (b) the data is recent.

And check any company specifics. Does the AI describe your products, services, and capabilities accurately? Can it explain product features and pricing? Is it using social proof appropriately?  

While AI is extremely helpful, it can at times mix up facts or provide plausible yet incorrect info. Fact-checking while you’re fine-tuning and debugging your prompt will save you from awkward conversations down the road.

Step 2: Analyze consistency

After checking the AI’s accuracy, your next step is to make sure everything flows logically and tells a consistent story. Think of it like a well-rehearsed presentation where every part smoothly connects to the next.

Start by reading your sales copy from start to finish.

Are there any contradictions? Does the AI suggest one thing only to recommend something else later on?

Also, pay attention to how AI uses technical terms. Does it call you a “platform” in one sentence only to call you a “tool” in the next? Does it refer to the same feature with different names?

And check if the content reflects what your company actually delivers. AI was designed to fulfill requests to the best of its ability, which might lead to it making promises that you can’t meet. For instance, if you don’t offer 24/7 customer support, the AI shouldn’t imply you do.

Ultimately, while reviewing content, you think to look at it from your customer’s shoes. Can they follow the logic easily? Do points build on each other? Will it guide them to the next step of their customer journey?

Step 3: Check brand alignment

Your brand is how clients recognize and remember you. That’s why you need to make sure it speaks like you or your company.

There are a couple of ways to do this:

• Designing your own email framework
• Feeding it a dataset of your own emails
• Having AI scrape your website

Once you have some sales copy in hand, look at the tone. Does it match how you usually talk? If you’re known for being practical and straightforward, yet the copy is flowery or technical, it’s a mismatch.

Next, check if the copy aligns with your positioning. If you position yourself as an enterprise solution yet the social proof uses examples more suitable to start-ups and SMBs, it’s a mismatch.

This is also true if you want to highlight specific values like sustainability or innovation, or fine-tune product descriptions and messaging.

Step 4: Define AI evaluation metrics (“AI evals”)

If you want to continuously assess AI quality (hint: you should), you need a systematic way to measure performance.

That’s where AI evaluation metrics (or AI evals) come in.

Start by creating a scorecard for different types of AI sales copy. For instance, if you’re using AI for sales emails, you might score them on factors like product accuracy, social proof relevance, and personalization quality. 

To make it easier to see where improvements are needed, measure factors on a scale from 1-5 or 1-10 and decide what’s acceptable.

Maybe you need all pricing descriptions to be a 5 of 5 while product descriptions can get away with 4 of 5? These standards will make it easier for your team to make consistent decisions.

You should also track how content performs over type. Are there certain types that score lower consistently? Maybe product descriptions aren’t always spot on and need revisions?

And don’t forget to track when and how AI sales copy fails. Record common mistakes or problems, such as difficulties explaining pricing or poor word choice. This will help you develop better review processes.

Step 5: Confirm client-specific relevance

Even perfect AI sales copy that’s accurate and well-written won’t get results if it doesn’t speak to your customer’s needs.

Start by checking if the AI copy addresses your customer’s specific industry challenges. If you’re selling to sales teams, does the content speak to sales issues like pipeline leakage or insufficient follow-ups? Or if you’re selling to healthcare businesses, does it speak to healthcare issues like patient data security and regulatory compliance?

That’s why you need to make sure examples and use cases match your customer’s situations.

You should also confirm if the sales copy matches where customers are at in their journey, as well as their scale, budget, and complexity.

Result

While there are a few extra necessities like reviewing the technical specifics and compatibility or ensuring that all compliance requirements are met, this 5-step framework gives you a practical way to improve AI outputs.

You might also consider maintaining a library of approved AI content and a clear path for escalating questionable outputs.

And to quickly recap, here are a few red flags to watch out for when assessing AI outputs:

• Inconsistent formatting or styling
• Non-specific recommendations
• Missing or incorrect details
• Outdated information or references
• Inappropriate wording or word choice
• Unsubstantiated claims

Just keep in mind that while AI is a powerful tool, it still needs some human oversight to maximize its effectiveness.