January 15, 2026
How Shopify brands should evaluate AI CX vendors
Every Shopify brand is hearing the same pitch. AI that will transform your customer experience. Agentic automation that resolves tickets instantly. CDPs that unify your data. The acronyms pile up faster than your inbox.
But here's what matters. According to Gartner, 85% of customer service leaders will pilot conversational AI in 2025. And 77% feel executive pressure to deploy these tools. That pressure creates urgency. Urgency creates poor decisions.
The vendors selling you on buzzwords aren't thinking about your Shopify store's real challenges. They're thinking about their demo script.
A practical framework for cutting through the noise
Before you evaluate any AI CX vendor, answer these five questions.
1. Does the AI work with your Shopify data natively?
Most vendors require complex integrations that take months to deploy. Native Shopify integration means your customer's order history, lifetime value, and preferences flow directly into every AI interaction. When a customer asks about their order, the AI should already know the answer.
Brands using platforms with native Shopify integration report 87% resolution rates for order-related inquiries and launch in days instead of months.
2. Can you measure resolution, not just deflection?
Deflection sounds like a win until you realize it measures how many customers you successfully avoided helping. Resolution measures how many customers actually got their problem solved.
Gladly pro tip.
The market has created a false choice. Most AI vendors measure success by how many customers they push away (deflection) rather than how many customers they serve well (resolution that builds a relationship). This thinking leads to incomplete business outcomes.
Buyers who understand cost pressure are especially vulnerable to this trap. They see impressive deflection numbers and think, “Great, we’ll save money.” What they don’t see is the long-term cost: customers who feel dismissed, loyalty that erodes, and lifetime value that never materializes.
The AI customer service market is growing at 25.8% annually and is projected to reach $47.82 billion by 2030. The vendors winning that market are the ones proving resolution, not deflection.
Ask any vendor this question directly. What percentage of AI interactions result in complete resolution without human handoff? If they can't answer with specifics, move on.
3. How does the AI handle escalation?
The best AI knows when to step back. When a customer is frustrated or the issue is complex, seamless handoff to a human makes the difference between a loyal customer and a lost one.
Gartner research found that 64% of consumers would rather companies didn't use AI for customer service. The issue isn't the technology. It's implementation that traps customers in loops without human options.
4. What's the true cost per resolution?
AI interactions cost roughly $0.50 versus $6.00 for human interactions. That 12x difference sounds compelling until you factor in failed resolutions that create repeat contacts, escalations, and lost customers.
Calculate total cost of ownership. Include implementation time, integration complexity, ongoing training, and the hidden cost of customers who abandon after poor AI experiences.
5. Does the vendor treat customers as people or tickets?
This isn't philosophical. It's operational.
Ticket-based systems create duplicate records, fragmented conversations, and agents who ask customers to repeat information across channels. People-centered platforms maintain one continuous conversation history regardless of channel.
Allbirds achieved an 87% resolution rate and 41% reduction in handle time by moving from tickets to conversations. Tecovas reached a 55% resolution rate on product help and recommendation questions.
Gladly helps us connect with high-intent shoppers in the moment, guide them to the right products, and drive immediate revenue, all while laying the groundwork for long-term loyalty.
Krystal Kay Cortez
CX Sr. Ops Manager, Tecovas
What to ignore
Some vendor claims should trigger immediate skepticism.
"100% automation" is a red flag. Even the most advanced AI cannot handle every customer scenario. Vendors promising complete automation are either misrepresenting their technology or planning to frustrate your customers.
"Works with any platform" usually means "works poorly with every platform." Shopify-specific capabilities matter. Your vendor should understand commerce workflows, not just customer service workflows.
"AI-powered" without specifics tells you nothing. Every vendor claims AI now. Ask what kind. Ask how it was trained. Ask how it improves over time. If they can't explain it clearly, they probably don't understand it themselves.
When you meet with your next AI CX vendor, bring this evaluation checklist
Integration depth
Does it connect natively to Shopify without middleware?
Can it access order history, returns, and customer preferences in real time?
How long until you're live? Days or months?
Resolution metrics
What's the actual resolution rate, not containment or deflection?
Can they show you before and after data from similar Shopify brands?
How do they measure customer satisfaction after AI interactions?
Escalation quality
How does the AI decide when to involve a human?
Does the human receive full conversation context?
Can customers request human help at any point?
Total cost clarity
What's the cost per resolution, not just per interaction?
What implementation and training costs should you expect?
How does pricing scale with volume?
Customer data philosophy
Is the system built around tickets or around people?
Can you see a customer's full history across all channels in one view?
Does the AI use customer context to personalize responses?
The bottom line
The AI CX market is moving fast. Shopify brands that choose vendors based on buzzwords will spend 2026 managing implementations that don't deliver. While 72% of their consumers will spend more with brands that provide great experiences.
That's the only statistic that matters. Every vendor evaluation should start with one question.
“Will this make my customers want to come back?”
Frequently asked questions
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