Your CRM's AI Has a Meter. Do You Know Where It Is?

As CRM vendors fold AI into seat prices, credit pools and per-action fees, sales leaders need five questions to put a real number on what CRM AI costs before their next renewal.

AI Won’t Kill A/B Testing, but Marketers Must Redefine What They Compare

Success will depend on how well marketers can design, evaluate, and optimize customer experiences.

AI Can Make the Purchase, But Companies Still Need to Earn the Loyalty

As personal AI agents take on more purchasing and service interactions, companies must earn loyalty through reliable, personalized experiences and measure success by customer lifetime value.

Before a CRM Agent Acts, Check Which Customer It Has Found

A CRM agent needs more than a plausible match: it must know whose records it has joined, whether those facts are current, and which action the system permits for this request.

The Outreach Success Rate That Flatters the Team

Outreach conversations closed can't stand as a metric on its own.

The Mobile CRM Screen Should Start with the Next Decision

A decision-centered mobile CRM should give field salespeople the context to act, capture the essential outcome, and preserve enough information for the next owner to complete the handoff.

The First 15 Minutes of a Lead: Where Website Enquiries Get Lost

Following a test enquiry from the website into the CRM helps small service businesses uncover missing information, unclear ownership, and delays that customers experience long before anyone replies.

Operational Minimalism: An Essential Discipline for AI-Centric CX Organizations

The payoff from operational minimalism is immediate: Employees are empowered, errors decline, cost to serve decreases, and customers get the service they expect. (Featured on SmartCustomerService.com.)

From System of Record to System of Action: Using Automation and AI to Unlock CRM

Here's what a real-world CRM pipeline looks like, combining AI judgment with RPA and API-driven action to move abuse cases from inception to fully resolved without human intervention.

From Customer Record to Connected Conversation

After decades of talking about omnichannel, there is a straightforward way to judge whether it is working.

The Missing Middle: 7 Ways Marketers Can Fix the Biggest Gap in Their Martech Stacks

Many organizations still struggle to deliver timely, relevant customer experiences because they're missing the middle layer.

The Rise of the AI Customer: How Service Leaders Should Prepare Now

Organizations should selectively enable AI-driven interactions while implementing appropriate risk mitigation measures. (Featured on SmartCustomerService.com.)

The SaaS Model Was Built for Humans. Agents Don't Care.

Agents need to get information themselves, synthesize it, and have the agency to act. Software that can't support that isn't ready for what's coming.

The CRM Says Resolved, But Voice AI Says Otherwise

Voice AI can detect patterns that single-call analysis never could. (Featured on SmartCustomerService.com.)

Why the Best Growth Strategy Starts with a Product People Want to Share

Customer recommendations are one of the biggest drivers of company success.

The Hidden Cost of Optimizing E-Commerce One Decision at a Time

Understanding customers is no longer enough if the business can't connect that understanding to the decisions that shape the experience they actually receive.

If the Email Bounces, Do You Still Have the Lead?

When a capture form treats its notification email as the delivery mechanism rather than as an alert about a record that already exists, a wrong address or a rejected message erases the enquiry with no trace, and the audit that finds those losses runs against the mail log rather than the CRM.

Your CRM Isn't Obsolete. It's the Backbone of Your Agentic System

To realize the full value of agentic AI, CRM must remain a living, connected, and continuously improving foundation for transformation.

The Squeaky Wheel Might Get the Oil, But You Should Really Be Worried About Your Quietest Customers

Your CRM views quietly dissatisfied customers in the same way as your genuinely satisfied customers.

Enterprise AI Has a Prompting Problem

Most companies are focused on whether their AI gives them the right answer. Perhaps the harder question is whether they'd know if it didn't.