There is no shelf quite so sturdy as the one trying to accommodate all the marketing technology (martech) available to today's marketing teams. The reasons for this abundance are manyfold, but the fact is that the number of available martech options has been exponentially growing for the past 10-15 years.

On the other hand, completely disassociated with the number of options available is the inefficiency in integrating and using martech, with CMOs ending up wasting a majority of their tech investments.

A not-so-new solution that emerges as a lifeguard to marketing teams is conversational AI, helping them with personalised customer journeys, which is what makes companies stay competitive and drastically increase revenue.

In this article, we’re not going to go into technical detail on how to incorporate it, just highlight the effect its integration and proper utilisation will have on your customers and growth.

Martech Stack Underutilisation Issues

Let’s start with the number one problem of the current marketing tech used within companies: underutilisation. Perhaps you’ll recognise your own experience as similar.

While marketing tech has been, or rather, is supposed to be built to help marketers navigate their complex data-abundant surroundings, their fate is somewhat different. According to numerous studies, companies report shocking underutilisation numbers, which ultimately causes major investment failures:

• Only 34% of marketers say their tech stack is very successful at meeting their goals.
• About two-thirds admit their stacks are only somewhat successful or unsuccessful.
• Studies show martech utilisation averages just 33%, meaning most of the investment goes unused.
• One audit found 44% of tools are never used, rising to 56% when including underused tools.
• Nearly one in three marketers worry they’re not making full use of their current stack’s capabilities.

Companies seem to be investing large portions of their tech budget in different complex tools, but end up using only a couple of features, ultimately wasting most of that budget. What is more, the marketing teams of today are faced with 230% more data than they were in 2020, but lack the time to analyse it.

Tools with overlapping features, unused premium capabilities, inactive user licenses: a company with, let’s say, £250 million in annual revenue, can lose nearly £4 million each year. Meaning - this issue cannot be overlooked.

Successfully Integrating Conversational AI

We mentioned in the intro that the way to escape this martech mayhem is with conversational AI. While you may, and rightfully so, wonder what makes conversational AI different from all the existing martech (and what gives you a guarantee that you won’t end up with yet another dusty and unused tool), before you start using it, you need to set the ground.

This means two things: it needs to be deployed strategically, and it needs to integrate with the rest of the stack, thus bridging the gap between each separate app and tool.

Conversational AI needs to integrate with your existing CRM and similar tools. Only then does it live on all of its promises, as it uses, unifies and makes sense of your data, thus enabling a hyper-personalised customer journey - ultimately driving revenue and increasing Customer Lifetime Value (CLTV).

The strategic approach to implementation means that AI will not be used for the sake of AI. Everyone has it, you should too, and you’ll plan later on how and where to use it - wrong. Firney’s approach to conversational commerce implementation is problem-focused, not tool-focused. Start with an outcome, e.g., "We need to shorten our sales cycle”, and then architect an AI solution that solves it.

Practical Uses of Conversational Commerce

In this section, we’ll not only describe how conversational AI can be used to escape the martech mayhem, or rather, to resolve it, but we will also once again highlight the importance of proper integration, as it cannot work without it.

Here’s what that looks like in practice:

1. A 24/7 sales engine through conversational commerce

Conversational AI can act as a full-time sales representative whose focus is not to reply to FAQ, but to help customers complete purchases directly within the chat. By connecting to your e-commerce platform, inventory systems, and product catalogue, the AI has access to real-time stock levels and product data, guiding the customer from question to checkout in a single interaction.

2. Hyper-personalisation

The real advantage of conversational AI lies in its ability to make every interaction feel personal, even when engaging with thousands of customers. Through bi-directional integration with your CRM or Customer Data Platform, it reads a customer’s history, behaviours, and preferences, and updates new data in real time. This creates a continuously evolving customer profile, provides customers with the personalised experience they desire, and unavoidably increases CLTV.

3. Recovering lost revenue before it’s lost

Abandoned carts are one of the biggest silent killers of online sales and one conversational AI can easily solve. Integrated directly into your e-commerce platform, AI agents can detect when a customer drops off and automatically reach out, which results in recovering up to 35% of potential lost sales. Whether through chat, email, or SMS, this type of automated follow-up feels helpful, not pushy.

4. Automating routine tasks, freeing up human time

Finally, conversational AI brings much-needed efficiency. By integrating with your internal knowledge base, ticketing system, or ERP, it can independently handle up to 80% of common customer inquiries, from order tracking and return requests to basic troubleshooting. That means your human agents can focus on higher-value tasks, while customers get faster, consistent support.

Conclusion

The path out of the martech chaos isn’t about adding another tool to the stack. It’s about making the tools you already have work better together.

When done right, conversational AI becomes that missing link, the element that unifies systems, connects data, and brings meaning to every customer interaction. It’s not about automation for the sake of efficiency. It’s about using technology to finally achieve what marketers have been aiming for all along: understanding customers in real time, responding with relevance, and proving tangible impact.

What we’ve seen time and again with our clients is that when conversational AI is strategically deployed and properly integrated, it transforms the way marketing teams operate. It helps CMOs turn complex martech ecosystems into cohesive, intelligent systems that not only simplify operations but also drive measurable growth.

If you’re looking to make sense of your own martech stack and see how conversational AI could fit into it, that’s exactly the kind of challenge we like solving at Firney. Because in the end, it’s not about having more technology, but about finally making it work the way you need it to.